From 3215422b8bf68c3e0fed09cef2ebe978e0fc4548 Mon Sep 17 00:00:00 2001 From: rchiodo <19672699+rchiodo@users.noreply.github.com> Date: Fri, 18 Sep 2026 06:11:13 +0000 Subject: [PATCH] Update benchmark results from workflow runner --- latest-results.md | 326 +- ...lsp-mypy-20260918T060520Z-responses.jsonl} | 4 +- ....json => pylsp-mypy-20260918T060520Z.json} | 2756 +++---- ... pyrefly-20260918T060520Z-responses.jsonl} | 52 +- ...26Z.json => pyrefly-20260918T060520Z.json} | 6750 +++++++++-------- ... pyright-20260918T060520Z-responses.jsonl} | 0 ...26Z.json => pyright-20260918T060520Z.json} | 2740 +++---- latest-results/summary-20260917T060626Z.csv | 132 - latest-results/summary-20260918T060520Z.csv | 132 + ...26Z.json => summary-20260918T060520Z.json} | 18 +- ...060626Z.md => summary-20260918T060520Z.md} | 320 +- ...nl => ty-20260918T060520Z-responses.jsonl} | 50 +- ...T060626Z.json => ty-20260918T060520Z.json} | 3106 ++++---- 13 files changed, 8207 insertions(+), 8179 deletions(-) rename latest-results/{pylsp-mypy-20260917T060626Z-responses.jsonl => pylsp-mypy-20260918T060520Z-responses.jsonl} (100%) rename latest-results/{pylsp-mypy-20260917T060626Z.json => pylsp-mypy-20260918T060520Z.json} (90%) rename latest-results/{pyrefly-20260917T060626Z-responses.jsonl => pyrefly-20260918T060520Z-responses.jsonl} (99%) rename latest-results/{pyrefly-20260917T060626Z.json => pyrefly-20260918T060520Z.json} (91%) rename latest-results/{pyright-20260917T060626Z-responses.jsonl => pyright-20260918T060520Z-responses.jsonl} (100%) rename latest-results/{pyright-20260917T060626Z.json => pyright-20260918T060520Z.json} (90%) delete mode 100644 latest-results/summary-20260917T060626Z.csv create mode 100644 latest-results/summary-20260918T060520Z.csv rename latest-results/{summary-20260917T060626Z.json => summary-20260918T060520Z.json} (89%) rename latest-results/{summary-20260917T060626Z.md => summary-20260918T060520Z.md} (61%) rename latest-results/{ty-20260917T060626Z-responses.jsonl => ty-20260918T060520Z-responses.jsonl} (80%) rename latest-results/{ty-20260917T060626Z.json => ty-20260918T060520Z.json} (89%) diff --git a/latest-results.md b/latest-results.md index 15a039a..7f3ccd4 100644 --- a/latest-results.md +++ b/latest-results.md @@ -1,8 +1,8 @@ # Python LSP Benchmark Comparison -Generated from `results/bench-servers/summary-20260917T060626Z.json` +Generated from `results/bench-servers/summary-20260918T060520Z.json` -- Generated at: 20260917T060626Z +- Generated at: 20260918T060520Z - Config: `github-releases` - Servers: pyright, ty, pyrefly, pylsp-mypy - Baseline server: Pyright (pyright) @@ -13,7 +13,7 @@ Generated from `results/bench-servers/summary-20260917T060626Z.json` | Server | Version | Source | | --- | --- | --- | | Pyright | 1.1.414 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/pyright/1.1.414/package/dist/pyright-langserver.js | -| Ty | 0.0.81 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.81/ty-x86_64-unknown-linux-gnu/ty | +| Ty | 0.0.82 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.82/ty-x86_64-unknown-linux-gnu/ty | | Pyrefly | 1.3.1 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/pyrefly/venv/bin/pyrefly | | pylsp-mypy | 1.15.0 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/pylsp-mypy/venv/bin/pylsp | @@ -30,10 +30,10 @@ Generated from `results/bench-servers/summary-20260917T060626Z.json` | Server | Success | Benchmarks | Wall clock ms | Avg measured ms | Measured requests | Non-empty % | Failed points | | --- | --- | --- | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 6 | 4893.94 | 3.96 | 150 | 100% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | no | 8 | 15742.33 | 33.47 | 205 | 97% | 2 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 6 | 39362.93 | 75.06 | 150 | 97% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 6 | 257590.03 | 378.08 | 150 | 80% | 5 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 6 | 5143.02 | 4.22 | 150 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | no | 8 | 16463.60 | 36.20 | 205 | 97% | 2 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 6 | 37971.23 | 67.61 | 150 | 97% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 6 | 220250.41 | 370.24 | 150 | 80% | 5 | *Wall clock ms includes server startup, warmup iterations, and shutdown — but excludes one-time environment creation and dependency installation.* @@ -41,10 +41,10 @@ Generated from `results/bench-servers/summary-20260917T060626Z.json` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 396.37 | 3.37 | 5 | 25 | 100% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 1135.26 | 22.68 | 5 | 25 | 100% | 0 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 4702.15 | 82.68 | 5 | 25 | 100% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 7787.40 | 114.15 | 5 | 25 | 80% | 1 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 534.85 | 4.11 | 5 | 25 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 1274.19 | 24.95 | 5 | 25 | 100% | 0 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 4502.03 | 73.39 | 5 | 25 | 100% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 7881.47 | 111.48 | 5 | 25 | 80% | 1 | ### dataframe completion @@ -52,10 +52,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 1.73 | 1.93 | 100% | 223.00 | +22.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 6.85 | 12.24 | 100% | 201.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 85.70 | 340.01 | 100% | 250.00 | +49.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 215.30 | 451.37 | 100% | 188.00 | -13.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 1.70 | 1.95 | 100% | 223.00 | +22.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 5.50 | 8.60 | 100% | 201.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 89.08 | 341.83 | 100% | 250.00 | +49.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 207.64 | 433.52 | 100% | 188.00 | -13.00 | pass | ### dataframe describe hover @@ -63,10 +63,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.33 | 0.38 | 100% | 4232.00 | +213.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 1.09 | 1.33 | 100% | 4019.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 5.53 | 8.03 | 100% | 3182.00 | -837.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 182.41 | 186.40 | 100% | 4134.00 | +115.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.32 | 0.35 | 100% | 4232.00 | +213.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 1.12 | 1.32 | 100% | 4019.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 2.33 | 2.63 | 100% | 3182.00 | -837.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 177.83 | 178.98 | 100% | 4134.00 | +115.00 | pass | ### summarize definition @@ -74,10 +74,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.22 | 0.24 | 100% | 1.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.23 | 0.26 | 100% | 1.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.40 | 0.46 | 100% | 1.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 1.05 | 1.10 | 100% | 1.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.20 | 0.21 | 100% | 1.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.22 | 0.25 | 100% | 1.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.41 | 0.45 | 100% | 1.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 1.05 | 1.08 | 100% | 1.00 | 0.00 | pass | ### edit array then complete (edit+completion) @@ -85,10 +85,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 4.13 | 4.34 | 0% | 0.00 | -168.00 | fail (10) | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 10.78 | 11.35 | 100% | 168.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 20.90 | 27.80 | 100% | 149.00 | -19.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 370.53 | 453.48 | 100% | 168.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 4.15 | 4.26 | 0% | 0.00 | -168.00 | fail (10) | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 12.47 | 14.02 | 100% | 168.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 28.55 | 77.89 | 100% | 149.00 | -19.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 328.39 | 459.82 | 100% | 168.00 | 0.00 | pass | ### edit array then hover (edit+hover) @@ -96,10 +96,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 1.06 | 2.97 | 100% | 2546.00 | +2268.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 3.76 | 3.91 | 100% | 267.00 | -11.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 34.53 | 36.47 | 100% | 278.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 167.85 | 169.34 | 100% | 5662.00 | +5384.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 4.57 | 6.26 | 100% | 2546.00 | +2268.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 5.85 | 5.89 | 100% | 267.00 | -11.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 31.53 | 34.60 | 100% | 278.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 166.72 | 168.28 | 100% | 5662.00 | +5384.00 | pass | ### Result Differences @@ -112,10 +112,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 259.60 | 2.54 | 5 | 25 | 100% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 272.62 | 3.99 | 5 | 25 | 100% | 0 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 1469.45 | 14.03 | 5 | 25 | 100% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 8045.82 | 182.14 | 5 | 25 | 100% | 0 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 259.77 | 2.60 | 5 | 25 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 270.56 | 4.01 | 5 | 25 | 100% | 0 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 1482.86 | 13.72 | 5 | 25 | 100% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 7942.52 | 178.10 | 5 | 25 | 100% | 0 | ### queryset completion @@ -123,10 +123,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 4.70 | 7.37 | 100% | 10.00 | 0.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 4.85 | 7.17 | 100% | 261.00 | +251.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 16.67 | 64.64 | 100% | 15.00 | +5.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 224.94 | 694.83 | 100% | 2.00 | -8.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 4.61 | 7.38 | 100% | 10.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 4.75 | 7.18 | 100% | 261.00 | +251.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 15.68 | 61.12 | 100% | 15.00 | +5.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 226.80 | 676.27 | 100% | 2.00 | -8.00 | pass | ### queryset filter hover @@ -134,10 +134,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.24 | 0.26 | 100% | 46.00 | -11.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.41 | 0.46 | 100% | 298.00 | +241.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.53 | 0.58 | 100% | 57.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 158.86 | 161.94 | 100% | 57.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.23 | 0.25 | 100% | 46.00 | -11.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.43 | 0.45 | 100% | 298.00 | +241.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.55 | 0.61 | 100% | 57.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 157.93 | 161.63 | 100% | 57.00 | 0.00 | pass | ### model definition @@ -145,10 +145,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.20 | 0.21 | 100% | 1.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.32 | 0.41 | 100% | 1.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.39 | 0.43 | 100% | 1.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 1.09 | 1.13 | 100% | 1.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.21 | 0.21 | 100% | 1.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.39 | 0.46 | 100% | 1.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.41 | 0.43 | 100% | 1.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 1.09 | 1.14 | 100% | 1.00 | 0.00 | pass | ### edit queryset then complete (edit+completion) @@ -156,10 +156,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 1.84 | 1.89 | 100% | 83.00 | -21.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 4.51 | 4.96 | 100% | 104.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 25.76 | 28.27 | 100% | 104.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 278.11 | 323.96 | 100% | 143.00 | +39.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 2.75 | 3.82 | 100% | 83.00 | -21.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 4.61 | 4.72 | 100% | 104.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 25.60 | 28.18 | 100% | 104.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 257.36 | 293.91 | 100% | 143.00 | +39.00 | pass | ### edit queryset then hover (edit+hover) @@ -167,10 +167,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.71 | 0.74 | 100% | 858.00 | +775.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 2.89 | 2.94 | 100% | 100.00 | +17.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 38.76 | 44.28 | 100% | 83.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 247.68 | 253.73 | 100% | 71.00 | -12.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.79 | 0.88 | 100% | 858.00 | +775.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 3.19 | 3.23 | 100% | 100.00 | +17.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 37.43 | 45.40 | 100% | 83.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 247.31 | 252.37 | 100% | 71.00 | -12.00 | pass | ### Result Differences @@ -183,10 +183,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 828.39 | 7.69 | 5 | 25 | 100% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 1098.59 | 27.84 | 5 | 25 | 100% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 7863.39 | 140.43 | 5 | 25 | 100% | 0 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 12026.90 | 179.57 | 5 | 25 | 100% | 0 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 852.17 | 8.21 | 5 | 25 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 1295.68 | 32.03 | 5 | 25 | 100% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 8102.19 | 143.67 | 5 | 25 | 100% | 0 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 10800.19 | 150.43 | 5 | 25 | 100% | 0 | ### report dataframe completion @@ -194,10 +194,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 18.41 | 22.19 | 100% | 1000.00 | +728.80 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 77.21 | 263.36 | 100% | 271.20 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 89.91 | 199.14 | 100% | 6.00 | -265.20 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 91.64 | 364.49 | 100% | 16.00 | -255.20 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 18.87 | 22.52 | 100% | 1000.00 | +728.80 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 85.15 | 285.03 | 100% | 271.20 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 89.34 | 356.41 | 100% | 16.00 | -255.20 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 94.12 | 218.52 | 100% | 6.00 | -265.20 | pass | ### dataframe groupby hover @@ -205,10 +205,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.25 | 0.27 | 100% | 329.00 | -21.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.79 | 0.90 | 100% | 350.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 2.44 | 2.63 | 100% | 2759.00 | +2409.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 194.17 | 199.56 | 100% | 301.00 | -49.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.27 | 0.28 | 100% | 329.00 | -21.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.70 | 0.77 | 100% | 350.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 2.40 | 2.54 | 100% | 2759.00 | +2409.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 194.32 | 197.05 | 100% | 301.00 | -49.00 | pass | ### build report definition @@ -216,10 +216,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.23 | 0.29 | 100% | 1.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.24 | 0.25 | 100% | 1.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.45 | 0.54 | 100% | 1.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 1.09 | 1.14 | 100% | 1.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.20 | 0.21 | 100% | 1.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.25 | 0.26 | 100% | 1.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.45 | 0.47 | 100% | 1.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 1.08 | 1.12 | 100% | 1.00 | 0.00 | pass | ### edit dataframe then complete (edit+completion) @@ -227,10 +227,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 16.71 | 17.68 | 100% | 448.00 | +8.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 44.10 | 67.19 | 100% | 256.00 | -184.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 230.56 | 236.24 | 100% | 441.00 | +1.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 809.83 | 1273.60 | 100% | 440.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 16.80 | 17.92 | 100% | 448.00 | +8.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 41.33 | 59.91 | 100% | 256.00 | -184.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 244.31 | 249.95 | 100% | 441.00 | +1.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 653.49 | 1370.85 | 100% | 440.00 | 0.00 | pass | ### edit dataframe then hover (edit+hover) @@ -238,10 +238,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.78 | 0.84 | 100% | 943.00 | -3349.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 2.84 | 2.96 | 100% | 4441.00 | +149.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 9.57 | 10.78 | 100% | 4292.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 186.42 | 190.40 | 100% | 232.00 | -4060.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 4.90 | 4.93 | 100% | 4441.00 | +149.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 12.38 | 15.05 | 100% | 4292.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 26.83 | 83.79 | 100% | 943.00 | -3349.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 184.52 | 186.72 | 100% | 232.00 | -4060.00 | pass | ### Result Differences @@ -254,10 +254,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 357.80 | 2.48 | 5 | 25 | 100% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 809.80 | 17.31 | 5 | 25 | 100% | 0 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 3671.70 | 50.35 | 5 | 25 | 100% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 7226.75 | 127.07 | 5 | 25 | 60% | 2 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 359.68 | 2.64 | 5 | 25 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 800.39 | 17.20 | 5 | 25 | 100% | 0 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 3633.40 | 48.44 | 5 | 25 | 100% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 7220.44 | 126.02 | 5 | 25 | 60% | 2 | ### query completion @@ -265,10 +265,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 3.31 | 7.32 | 100% | 1.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 7.47 | 13.35 | 100% | 1.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 84.05 | 335.21 | 100% | 15.00 | +14.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 223.34 | 409.40 | 100% | 1.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 3.38 | 7.77 | 100% | 1.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 6.78 | 10.93 | 100% | 1.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 83.60 | 333.55 | 100% | 15.00 | +14.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 215.87 | 459.50 | 100% | 1.00 | 0.00 | pass | ### sessionmaker hover @@ -276,10 +276,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.41 | 0.43 | 100% | 10621.00 | +49.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 1.06 | 1.13 | 100% | 15232.00 | +4660.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 1.25 | 1.44 | 100% | 10572.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 331.65 | 338.00 | 100% | 10498.00 | -74.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.41 | 0.42 | 100% | 10621.00 | +49.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.95 | 1.01 | 100% | 15232.00 | +4660.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 1.28 | 1.59 | 100% | 10572.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 332.72 | 340.78 | 100% | 10498.00 | -74.00 | pass | ### mapped class definition @@ -287,10 +287,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.23 | 0.24 | 100% | 2.00 | +1.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.24 | 0.26 | 100% | 1.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.46 | 0.51 | 100% | 1.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 1.19 | 1.34 | 100% | 1.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.21 | 0.23 | 100% | 1.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.22 | 0.23 | 100% | 2.00 | +1.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.42 | 0.47 | 100% | 1.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 1.09 | 1.13 | 100% | 1.00 | 0.00 | pass | ### edit query then complete (edit+completion) @@ -298,10 +298,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.71 | 0.75 | 100% | 17.00 | -21.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 4.37 | 4.78 | 100% | 23.00 | -15.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 39.51 | 40.57 | 0% | 0.00 | -38.00 | fail (10) | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 145.39 | 185.92 | 100% | 38.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.74 | 0.77 | 100% | 17.00 | -21.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 4.82 | 5.32 | 100% | 23.00 | -15.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 40.02 | 40.62 | 0% | 0.00 | -38.00 | fail (10) | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 140.86 | 205.00 | 100% | 38.00 | 0.00 | pass | ### edit session then hover (edit+hover) @@ -309,10 +309,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.49 | 0.52 | 100% | 2246.00 | +1346.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 4.10 | 4.18 | 100% | 958.00 | +58.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 39.67 | 41.49 | 0% | 0.00 | -900.00 | fail (10) | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 97.16 | 105.77 | 100% | 900.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.52 | 0.55 | 100% | 2246.00 | +1346.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 4.39 | 4.42 | 100% | 958.00 | +58.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 40.38 | 40.53 | 0% | 0.00 | -900.00 | fail (10) | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 92.86 | 108.30 | 100% | 900.00 | 0.00 | pass | ### Result Differences @@ -326,10 +326,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 2730.05 | 4.89 | 5 | 25 | 100% | 0 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 15913.06 | 114.45 | 5 | 25 | 80% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 5401.79 | 169.92 | 5 | 25 | 80% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 221534.85 | 1587.86 | 5 | 25 | 40% | 2 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 2709.42 | 4.59 | 5 | 25 | 100% | 0 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 15992.37 | 110.40 | 5 | 25 | 80% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 5581.13 | 177.48 | 5 | 25 | 80% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 184246.25 | 1559.35 | 5 | 25 | 40% | 2 | ### classifier pipeline completion @@ -337,10 +337,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 11.58 | 12.78 | 100% | 776.00 | +653.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 50.67 | 77.69 | 100% | 123.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 152.87 | 156.82 | 100% | 2.00 | -121.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 836.29 | 3344.21 | 100% | 15.00 | -108.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 10.80 | 11.98 | 100% | 776.00 | +653.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 52.88 | 84.92 | 100% | 123.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 146.86 | 152.52 | 100% | 2.00 | -121.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 863.10 | 3451.47 | 100% | 15.00 | -108.00 | pass | ### pipeline hover @@ -348,10 +348,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.21 | 0.22 | 100% | 48.00 | +14.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.23 | 0.26 | 100% | 7.00 | -27.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.47 | 0.55 | 100% | 34.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 2846.33 | 2909.71 | 0% | 0.00 | -34.00 | fail (10) | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.22 | 0.22 | 100% | 48.00 | +14.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.23 | 0.26 | 100% | 7.00 | -27.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.48 | 0.53 | 100% | 34.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 2770.92 | 2839.83 | 0% | 0.00 | -34.00 | fail (10) | ### auto tokenizer definition @@ -359,10 +359,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.22 | 0.23 | 100% | 1.00 | 0.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.27 | 0.29 | 100% | 1.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.48 | 0.67 | 100% | 1.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 2229.58 | 2274.33 | 100% | 1.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.22 | 0.22 | 100% | 1.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.27 | 0.29 | 100% | 1.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.44 | 0.52 | 100% | 1.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 2224.23 | 2259.46 | 100% | 1.00 | 0.00 | pass | ### edit prediction then complete (edit+completion) @@ -370,10 +370,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 2.54 | 2.65 | 0% | 0.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 6.26 | 17.14 | 0% | 0.00 | 0.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 6.75 | 8.02 | 100% | 23.00 | +23.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 7.72 | 9.29 | 0% | 0.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 2.71 | 2.80 | 0% | 0.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 5.94 | 6.06 | 100% | 23.00 | +23.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 6.90 | 8.96 | 0% | 0.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 13.52 | 26.37 | 0% | 0.00 | 0.00 | pass | ### edit tokenizer then hover (edit+hover) @@ -381,10 +381,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 5.63 | 5.74 | 100% | 7.00 | -23.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 6.61 | 22.64 | 100% | 33.00 | +3.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 512.91 | 546.57 | 100% | 30.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | no | 2707.97 | 2737.51 | 0% | 0.00 | -30.00 | fail (10) | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 5.73 | 5.89 | 100% | 7.00 | -23.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 10.36 | 28.96 | 100% | 33.00 | +3.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 491.31 | 518.60 | 100% | 30.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | no | 2652.00 | 2674.70 | 0% | 0.00 | -30.00 | fail (10) | ### Result Differences @@ -397,10 +397,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 321.72 | 2.79 | 5 | 25 | 100% | 0 | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 1579.67 | 9.28 | 5 | 25 | 100% | 0 | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 881.55 | 12.92 | 5 | 25 | 100% | 0 | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 5131.83 | 116.81 | 5 | 25 | 100% | 0 | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 427.13 | 3.16 | 5 | 25 | 100% | 0 | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 1560.39 | 9.30 | 5 | 25 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 900.20 | 14.26 | 5 | 25 | 100% | 0 | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 4857.54 | 102.83 | 5 | 25 | 100% | 0 | ### request args completion @@ -408,10 +408,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 6.07 | 10.60 | 100% | 14.00 | 0.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 6.25 | 9.07 | 100% | 467.00 | +453.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 56.00 | 184.05 | 100% | 487.80 | +473.80 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 95.80 | 161.84 | 100% | 1.00 | -13.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 4.69 | 8.81 | 100% | 14.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 6.53 | 9.17 | 100% | 467.00 | +453.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 63.68 | 183.47 | 100% | 487.80 | +473.80 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 68.68 | 116.51 | 100% | 1.00 | -13.00 | pass | ### client session hover @@ -419,10 +419,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.22 | 0.24 | 100% | 7.00 | -19.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.52 | 0.59 | 100% | 26.00 | 0.00 | pass | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 5.34 | 18.56 | 100% | 167.00 | +141.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 151.61 | 198.46 | 100% | 359.00 | +333.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.21 | 0.23 | 100% | 7.00 | -19.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.52 | 0.62 | 100% | 26.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 5.25 | 18.19 | 100% | 167.00 | +141.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 110.69 | 235.70 | 100% | 359.00 | +333.00 | pass | ### client references @@ -430,10 +430,10 @@ Method: `textDocument/references` | Server | Success | Mean ms | P95 ms | Non-empty % | References found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.32 | 0.34 | 100% | 2.00 | 0.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 0.58 | 0.71 | 100% | 2.00 | 0.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 0.79 | 0.95 | 100% | 2.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 4.08 | 5.08 | 100% | 2.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.34 | 0.35 | 100% | 2.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 0.68 | 0.75 | 100% | 2.00 | 0.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 0.76 | 0.88 | 100% | 2.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 20.40 | 62.90 | 100% | 2.00 | 0.00 | pass | ### edit response then complete (edit+completion) @@ -441,10 +441,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.59 | 0.62 | 100% | 32.00 | -173.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 4.44 | 5.19 | 100% | 225.00 | +20.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 4.84 | 6.02 | 100% | 205.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 94.40 | 96.61 | 100% | 57.00 | -148.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.56 | 0.57 | 100% | 32.00 | -173.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 4.94 | 5.77 | 100% | 205.00 | 0.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 5.07 | 5.77 | 100% | 225.00 | +20.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 86.27 | 88.97 | 100% | 57.00 | -148.00 | pass | ### edit response then hover (edit+hover) @@ -452,23 +452,23 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 2.34 | 4.75 | 100% | 9977.00 | +9557.00 | pass | -| [Ty](latest-results/ty-20260917T060626Z.json) | yes | 2.44 | 2.49 | 100% | 1613.00 | +1193.00 | pass | -| [Pyright](latest-results/pyright-20260917T060626Z.json) | yes | 34.16 | 38.28 | 100% | 420.00 | 0.00 | pass | -| [pylsp-mypy](latest-results/pylsp-mypy-20260917T060626Z.json) | yes | 238.17 | 245.23 | 100% | 880.00 | +460.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 1.48 | 1.51 | 100% | 9977.00 | +9557.00 | pass | +| [Ty](latest-results/ty-20260918T060520Z.json) | yes | 3.31 | 3.33 | 100% | 1555.00 | +1135.00 | pass | +| [Pyright](latest-results/pyright-20260918T060520Z.json) | yes | 35.61 | 41.53 | 100% | 420.00 | 0.00 | pass | +| [pylsp-mypy](latest-results/pylsp-mypy-20260918T060520Z.json) | yes | 228.13 | 230.10 | 100% | 880.00 | +460.00 | pass | ### Result Differences - request args completion: result differences detected (1.00, 14.00, 467.00, 487.80). - client session hover: result differences detected (167.00, 26.00, 359.00, 7.00). - edit response then complete (edit+completion): result differences detected (205.00, 225.00, 32.00, 57.00). -- edit response then hover (edit+hover): result differences detected (1613.00, 420.00, 880.00, 9977.00). +- edit response then hover (edit+hover): result differences detected (1555.00, 420.00, 880.00, 9977.00). ## Benchmark: tsp_core | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | no | 223.92 | 0.32 | 8 | 40 | 100% | 2 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | no | 221.69 | 0.32 | 8 | 40 | 100% | 2 | ### builtins semantic tokens @@ -476,7 +476,7 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 1.00 | 1.03 | 100% | 30.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 1.00 | 1.03 | 100% | 30.00 | 0.00 | pass | ### builtin int computed type @@ -484,7 +484,7 @@ Method: `typeServer/getComputedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.21 | 0.22 | 100% | 7.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.20 | 0.21 | 100% | 7.00 | 0.00 | pass | ### list declared type @@ -492,7 +492,7 @@ Method: `typeServer/getDeclaredType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.24 | 0.25 | 100% | 7.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.24 | 0.28 | 100% | 7.00 | 0.00 | pass | ### generic specialization computed type @@ -500,7 +500,7 @@ Method: `typeServer/getComputedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.24 | 0.25 | 100% | 7.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.23 | 0.25 | 100% | 7.00 | 0.00 | pass | ### stdlib path computed type @@ -508,7 +508,7 @@ Method: `typeServer/getComputedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.22 | 0.23 | 100% | 7.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.25 | 0.29 | 100% | 7.00 | 0.00 | pass | ### function argument expected type @@ -516,13 +516,13 @@ Method: `typeServer/getExpectedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 0.22 | 0.27 | 100% | 7.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 0.24 | 0.26 | 100% | 7.00 | 0.00 | pass | ## Benchmark: tsp_semantic | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 5918.79 | 32.19 | 3 | 15 | 100% | 0 | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 6119.76 | 44.02 | 3 | 15 | 100% | 0 | ### django semantic tokens @@ -530,7 +530,7 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 15.31 | 31.68 | 100% | 126.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 31.34 | 63.97 | 100% | 126.00 | 0.00 | pass | ### transformers semantic tokens @@ -538,7 +538,7 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 71.02 | 87.82 | 100% | 74.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 79.17 | 95.11 | 100% | 74.00 | 0.00 | pass | ### stdlib semantic tokens @@ -546,4 +546,4 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| [Pyrefly](latest-results/pyrefly-20260917T060626Z.json) | yes | 10.25 | 17.16 | 100% | 75.00 | 0.00 | pass | +| [Pyrefly](latest-results/pyrefly-20260918T060520Z.json) | yes | 21.54 | 29.70 | 100% | 75.00 | 0.00 | pass | diff --git a/latest-results/pylsp-mypy-20260917T060626Z-responses.jsonl b/latest-results/pylsp-mypy-20260918T060520Z-responses.jsonl similarity index 100% rename from latest-results/pylsp-mypy-20260917T060626Z-responses.jsonl rename to latest-results/pylsp-mypy-20260918T060520Z-responses.jsonl index 40da258..28ee3ef 100644 --- a/latest-results/pylsp-mypy-20260917T060626Z-responses.jsonl +++ b/latest-results/pylsp-mypy-20260918T060520Z-responses.jsonl @@ -63,10 +63,10 @@ {"suite": "pandas", "label": "build report definition", "method": "textDocument/definition", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/pandas/src/report.py", "line": 16, "character": 17, "iteration": 3, "result": [{"uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/pandas/src/report.py", "range": {"start": {"line": 3, "character": 4}, "end": {"line": 3, "character": 16}}}]} {"suite": "pandas", "label": "build report definition", "method": "textDocument/definition", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/pandas/src/report.py", "line": 16, "character": 17, "iteration": 4, "result": [{"uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/pandas/src/report.py", "range": {"start": {"line": 3, "character": 4}, "end": {"line": 3, "character": 16}}}]} {"suite": "pandas", 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rename to latest-results/pyrefly-20260918T060520Z-responses.jsonl index 841fe29..1988e32 100644 --- a/latest-results/pyrefly-20260917T060626Z-responses.jsonl +++ b/latest-results/pyrefly-20260918T060520Z-responses.jsonl @@ -123,41 +123,41 @@ {"suite": "transformers", "label": "edit tokenizer then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 10, "character": 30, "iteration": 3, "result": {"canIncreaseVerbosity": false, "contents": {"kind": "markdown", "value": "```python\nvocab_size: Unknown\n```"}}} {"suite": "transformers", "label": "edit tokenizer then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 10, "character": 30, "iteration": 4, "result": {"canIncreaseVerbosity": false, "contents": {"kind": "markdown", "value": "```python\nvocab_size: Unknown\n```"}}} {"suite": "transformers", "label": "edit tokenizer then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 10, "character": 30, "iteration": 5, "result": {"canIncreaseVerbosity": false, "contents": {"kind": "markdown", "value": "```python\nvocab_size: Unknown\n```"}}} -{"suite": "tsp_core", "label": "builtins semantic tokens", "method": "typeServer/semanticTokens", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/tsp_core/src/builtins_basic.py", "line": 0, "character": 0, "iteration": 1, "result": {"data": [0, 0, 5, 10, 1, 0, 5, 1, 2, 0, 0, 2, 3, 5, 0, 0, 4, 1, 2, 0, 0, 2, 1, 4, 0, 1, 0, 4, 10, 1, 0, 4, 1, 2, 0, 0, 2, 3, 5, 0, 0, 4, 1, 2, 0, 0, 2, 8, 3, 0, 1, 0, 5, 10, 1, 0, 5, 1, 2, 0, 0, 2, 4, 5, 0, 0, 4, 1, 2, 0, 0, 1, 3, 5, 0, 0, 3, 1, 2, 0, 0, 2, 1, 2, 0, 0, 2, 1, 2, 0, 0, 1, 1, 4, 0, 0, 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"duration_ms": 0.03038700000956851, + "duration_ms": 0.03561699998044787, "success": true, - "started_at_unix": 1789625281.0616598, + "started_at_unix": 1789711610.450953, "bytes_sent": 319, "bytes_received": 0, "request_id": null, @@ -17284,9 +17284,9 @@ { "kind": "notification", "method": "textDocument/didClose", - "duration_ms": 0.01564899997674729, + "duration_ms": 0.02169100000060098, "success": true, - "started_at_unix": 1789625281.061781, + "started_at_unix": 1789711610.4511094, "bytes_sent": 198, "bytes_received": 0, "request_id": null, @@ -17299,9 +17299,9 @@ { "kind": "request", "method": "shutdown", - "duration_ms": 2.3538190000067516, + "duration_ms": 2.26810200001637, "success": true, - "started_at_unix": 1789625281.0618038, + "started_at_unix": 1789711610.4511409, "bytes_sent": 67, "bytes_received": 61, "request_id": 32, @@ -17319,9 +17319,9 @@ { "kind": "notification", "method": "exit", - "duration_ms": 0.022642000004680085, + "duration_ms": 0.027612000025101224, "success": true, - "started_at_unix": 1789625281.064175, + "started_at_unix": 1789711610.4534323, "bytes_sent": 55, "bytes_received": 0, "request_id": null, diff --git a/latest-results/summary-20260917T060626Z.csv b/latest-results/summary-20260917T060626Z.csv deleted file mode 100644 index b1b351b..0000000 --- a/latest-results/summary-20260917T060626Z.csv +++ /dev/null @@ -1,132 +0,0 @@ -report_type,baseline_server_id,server_id,server_name,suite_name,scenario_name,point_label,method,method_display,success,mean_ms,p95_ms,non_empty_rate,result_metric_name,result_metric_label,result_metric_value,result_metric_delta,validation_passed,validation_failure_count -benchmark,pyright,pyright,Pyright,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,6.853805800000146,12.243956199989725,1.0,completion_item_count,Completions found,201.0,0.0,True,0 -benchmark,pyright,ty,Ty,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,1.7329913999958535,1.9259646000023167,1.0,completion_item_count,Completions found,223.0,22.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,85.69967280000128,340.00540259999633,1.0,completion_item_count,Completions found,250.0,49.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,215.3005807999989,451.3672452000151,1.0,completion_item_count,Completions found,188.0,-13.0,True,0 -benchmark,pyright,pyright,Pyright,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,1.0862263999968036,1.329381199997215,1.0,hover_text_char_count,Hover length,4019.0,0.0,True,0 -benchmark,pyright,ty,Ty,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,0.33128119999901173,0.3821684000058667,1.0,hover_text_char_count,Hover length,4232.0,213.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,5.529336999995849,8.028560399992557,1.0,hover_text_char_count,Hover length,3182.0,-837.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,182.40587960000312,186.3973165999937,1.0,hover_text_char_count,Hover length,4134.0,115.0,True,0 -benchmark,pyright,pyright,Pyright,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,0.4023541999970348,0.46267319998491985,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,ty,Ty,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,0.21780660001127217,0.24079820001929875,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,0.23275319999811472,0.261802200003558,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,1.0502068000050713,1.1045424000144521,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,True,370.5255637999983,453.4820638000042,1.0,completion_item_count,Completions found,168.0,0.0,True,0 -benchmark,pyright,ty,Ty,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,True,10.780125799999496,11.353542800009109,1.0,completion_item_count,Completions found,168.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,True,20.89862479999738,27.802609400009715,1.0,completion_item_count,Completions found,149.0,-19.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,False,4.130732800001624,4.338583399999152,0.0,completion_item_count,Completions found,0.0,-168.0,False,10 -benchmark,pyright,pyright,Pyright,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,34.52936919999843,36.47074819999716,1.0,hover_text_char_count,Hover length,278.0,0.0,True,0 -benchmark,pyright,ty,Ty,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,3.7637874000040483,3.9094376000036846,1.0,hover_text_char_count,Hover length,267.0,-11.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,1.0562052000068434,2.9652732000101873,1.0,hover_text_char_count,Hover length,2546.0,2268.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,167.84747819997392,169.34237639998173,1.0,hover_text_char_count,Hover length,5662.0,5384.0,True,0 -benchmark,pyright,pyright,Pyright,django,,queryset completion,textDocument/completion,textDocument/completion,True,4.704463400008763,7.366456199997628,1.0,completion_item_count,Completions found,10.0,0.0,True,0 -benchmark,pyright,ty,Ty,django,,queryset completion,textDocument/completion,textDocument/completion,True,4.852680200002624,7.173377999998819,1.0,completion_item_count,Completions found,261.0,251.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,django,,queryset completion,textDocument/completion,textDocument/completion,True,16.667461200006528,64.64360340001461,1.0,completion_item_count,Completions found,15.0,5.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,queryset completion,textDocument/completion,textDocument/completion,True,224.9419047999936,694.8293568000053,1.0,completion_item_count,Completions found,2.0,-8.0,True,0 -benchmark,pyright,pyright,Pyright,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,0.5313995999983945,0.5800768000142398,1.0,hover_text_char_count,Hover length,57.0,0.0,True,0 -benchmark,pyright,ty,Ty,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,0.24100619999671835,0.25943460000235063,1.0,hover_text_char_count,Hover length,46.0,-11.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,0.4056583999954455,0.4644783999935953,1.0,hover_text_char_count,Hover length,298.0,241.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,158.86321699999826,161.93930780001438,1.0,hover_text_char_count,Hover length,57.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,django,,model definition,textDocument/definition,textDocument/definition,True,0.3861859999972239,0.42815420001147686,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,ty,Ty,django,,model definition,textDocument/definition,textDocument/definition,True,0.20442599998773403,0.21383919999493628,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,django,,model definition,textDocument/definition,textDocument/definition,True,0.3172632000030262,0.41120220000152585,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,model definition,textDocument/definition,textDocument/definition,True,1.0883399999897847,1.1264891999985593,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,25.762384399996563,28.26996879999797,1.0,completion_item_count,Completions found,104.0,0.0,True,0 -benchmark,pyright,ty,Ty,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.511137999992343,4.9553819999914595,1.0,completion_item_count,Completions found,104.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,1.840021599997499,1.8919007999897985,1.0,completion_item_count,Completions found,83.0,-21.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,278.1143494000048,323.96343540000316,1.0,completion_item_count,Completions found,143.0,39.0,True,0 -benchmark,pyright,pyright,Pyright,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,38.76132579999876,44.27628639999739,1.0,hover_text_char_count,Hover length,83.0,0.0,True,0 -benchmark,pyright,ty,Ty,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,2.888580799998408,2.9442403999894395,1.0,hover_text_char_count,Hover length,100.0,17.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,0.708674599997039,0.7441947999893728,1.0,hover_text_char_count,Hover length,858.0,775.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,247.68304980000266,253.72805360000257,1.0,hover_text_char_count,Hover length,71.0,-12.0,True,0 -benchmark,pyright,pyright,Pyright,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,77.20737200000372,263.36020300000763,1.0,completion_item_count,Completions found,271.2,0.0,True,0 -benchmark,pyright,ty,Ty,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,18.41168440000729,22.190245000012965,1.0,completion_item_count,Completions found,1000.0,728.8,True,0 -benchmark,pyright,pyrefly,Pyrefly,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,91.64153120000265,364.4934544000079,1.0,completion_item_count,Completions found,16.0,-255.2,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,89.91041719999657,199.14463179998162,1.0,completion_item_count,Completions found,6.0,-265.2,True,0 -benchmark,pyright,pyright,Pyright,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,0.7878365999999914,0.9001345999990917,1.0,hover_text_char_count,Hover length,350.0,0.0,True,0 -benchmark,pyright,ty,Ty,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,0.2544016000058491,0.2731928000116568,1.0,hover_text_char_count,Hover length,329.0,-21.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,2.443409199997859,2.6346865999926194,1.0,hover_text_char_count,Hover length,2759.0,2409.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,194.17426039999555,199.56293960001403,1.0,hover_text_char_count,Hover length,301.0,-49.0,True,0 -benchmark,pyright,pyright,Pyright,pandas,,build report definition,textDocument/definition,textDocument/definition,True,0.4453322000017579,0.5399851999925431,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,ty,Ty,pandas,,build report definition,textDocument/definition,textDocument/definition,True,0.23185140000805404,0.2861866000102964,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,pandas,,build report definition,textDocument/definition,textDocument/definition,True,0.24237279999397288,0.2513255999872399,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,build report definition,textDocument/definition,textDocument/definition,True,1.0864704000255188,1.1364240000034442,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,809.8325284000055,1273.5999338000113,1.0,completion_item_count,Completions found,440.0,0.0,True,0 -benchmark,pyright,ty,Ty,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,16.71307519999914,17.682819400010885,1.0,completion_item_count,Completions found,448.0,8.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,44.102225800003225,67.19199579999895,1.0,completion_item_count,Completions found,256.0,-184.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,230.5560805999903,236.24279939996313,1.0,completion_item_count,Completions found,441.0,1.0,True,0 -benchmark,pyright,pyright,Pyright,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,9.570147799996676,10.779148199986821,1.0,hover_text_char_count,Hover length,4292.0,0.0,True,0 -benchmark,pyright,ty,Ty,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,2.8424651999955586,2.9579449999914686,1.0,hover_text_char_count,Hover length,4441.0,149.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,0.7800437999947007,0.8363164000002143,1.0,hover_text_char_count,Hover length,943.0,-3349.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,186.41741039999715,190.40413160000753,1.0,hover_text_char_count,Hover length,232.0,-4060.0,True,0 -benchmark,pyright,pyright,Pyright,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,7.46887020000031,13.350204000005306,1.0,completion_item_count,Completions found,1.0,0.0,True,0 -benchmark,pyright,ty,Ty,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,3.3112353999911193,7.324279999988901,1.0,completion_item_count,Completions found,1.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,84.05303040000831,335.21026280001814,1.0,completion_item_count,Completions found,15.0,14.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,223.34092720001308,409.40285920002,1.0,completion_item_count,Completions found,1.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,1.2492621999967923,1.4382423999961702,1.0,hover_text_char_count,Hover length,10572.0,0.0,True,0 -benchmark,pyright,ty,Ty,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,0.40695280000591083,0.4286356000136493,1.0,hover_text_char_count,Hover length,10621.0,49.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,1.0631709999984196,1.1336829999947895,1.0,hover_text_char_count,Hover length,15232.0,4660.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,331.6529540000033,338.0031270000245,1.0,hover_text_char_count,Hover length,10498.0,-74.0,True,0 -benchmark,pyright,pyright,Pyright,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,0.4646763999971881,0.5108007999979236,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,ty,Ty,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,0.2283086000034018,0.24342840001168042,1.0,location_count,Definitions found,2.0,1.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,0.2353140000025178,0.2639154000007693,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,1.1915918000227066,1.3429442000301606,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,True,145.38746619999756,185.92269539999506,1.0,completion_item_count,Completions found,38.0,0.0,True,0 -benchmark,pyright,ty,Ty,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.372194399996943,4.784285999994609,1.0,completion_item_count,Completions found,23.0,-15.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,True,0.71343960000263,0.7524344000046312,1.0,completion_item_count,Completions found,17.0,-21.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,False,39.51081139999815,40.56785380000747,0.0,completion_item_count,Completions found,0.0,-38.0,False,10 -benchmark,pyright,pyright,Pyright,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,True,97.1639792000019,105.77158640000448,1.0,hover_text_char_count,Hover length,900.0,0.0,True,0 -benchmark,pyright,ty,Ty,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,True,4.095067800000152,4.178271800003586,1.0,hover_text_char_count,Hover length,958.0,58.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,True,0.48679560000550737,0.5232498000111718,1.0,hover_text_char_count,Hover length,2246.0,1346.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,False,39.66808240001001,41.48695580000776,0.0,hover_text_char_count,Hover length,0.0,-900.0,False,10 -benchmark,pyright,pyright,Pyright,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,50.667706400003,77.69089120000672,1.0,completion_item_count,Completions found,123.0,0.0,True,0 -benchmark,pyright,ty,Ty,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,11.583579600005578,12.776557599994476,1.0,completion_item_count,Completions found,776.0,653.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,836.2892396000063,3344.2146756000047,1.0,completion_item_count,Completions found,15.0,-108.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,152.866913999992,156.82470320000448,1.0,completion_item_count,Completions found,2.0,-121.0,True,0 -benchmark,pyright,pyright,Pyright,transformers,,pipeline hover,textDocument/hover,textDocument/hover,True,0.46792659999823627,0.5549394000013308,1.0,hover_text_char_count,Hover length,34.0,0.0,True,0 -benchmark,pyright,ty,Ty,transformers,,pipeline hover,textDocument/hover,textDocument/hover,True,0.22950499999865315,0.26370079998514484,1.0,hover_text_char_count,Hover length,7.0,-27.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,transformers,,pipeline hover,textDocument/hover,textDocument/hover,True,0.2146293999999216,0.21723439999732364,1.0,hover_text_char_count,Hover length,48.0,14.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,pipeline hover,textDocument/hover,textDocument/hover,False,2846.328490999997,2909.7137050000015,0.0,hover_text_char_count,Hover length,0.0,-34.0,False,10 -benchmark,pyright,pyright,Pyright,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,0.48497659999497955,0.6700103999889961,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,ty,Ty,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,0.2679810000017824,0.286371199996438,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,0.22056800002019372,0.22759940002288204,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,2229.5765566,2274.33223659998,1.0,location_count,Definitions found,1.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,7.721935399996482,9.292573600009746,0.0,completion_item_count,Completions found,0.0,0.0,True,0 -benchmark,pyright,ty,Ty,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,6.751367399999708,8.016155599995045,1.0,completion_item_count,Completions found,23.0,23.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,6.25848880000035,17.143410399995673,0.0,completion_item_count,Completions found,0.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,2.5418057999900157,2.6453074000073684,0.0,completion_item_count,Completions found,0.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,True,512.9132620000007,546.5719369999988,1.0,hover_text_char_count,Hover length,30.0,0.0,True,0 -benchmark,pyright,ty,Ty,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,True,5.6297287999996115,5.737766399988686,1.0,hover_text_char_count,Hover length,7.0,-23.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,True,6.613427599995703,22.636556999998444,1.0,hover_text_char_count,Hover length,33.0,3.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,False,2707.972011800007,2737.5106886000026,0.0,hover_text_char_count,Hover length,0.0,-30.0,False,10 -benchmark,pyright,pyright,Pyright,web,,request args completion,textDocument/completion,textDocument/completion,True,6.071855799996229,10.602265000011357,1.0,completion_item_count,Completions found,14.0,0.0,True,0 -benchmark,pyright,ty,Ty,web,,request args completion,textDocument/completion,textDocument/completion,True,6.248964200000273,9.070722400008435,1.0,completion_item_count,Completions found,467.0,453.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,web,,request args completion,textDocument/completion,textDocument/completion,True,56.001089400012916,184.05420299999375,1.0,completion_item_count,Completions found,487.8,473.8,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,request args completion,textDocument/completion,textDocument/completion,True,95.80376840000326,161.83794859999807,1.0,completion_item_count,Completions found,1.0,-13.0,True,0 -benchmark,pyright,pyright,Pyright,web,,client session hover,textDocument/hover,textDocument/hover,True,0.5212363999987701,0.5940724000026876,1.0,hover_text_char_count,Hover length,26.0,0.0,True,0 -benchmark,pyright,ty,Ty,web,,client session hover,textDocument/hover,textDocument/hover,True,0.21847020000222983,0.24011499999687658,1.0,hover_text_char_count,Hover length,7.0,-19.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,web,,client session hover,textDocument/hover,textDocument/hover,True,5.337137599997277,18.56390679998867,1.0,hover_text_char_count,Hover length,167.0,141.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,client session hover,textDocument/hover,textDocument/hover,True,151.60762399999612,198.45799759996225,1.0,hover_text_char_count,Hover length,359.0,333.0,True,0 -benchmark,pyright,pyright,Pyright,web,,client references,textDocument/references,textDocument/references,True,0.7897623999951975,0.9522522000054322,1.0,location_count,References found,2.0,0.0,True,0 -benchmark,pyright,ty,Ty,web,,client references,textDocument/references,textDocument/references,True,0.5772210000031919,0.7076808000022083,1.0,location_count,References found,2.0,0.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,web,,client references,textDocument/references,textDocument/references,True,0.3247649999934765,0.33649540000624256,1.0,location_count,References found,2.0,0.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,client references,textDocument/references,textDocument/references,True,4.0757962000043335,5.077315399989857,1.0,location_count,References found,2.0,0.0,True,0 -benchmark,pyright,pyright,Pyright,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.842892400000665,6.022433000003957,1.0,completion_item_count,Completions found,205.0,0.0,True,0 -benchmark,pyright,ty,Ty,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.441810199995189,5.1921430000049895,1.0,completion_item_count,Completions found,225.0,20.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,0.5927923999934137,0.619382599995788,1.0,completion_item_count,Completions found,32.0,-173.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,94.39547940003195,96.60628300005101,1.0,completion_item_count,Completions found,57.0,-148.0,True,0 -benchmark,pyright,pyright,Pyright,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,34.16491280000287,38.27747339999519,1.0,hover_text_char_count,Hover length,420.0,0.0,True,0 -benchmark,pyright,ty,Ty,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,2.443920200011007,2.488253200010604,1.0,hover_text_char_count,Hover length,1613.0,1193.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,2.337145200010582,4.746534200023688,1.0,hover_text_char_count,Hover length,9977.0,9557.0,True,0 -benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,238.17242640002405,245.22880840008838,1.0,hover_text_char_count,Hover length,880.0,460.0,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,builtins semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,1.0036100000036186,1.0274059999971996,1.0,semantic_token_count,Semantic tokens found,30.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,builtin int computed type,typeServer/getComputedType,typeServer/getComputedType,True,0.20580080000058842,0.21774340000888515,1.0,top_level_count,Results found,7.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,list declared type,typeServer/getDeclaredType,typeServer/getDeclaredType,True,0.23921059999452154,0.2546547999827453,1.0,top_level_count,Results found,7.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,generic specialization computed type,typeServer/getComputedType,typeServer/getComputedType,True,0.23621619999403265,0.25123459998326325,1.0,top_level_count,Results found,7.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,flow narrowed branch type,typeServer/getComputedType,typeServer/getComputedType,False,0.21575100000177372,0.2247509999904196,,,,,,False,10 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,stdlib path computed type,typeServer/getComputedType,typeServer/getComputedType,True,0.22181580000051326,0.22974679999379077,1.0,top_level_count,Results found,7.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,function argument expected type,typeServer/getExpectedType,typeServer/getExpectedType,True,0.2225603999931991,0.27065239999615187,1.0,top_level_count,Results found,7.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_core,,edited narrowing recomputes type (edit+getComputedType),typeServer/getComputedType,typeServer/getComputedType,False,0.21776280000267434,0.2290052000034848,,,,,,False,10 -benchmark,pyright,pyrefly,Pyrefly,tsp_semantic,,django semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,15.308100799990143,31.67596600000024,1.0,semantic_token_count,Semantic tokens found,126.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_semantic,,transformers semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,71.0187471999916,87.81578400000853,1.0,semantic_token_count,Semantic tokens found,74.0,,True,0 -benchmark,pyright,pyrefly,Pyrefly,tsp_semantic,,stdlib semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,10.251338599994142,17.163958999992698,1.0,semantic_token_count,Semantic tokens found,75.0,,True,0 diff --git a/latest-results/summary-20260918T060520Z.csv b/latest-results/summary-20260918T060520Z.csv new file mode 100644 index 0000000..f0c2a5b --- /dev/null +++ b/latest-results/summary-20260918T060520Z.csv @@ -0,0 +1,132 @@ +report_type,baseline_server_id,server_id,server_name,suite_name,scenario_name,point_label,method,method_display,success,mean_ms,p95_ms,non_empty_rate,result_metric_name,result_metric_label,result_metric_value,result_metric_delta,validation_passed,validation_failure_count +benchmark,pyright,pyright,Pyright,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,5.496455999997352,8.60027379998769,1.0,completion_item_count,Completions found,201.0,0.0,True,0 +benchmark,pyright,ty,Ty,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,1.702037200010409,1.9497165999950992,1.0,completion_item_count,Completions found,223.0,22.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,89.08242700001097,341.83216779999265,1.0,completion_item_count,Completions found,250.0,49.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,dataframe completion,textDocument/completion,textDocument/completion,True,207.64093060000164,433.51646080001274,1.0,completion_item_count,Completions found,188.0,-13.0,True,0 +benchmark,pyright,pyright,Pyright,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,1.1164878000016643,1.3242484000045351,1.0,hover_text_char_count,Hover length,4019.0,0.0,True,0 +benchmark,pyright,ty,Ty,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,0.32037719999493675,0.3541161999976339,1.0,hover_text_char_count,Hover length,4232.0,213.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,2.3324552000019594,2.6348923999989893,1.0,hover_text_char_count,Hover length,3182.0,-837.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,dataframe describe hover,textDocument/hover,textDocument/hover,True,177.83136040000045,178.97902740000404,1.0,hover_text_char_count,Hover length,4134.0,115.0,True,0 +benchmark,pyright,pyright,Pyright,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,0.40752360000055887,0.4502815999927634,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,ty,Ty,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,0.20147460000430328,0.2062455999919166,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,0.2210837999996329,0.250672999999324,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,summarize definition,textDocument/definition,textDocument/definition,True,1.047413199995617,1.07879819999539,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,True,328.3863616000019,459.8196079999979,1.0,completion_item_count,Completions found,168.0,0.0,True,0 +benchmark,pyright,ty,Ty,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,True,12.470503600002303,14.02091719999703,1.0,completion_item_count,Completions found,168.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,True,28.550184400000944,77.88517060000116,1.0,completion_item_count,Completions found,149.0,-19.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,edit array then complete (edit+completion),textDocument/completion,textDocument/completion,False,4.146331399999781,4.261635000000297,0.0,completion_item_count,Completions found,0.0,-168.0,False,10 +benchmark,pyright,pyright,Pyright,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,31.53113639999674,34.596414399999276,1.0,hover_text_char_count,Hover length,278.0,0.0,True,0 +benchmark,pyright,ty,Ty,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,5.853197400006138,5.889599800002543,1.0,hover_text_char_count,Hover length,267.0,-11.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,4.568133599991597,6.259819999985439,1.0,hover_text_char_count,Hover length,2546.0,2268.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,data_science,,edit array then hover (edit+hover),textDocument/hover,textDocument/hover,True,166.71890860000076,168.27697060001015,1.0,hover_text_char_count,Hover length,5662.0,5384.0,True,0 +benchmark,pyright,pyright,Pyright,django,,queryset completion,textDocument/completion,textDocument/completion,True,4.613223800004107,7.3764670000031165,1.0,completion_item_count,Completions found,10.0,0.0,True,0 +benchmark,pyright,ty,Ty,django,,queryset completion,textDocument/completion,textDocument/completion,True,4.746930000004568,7.180571200001395,1.0,completion_item_count,Completions found,261.0,251.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,django,,queryset completion,textDocument/completion,textDocument/completion,True,15.677579000004016,61.11533099999632,1.0,completion_item_count,Completions found,15.0,5.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,queryset completion,textDocument/completion,textDocument/completion,True,226.79736960000128,676.2697167999873,1.0,completion_item_count,Completions found,2.0,-8.0,True,0 +benchmark,pyright,pyright,Pyright,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,0.5515572000007296,0.6091711999999916,1.0,hover_text_char_count,Hover length,57.0,0.0,True,0 +benchmark,pyright,ty,Ty,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,0.23103620000597402,0.24977120000926334,1.0,hover_text_char_count,Hover length,46.0,-11.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,0.4348153999956139,0.4532859999926586,1.0,hover_text_char_count,Hover length,298.0,241.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,queryset filter hover,textDocument/hover,textDocument/hover,True,157.9314217999979,161.62682659999632,1.0,hover_text_char_count,Hover length,57.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,django,,model definition,textDocument/definition,textDocument/definition,True,0.39404640000100244,0.4577741999952422,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,ty,Ty,django,,model definition,textDocument/definition,textDocument/definition,True,0.20588300000667914,0.21431880001614445,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,django,,model definition,textDocument/definition,textDocument/definition,True,0.414954000001444,0.4341338000074302,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,model definition,textDocument/definition,textDocument/definition,True,1.0888462000139043,1.1400758000206679,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,25.59900400000288,28.17517500000406,1.0,completion_item_count,Completions found,104.0,0.0,True,0 +benchmark,pyright,ty,Ty,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.613522800002556,4.723736199997575,1.0,completion_item_count,Completions found,104.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,2.747397600006707,3.817423800001052,1.0,completion_item_count,Completions found,83.0,-21.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,edit queryset then complete (edit+completion),textDocument/completion,textDocument/completion,True,257.3623601999998,293.90533400000436,1.0,completion_item_count,Completions found,143.0,39.0,True,0 +benchmark,pyright,pyright,Pyright,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,37.434204999999565,45.39536939999209,1.0,hover_text_char_count,Hover length,83.0,0.0,True,0 +benchmark,pyright,ty,Ty,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,3.1943323999996664,3.2300473999953283,1.0,hover_text_char_count,Hover length,100.0,17.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,0.7851548000019193,0.8791788000053202,1.0,hover_text_char_count,Hover length,858.0,775.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,django,,edit queryset then hover (edit+hover),textDocument/hover,textDocument/hover,True,247.31441639999616,252.36813980000647,1.0,hover_text_char_count,Hover length,71.0,-12.0,True,0 +benchmark,pyright,pyright,Pyright,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,85.15355219999776,285.02544320000135,1.0,completion_item_count,Completions found,271.2,0.0,True,0 +benchmark,pyright,ty,Ty,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,18.873921400006566,22.52329860000941,1.0,completion_item_count,Completions found,1000.0,728.8,True,0 +benchmark,pyright,pyrefly,Pyrefly,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,89.33931139999345,356.4083945999982,1.0,completion_item_count,Completions found,16.0,-255.2,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,report dataframe completion,textDocument/completion,textDocument/completion,True,94.11580300000537,218.52389160000592,1.0,completion_item_count,Completions found,6.0,-265.2,True,0 +benchmark,pyright,pyright,Pyright,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,0.6996195999988686,0.7710729999956811,1.0,hover_text_char_count,Hover length,350.0,0.0,True,0 +benchmark,pyright,ty,Ty,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,0.26673300000084055,0.2793662000101449,1.0,hover_text_char_count,Hover length,329.0,-21.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,2.4046264000048723,2.5392404000172064,1.0,hover_text_char_count,Hover length,2759.0,2409.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,dataframe groupby hover,textDocument/hover,textDocument/hover,True,194.32109659999242,197.04791039998213,1.0,hover_text_char_count,Hover length,301.0,-49.0,True,0 +benchmark,pyright,pyright,Pyright,pandas,,build report definition,textDocument/definition,textDocument/definition,True,0.44877899999846704,0.4714111999959414,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,ty,Ty,pandas,,build report definition,textDocument/definition,textDocument/definition,True,0.20467679999569555,0.212794199990185,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,pandas,,build report definition,textDocument/definition,textDocument/definition,True,0.25131600000918297,0.26436400002012306,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,build report definition,textDocument/definition,textDocument/definition,True,1.0819200000014462,1.1161277999974573,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,653.494982800001,1370.8534876000044,1.0,completion_item_count,Completions found,440.0,0.0,True,0 +benchmark,pyright,ty,Ty,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,16.796020399999634,17.920499600000994,1.0,completion_item_count,Completions found,448.0,8.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,41.334381000001486,59.91415359999905,1.0,completion_item_count,Completions found,256.0,-184.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,edit dataframe then complete (edit+completion),textDocument/completion,textDocument/completion,True,244.31413639999278,249.9497043999895,1.0,completion_item_count,Completions found,441.0,1.0,True,0 +benchmark,pyright,pyright,Pyright,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,12.3768081999998,15.049448000002029,1.0,hover_text_char_count,Hover length,4292.0,0.0,True,0 +benchmark,pyright,ty,Ty,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,4.898377600000003,4.927504200009025,1.0,hover_text_char_count,Hover length,4441.0,149.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,26.830662800000482,83.79032279999022,1.0,hover_text_char_count,Hover length,943.0,-3349.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,pandas,,edit dataframe then hover (edit+hover),textDocument/hover,textDocument/hover,True,184.51858459999926,186.72059280001463,1.0,hover_text_char_count,Hover length,232.0,-4060.0,True,0 +benchmark,pyright,pyright,Pyright,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,6.781364200003281,10.926096200006441,1.0,completion_item_count,Completions found,1.0,0.0,True,0 +benchmark,pyright,ty,Ty,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,3.3787885999970513,7.770302199998012,1.0,completion_item_count,Completions found,1.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,83.60451100000432,333.552261799997,1.0,completion_item_count,Completions found,15.0,14.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,query completion,textDocument/completion,textDocument/completion,True,215.87460220000025,459.49903979999925,1.0,completion_item_count,Completions found,1.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,1.2799771999993936,1.5876488000060363,1.0,hover_text_char_count,Hover length,10572.0,0.0,True,0 +benchmark,pyright,ty,Ty,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,0.4070474000059221,0.4223597999953199,1.0,hover_text_char_count,Hover length,10621.0,49.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,0.950063600004114,1.0116626000126416,1.0,hover_text_char_count,Hover length,15232.0,4660.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,sessionmaker hover,textDocument/hover,textDocument/hover,True,332.71890980000194,340.7764583999949,1.0,hover_text_char_count,Hover length,10498.0,-74.0,True,0 +benchmark,pyright,pyright,Pyright,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,0.4155212000028996,0.47095480000223233,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,ty,Ty,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,0.22478840000417222,0.23091220000992507,1.0,location_count,Definitions found,2.0,1.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,0.21038120000298477,0.23179940001227803,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,mapped class definition,textDocument/definition,textDocument/definition,True,1.0924371999919913,1.1288349999858838,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,True,140.85551080000016,205.00222719999215,1.0,completion_item_count,Completions found,38.0,0.0,True,0 +benchmark,pyright,ty,Ty,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.822577599998112,5.3224430000057055,1.0,completion_item_count,Completions found,23.0,-15.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,True,0.7382008000035967,0.7661149999933059,1.0,completion_item_count,Completions found,17.0,-21.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,edit query then complete (edit+completion),textDocument/completion,textDocument/completion,False,40.024937000009686,40.61631100001364,0.0,completion_item_count,Completions found,0.0,-38.0,False,10 +benchmark,pyright,pyright,Pyright,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,True,92.85680200000002,108.29673379999463,1.0,hover_text_char_count,Hover length,900.0,0.0,True,0 +benchmark,pyright,ty,Ty,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,True,4.387485600000218,4.4190367999874525,1.0,hover_text_char_count,Hover length,958.0,58.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,True,0.5213191999985156,0.5486043999837875,1.0,hover_text_char_count,Hover length,2246.0,1346.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,sqlalchemy,,edit session then hover (edit+hover),textDocument/hover,textDocument/hover,False,40.38254600000073,40.52707020001094,0.0,hover_text_char_count,Hover length,0.0,-900.0,False,10 +benchmark,pyright,pyright,Pyright,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,52.877534199996035,84.92119939999725,1.0,completion_item_count,Completions found,123.0,0.0,True,0 +benchmark,pyright,ty,Ty,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,10.801733999994667,11.98228979999385,1.0,completion_item_count,Completions found,776.0,653.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,863.0994364000002,3451.47443560001,1.0,completion_item_count,Completions found,15.0,-108.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,classifier pipeline completion,textDocument/completion,textDocument/completion,True,146.86205359999462,152.52222999998253,1.0,completion_item_count,Completions found,2.0,-121.0,True,0 +benchmark,pyright,pyright,Pyright,transformers,,pipeline hover,textDocument/hover,textDocument/hover,True,0.4844520000006014,0.5292797999970844,1.0,hover_text_char_count,Hover length,34.0,0.0,True,0 +benchmark,pyright,ty,Ty,transformers,,pipeline hover,textDocument/hover,textDocument/hover,True,0.23226840000347693,0.25872760000993367,1.0,hover_text_char_count,Hover length,7.0,-27.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,transformers,,pipeline hover,textDocument/hover,textDocument/hover,True,0.21573559999978897,0.22156699999413831,1.0,hover_text_char_count,Hover length,48.0,14.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,pipeline hover,textDocument/hover,textDocument/hover,False,2770.9204716000045,2839.8312876000205,0.0,hover_text_char_count,Hover length,0.0,-34.0,False,10 +benchmark,pyright,pyright,Pyright,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,0.4448263999961455,0.5206171999873277,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,ty,Ty,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,0.27070400000184236,0.29123619999040784,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,0.21903980000956835,0.22425959999736733,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,auto tokenizer definition,textDocument/definition,textDocument/definition,True,2224.2307422000067,2259.4618886000035,1.0,location_count,Definitions found,1.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,6.90462619999721,8.95788459998812,0.0,completion_item_count,Completions found,0.0,0.0,True,0 +benchmark,pyright,ty,Ty,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,5.940839400000186,6.058791999993218,1.0,completion_item_count,Completions found,23.0,23.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,13.52384220000431,26.36991119999834,0.0,completion_item_count,Completions found,0.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,edit prediction then complete (edit+completion),textDocument/completion,textDocument/completion,True,2.7139360000091983,2.798223600007077,0.0,completion_item_count,Completions found,0.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,True,491.31088419999287,518.5981758000196,1.0,hover_text_char_count,Hover length,30.0,0.0,True,0 +benchmark,pyright,ty,Ty,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,True,5.727290199990875,5.889211399988881,1.0,hover_text_char_count,Hover length,7.0,-23.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,True,10.360597400000415,28.955804000003123,1.0,hover_text_char_count,Hover length,33.0,3.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,transformers,,edit tokenizer then hover (edit+hover),textDocument/hover,textDocument/hover,False,2651.9987008000044,2674.6999837999965,0.0,hover_text_char_count,Hover length,0.0,-30.0,False,10 +benchmark,pyright,pyright,Pyright,web,,request args completion,textDocument/completion,textDocument/completion,True,4.685487199998306,8.808504999996101,1.0,completion_item_count,Completions found,14.0,0.0,True,0 +benchmark,pyright,ty,Ty,web,,request args completion,textDocument/completion,textDocument/completion,True,6.530250200000864,9.167653999992353,1.0,completion_item_count,Completions found,467.0,453.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,web,,request args completion,textDocument/completion,textDocument/completion,True,63.682403999996495,183.47257259999307,1.0,completion_item_count,Completions found,487.8,473.8,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,request args completion,textDocument/completion,textDocument/completion,True,68.67937039997969,116.50688419997549,1.0,completion_item_count,Completions found,1.0,-13.0,True,0 +benchmark,pyright,pyright,Pyright,web,,client session hover,textDocument/hover,textDocument/hover,True,0.5228457999976399,0.619039800005794,1.0,hover_text_char_count,Hover length,26.0,0.0,True,0 +benchmark,pyright,ty,Ty,web,,client session hover,textDocument/hover,textDocument/hover,True,0.20959799999218376,0.2318261999846527,1.0,hover_text_char_count,Hover length,7.0,-19.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,web,,client session hover,textDocument/hover,textDocument/hover,True,5.250325599996586,18.193736600005646,1.0,hover_text_char_count,Hover length,167.0,141.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,client session hover,textDocument/hover,textDocument/hover,True,110.68619119998857,235.69662599999216,1.0,hover_text_char_count,Hover length,359.0,333.0,True,0 +benchmark,pyright,pyright,Pyright,web,,client references,textDocument/references,textDocument/references,True,0.7614310000008118,0.8827992000021823,1.0,location_count,References found,2.0,0.0,True,0 +benchmark,pyright,ty,Ty,web,,client references,textDocument/references,textDocument/references,True,0.679871799997045,0.7496162000165896,1.0,location_count,References found,2.0,0.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,web,,client references,textDocument/references,textDocument/references,True,0.33852680000450164,0.3459086000020761,1.0,location_count,References found,2.0,0.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,client references,textDocument/references,textDocument/references,True,20.39878419999468,62.903712600018466,1.0,location_count,References found,2.0,0.0,True,0 +benchmark,pyright,pyright,Pyright,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,4.939684999999372,5.7673891999911575,1.0,completion_item_count,Completions found,205.0,0.0,True,0 +benchmark,pyright,ty,Ty,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,5.073002799997539,5.77391019999709,1.0,completion_item_count,Completions found,225.0,20.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,0.5581779999943137,0.5696919999877537,1.0,completion_item_count,Completions found,32.0,-173.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,edit response then complete (edit+completion),textDocument/completion,textDocument/completion,True,86.26605680000239,88.97244139998293,1.0,completion_item_count,Completions found,57.0,-148.0,True,0 +benchmark,pyright,pyright,Pyright,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,35.60840020001024,41.5327234000074,1.0,hover_text_char_count,Hover length,420.0,0.0,True,0 +benchmark,pyright,ty,Ty,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,3.312833000001092,3.3336735999967004,1.0,hover_text_char_count,Hover length,1555.0,1135.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,1.4822096000045804,1.505461000010655,1.0,hover_text_char_count,Hover length,9977.0,9557.0,True,0 +benchmark,pyright,pylsp-mypy,pylsp-mypy,web,,edit response then hover (edit+hover),textDocument/hover,textDocument/hover,True,228.12987160001512,230.0962152000011,1.0,hover_text_char_count,Hover length,880.0,460.0,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,builtins semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,0.9980327999983274,1.0298685999998725,1.0,semantic_token_count,Semantic tokens found,30.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,builtin int computed type,typeServer/getComputedType,typeServer/getComputedType,True,0.20216200000504614,0.20582500000614345,1.0,top_level_count,Results found,7.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,list declared type,typeServer/getDeclaredType,typeServer/getDeclaredType,True,0.2435098000034941,0.2765734000035991,1.0,top_level_count,Results found,7.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,generic specialization computed type,typeServer/getComputedType,typeServer/getComputedType,True,0.23393199999759418,0.25081400000317444,1.0,top_level_count,Results found,7.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,flow narrowed branch type,typeServer/getComputedType,typeServer/getComputedType,False,0.20041660000060801,0.21274959999573184,,,,,,False,10 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,stdlib path computed type,typeServer/getComputedType,typeServer/getComputedType,True,0.24981899999829693,0.290800000004765,1.0,top_level_count,Results found,7.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,function argument expected type,typeServer/getExpectedType,typeServer/getExpectedType,True,0.24340740000070582,0.25987820000068496,1.0,top_level_count,Results found,7.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_core,,edited narrowing recomputes type (edit+getComputedType),typeServer/getComputedType,typeServer/getComputedType,False,0.21152000000483895,0.2219606000096519,,,,,,False,10 +benchmark,pyright,pyrefly,Pyrefly,tsp_semantic,,django semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,31.3371783999969,63.96574560000089,1.0,semantic_token_count,Semantic tokens found,126.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_semantic,,transformers semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,79.17317199999161,95.1146683999923,1.0,semantic_token_count,Semantic tokens found,74.0,,True,0 +benchmark,pyright,pyrefly,Pyrefly,tsp_semantic,,stdlib semantic tokens,typeServer/semanticTokens,semantic token impl using typeServer/getComputedType,True,21.535625800004254,29.695889399994254,1.0,semantic_token_count,Semantic tokens found,75.0,,True,0 diff --git a/latest-results/summary-20260917T060626Z.json b/latest-results/summary-20260918T060520Z.json similarity index 89% rename from latest-results/summary-20260917T060626Z.json rename to latest-results/summary-20260918T060520Z.json index ba976a1..25ce39b 100644 --- a/latest-results/summary-20260917T060626Z.json +++ b/latest-results/summary-20260918T060520Z.json @@ -17,12 +17,12 @@ "tsp_semantic" ], "baseline_server": "pyright", - "generated_at": "20260917T060626Z", + "generated_at": "20260918T060520Z", "servers": [ { "id": "pyright", "display_name": "Pyright", - "output_path": "results/bench-servers/pyright-20260917T060626Z.json", + "output_path": "results/bench-servers/pyright-20260918T060520Z.json", "success": true, "benchmark_count": 6, "command": [ @@ -58,21 +58,21 @@ { "id": "ty", "display_name": "Ty", - "output_path": "results/bench-servers/ty-20260917T060626Z.json", + "output_path": "results/bench-servers/ty-20260918T060520Z.json", "success": true, "benchmark_count": 6, "command": [ - "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.81/ty-x86_64-unknown-linux-gnu/ty", + "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.82/ty-x86_64-unknown-linux-gnu/ty", "server" ], - "source_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.81/ty-x86_64-unknown-linux-gnu/ty", + "source_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.82/ty-x86_64-unknown-linux-gnu/ty", "version": { "kind": "release", - "label": "0.0.81", + "label": "0.0.82", "repo_root": null, "commit": null, "short_commit": null, - "source_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.81/ty-x86_64-unknown-linux-gnu/ty" + "source_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.82/ty-x86_64-unknown-linux-gnu/ty" }, "requested_benchmarks": [ "data_science", @@ -91,7 +91,7 @@ { "id": "pyrefly", "display_name": "Pyrefly", - "output_path": "results/bench-servers/pyrefly-20260917T060626Z.json", + "output_path": "results/bench-servers/pyrefly-20260918T060520Z.json", "success": false, "benchmark_count": 8, "command": [ @@ -131,7 +131,7 @@ { "id": "pylsp-mypy", "display_name": "pylsp-mypy", - "output_path": "results/bench-servers/pylsp-mypy-20260917T060626Z.json", + "output_path": "results/bench-servers/pylsp-mypy-20260918T060520Z.json", "success": false, "benchmark_count": 6, "command": [ diff --git a/latest-results/summary-20260917T060626Z.md b/latest-results/summary-20260918T060520Z.md similarity index 61% rename from latest-results/summary-20260917T060626Z.md rename to latest-results/summary-20260918T060520Z.md index 08d3559..3bbe469 100644 --- a/latest-results/summary-20260917T060626Z.md +++ b/latest-results/summary-20260918T060520Z.md @@ -1,8 +1,8 @@ # Python LSP Benchmark Comparison -Generated from `results/bench-servers/summary-20260917T060626Z.json` +Generated from `results/bench-servers/summary-20260918T060520Z.json` -- Generated at: 20260917T060626Z +- Generated at: 20260918T060520Z - Config: `github-releases` - Servers: pyright, ty, pyrefly, pylsp-mypy - Baseline server: Pyright (pyright) @@ -13,7 +13,7 @@ Generated from `results/bench-servers/summary-20260917T060626Z.json` | Server | Version | Source | | --- | --- | --- | | Pyright | 1.1.414 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/pyright/1.1.414/package/dist/pyright-langserver.js | -| Ty | 0.0.81 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.81/ty-x86_64-unknown-linux-gnu/ty | +| Ty | 0.0.82 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.82/ty-x86_64-unknown-linux-gnu/ty | | Pyrefly | 1.3.1 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/pyrefly/venv/bin/pyrefly | | pylsp-mypy | 1.15.0 | /home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/pylsp-mypy/venv/bin/pylsp | @@ -30,10 +30,10 @@ Generated from `results/bench-servers/summary-20260917T060626Z.json` | Server | Success | Benchmarks | Wall clock ms | Avg measured ms | Measured requests | Non-empty % | Failed points | | --- | --- | --- | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 6 | 4893.94 | 3.96 | 150 | 100% | 0 | -| Pyrefly | no | 8 | 15742.33 | 33.47 | 205 | 97% | 2 | -| Pyright | yes | 6 | 39362.93 | 75.06 | 150 | 97% | 0 | -| pylsp-mypy | no | 6 | 257590.03 | 378.08 | 150 | 80% | 5 | +| Ty | yes | 6 | 5143.02 | 4.22 | 150 | 100% | 0 | +| Pyrefly | no | 8 | 16463.60 | 36.20 | 205 | 97% | 2 | +| Pyright | yes | 6 | 37971.23 | 67.61 | 150 | 97% | 0 | +| pylsp-mypy | no | 6 | 220250.41 | 370.24 | 150 | 80% | 5 | *Wall clock ms includes server startup, warmup iterations, and shutdown — but excludes one-time environment creation and dependency installation.* @@ -41,10 +41,10 @@ Generated from `results/bench-servers/summary-20260917T060626Z.json` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 396.37 | 3.37 | 5 | 25 | 100% | 0 | -| Pyrefly | yes | 1135.26 | 22.68 | 5 | 25 | 100% | 0 | -| Pyright | yes | 4702.15 | 82.68 | 5 | 25 | 100% | 0 | -| pylsp-mypy | no | 7787.40 | 114.15 | 5 | 25 | 80% | 1 | +| Ty | yes | 534.85 | 4.11 | 5 | 25 | 100% | 0 | +| Pyrefly | yes | 1274.19 | 24.95 | 5 | 25 | 100% | 0 | +| Pyright | yes | 4502.03 | 73.39 | 5 | 25 | 100% | 0 | +| pylsp-mypy | no | 7881.47 | 111.48 | 5 | 25 | 80% | 1 | ### dataframe completion @@ -52,10 +52,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 1.73 | 1.93 | 100% | 223.00 | +22.00 | pass | -| Pyright | yes | 6.85 | 12.24 | 100% | 201.00 | 0.00 | pass | -| Pyrefly | yes | 85.70 | 340.01 | 100% | 250.00 | +49.00 | pass | -| pylsp-mypy | yes | 215.30 | 451.37 | 100% | 188.00 | -13.00 | pass | +| Ty | yes | 1.70 | 1.95 | 100% | 223.00 | +22.00 | pass | +| Pyright | yes | 5.50 | 8.60 | 100% | 201.00 | 0.00 | pass | +| Pyrefly | yes | 89.08 | 341.83 | 100% | 250.00 | +49.00 | pass | +| pylsp-mypy | yes | 207.64 | 433.52 | 100% | 188.00 | -13.00 | pass | ### dataframe describe hover @@ -63,10 +63,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.33 | 0.38 | 100% | 4232.00 | +213.00 | pass | -| Pyright | yes | 1.09 | 1.33 | 100% | 4019.00 | 0.00 | pass | -| Pyrefly | yes | 5.53 | 8.03 | 100% | 3182.00 | -837.00 | pass | -| pylsp-mypy | yes | 182.41 | 186.40 | 100% | 4134.00 | +115.00 | pass | +| Ty | yes | 0.32 | 0.35 | 100% | 4232.00 | +213.00 | pass | +| Pyright | yes | 1.12 | 1.32 | 100% | 4019.00 | 0.00 | pass | +| Pyrefly | yes | 2.33 | 2.63 | 100% | 3182.00 | -837.00 | pass | +| pylsp-mypy | yes | 177.83 | 178.98 | 100% | 4134.00 | +115.00 | pass | ### summarize definition @@ -74,10 +74,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.22 | 0.24 | 100% | 1.00 | 0.00 | pass | -| Pyrefly | yes | 0.23 | 0.26 | 100% | 1.00 | 0.00 | pass | -| Pyright | yes | 0.40 | 0.46 | 100% | 1.00 | 0.00 | pass | -| pylsp-mypy | yes | 1.05 | 1.10 | 100% | 1.00 | 0.00 | pass | +| Ty | yes | 0.20 | 0.21 | 100% | 1.00 | 0.00 | pass | +| Pyrefly | yes | 0.22 | 0.25 | 100% | 1.00 | 0.00 | pass | +| Pyright | yes | 0.41 | 0.45 | 100% | 1.00 | 0.00 | pass | +| pylsp-mypy | yes | 1.05 | 1.08 | 100% | 1.00 | 0.00 | pass | ### edit array then complete (edit+completion) @@ -85,10 +85,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| pylsp-mypy | no | 4.13 | 4.34 | 0% | 0.00 | -168.00 | fail (10) | -| Ty | yes | 10.78 | 11.35 | 100% | 168.00 | 0.00 | pass | -| Pyrefly | yes | 20.90 | 27.80 | 100% | 149.00 | -19.00 | pass | -| Pyright | yes | 370.53 | 453.48 | 100% | 168.00 | 0.00 | pass | +| pylsp-mypy | no | 4.15 | 4.26 | 0% | 0.00 | -168.00 | fail (10) | +| Ty | yes | 12.47 | 14.02 | 100% | 168.00 | 0.00 | pass | +| Pyrefly | yes | 28.55 | 77.89 | 100% | 149.00 | -19.00 | pass | +| Pyright | yes | 328.39 | 459.82 | 100% | 168.00 | 0.00 | pass | ### edit array then hover (edit+hover) @@ -96,10 +96,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 1.06 | 2.97 | 100% | 2546.00 | +2268.00 | pass | -| Ty | yes | 3.76 | 3.91 | 100% | 267.00 | -11.00 | pass | -| Pyright | yes | 34.53 | 36.47 | 100% | 278.00 | 0.00 | pass | -| pylsp-mypy | yes | 167.85 | 169.34 | 100% | 5662.00 | +5384.00 | pass | +| Pyrefly | yes | 4.57 | 6.26 | 100% | 2546.00 | +2268.00 | pass | +| Ty | yes | 5.85 | 5.89 | 100% | 267.00 | -11.00 | pass | +| Pyright | yes | 31.53 | 34.60 | 100% | 278.00 | 0.00 | pass | +| pylsp-mypy | yes | 166.72 | 168.28 | 100% | 5662.00 | +5384.00 | pass | ### Result Differences @@ -112,10 +112,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 259.60 | 2.54 | 5 | 25 | 100% | 0 | -| Pyrefly | yes | 272.62 | 3.99 | 5 | 25 | 100% | 0 | -| Pyright | yes | 1469.45 | 14.03 | 5 | 25 | 100% | 0 | -| pylsp-mypy | yes | 8045.82 | 182.14 | 5 | 25 | 100% | 0 | +| Ty | yes | 259.77 | 2.60 | 5 | 25 | 100% | 0 | +| Pyrefly | yes | 270.56 | 4.01 | 5 | 25 | 100% | 0 | +| Pyright | yes | 1482.86 | 13.72 | 5 | 25 | 100% | 0 | +| pylsp-mypy | yes | 7942.52 | 178.10 | 5 | 25 | 100% | 0 | ### queryset completion @@ -123,10 +123,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyright | yes | 4.70 | 7.37 | 100% | 10.00 | 0.00 | pass | -| Ty | yes | 4.85 | 7.17 | 100% | 261.00 | +251.00 | pass | -| Pyrefly | yes | 16.67 | 64.64 | 100% | 15.00 | +5.00 | pass | -| pylsp-mypy | yes | 224.94 | 694.83 | 100% | 2.00 | -8.00 | pass | +| Pyright | yes | 4.61 | 7.38 | 100% | 10.00 | 0.00 | pass | +| Ty | yes | 4.75 | 7.18 | 100% | 261.00 | +251.00 | pass | +| Pyrefly | yes | 15.68 | 61.12 | 100% | 15.00 | +5.00 | pass | +| pylsp-mypy | yes | 226.80 | 676.27 | 100% | 2.00 | -8.00 | pass | ### queryset filter hover @@ -134,10 +134,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.24 | 0.26 | 100% | 46.00 | -11.00 | pass | -| Pyrefly | yes | 0.41 | 0.46 | 100% | 298.00 | +241.00 | pass | -| Pyright | yes | 0.53 | 0.58 | 100% | 57.00 | 0.00 | pass | -| pylsp-mypy | yes | 158.86 | 161.94 | 100% | 57.00 | 0.00 | pass | +| Ty | yes | 0.23 | 0.25 | 100% | 46.00 | -11.00 | pass | +| Pyrefly | yes | 0.43 | 0.45 | 100% | 298.00 | +241.00 | pass | +| Pyright | yes | 0.55 | 0.61 | 100% | 57.00 | 0.00 | pass | +| pylsp-mypy | yes | 157.93 | 161.63 | 100% | 57.00 | 0.00 | pass | ### model definition @@ -145,10 +145,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.20 | 0.21 | 100% | 1.00 | 0.00 | pass | -| Pyrefly | yes | 0.32 | 0.41 | 100% | 1.00 | 0.00 | pass | -| Pyright | yes | 0.39 | 0.43 | 100% | 1.00 | 0.00 | pass | -| pylsp-mypy | yes | 1.09 | 1.13 | 100% | 1.00 | 0.00 | pass | +| Ty | yes | 0.21 | 0.21 | 100% | 1.00 | 0.00 | pass | +| Pyright | yes | 0.39 | 0.46 | 100% | 1.00 | 0.00 | pass | +| Pyrefly | yes | 0.41 | 0.43 | 100% | 1.00 | 0.00 | pass | +| pylsp-mypy | yes | 1.09 | 1.14 | 100% | 1.00 | 0.00 | pass | ### edit queryset then complete (edit+completion) @@ -156,10 +156,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 1.84 | 1.89 | 100% | 83.00 | -21.00 | pass | -| Ty | yes | 4.51 | 4.96 | 100% | 104.00 | 0.00 | pass | -| Pyright | yes | 25.76 | 28.27 | 100% | 104.00 | 0.00 | pass | -| pylsp-mypy | yes | 278.11 | 323.96 | 100% | 143.00 | +39.00 | pass | +| Pyrefly | yes | 2.75 | 3.82 | 100% | 83.00 | -21.00 | pass | +| Ty | yes | 4.61 | 4.72 | 100% | 104.00 | 0.00 | pass | +| Pyright | yes | 25.60 | 28.18 | 100% | 104.00 | 0.00 | pass | +| pylsp-mypy | yes | 257.36 | 293.91 | 100% | 143.00 | +39.00 | pass | ### edit queryset then hover (edit+hover) @@ -167,10 +167,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.71 | 0.74 | 100% | 858.00 | +775.00 | pass | -| Ty | yes | 2.89 | 2.94 | 100% | 100.00 | +17.00 | pass | -| Pyright | yes | 38.76 | 44.28 | 100% | 83.00 | 0.00 | pass | -| pylsp-mypy | yes | 247.68 | 253.73 | 100% | 71.00 | -12.00 | pass | +| Pyrefly | yes | 0.79 | 0.88 | 100% | 858.00 | +775.00 | pass | +| Ty | yes | 3.19 | 3.23 | 100% | 100.00 | +17.00 | pass | +| Pyright | yes | 37.43 | 45.40 | 100% | 83.00 | 0.00 | pass | +| pylsp-mypy | yes | 247.31 | 252.37 | 100% | 71.00 | -12.00 | pass | ### Result Differences @@ -183,10 +183,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 828.39 | 7.69 | 5 | 25 | 100% | 0 | -| Pyrefly | yes | 1098.59 | 27.84 | 5 | 25 | 100% | 0 | -| pylsp-mypy | yes | 7863.39 | 140.43 | 5 | 25 | 100% | 0 | -| Pyright | yes | 12026.90 | 179.57 | 5 | 25 | 100% | 0 | +| Ty | yes | 852.17 | 8.21 | 5 | 25 | 100% | 0 | +| Pyrefly | yes | 1295.68 | 32.03 | 5 | 25 | 100% | 0 | +| pylsp-mypy | yes | 8102.19 | 143.67 | 5 | 25 | 100% | 0 | +| Pyright | yes | 10800.19 | 150.43 | 5 | 25 | 100% | 0 | ### report dataframe completion @@ -194,10 +194,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 18.41 | 22.19 | 100% | 1000.00 | +728.80 | pass | -| Pyright | yes | 77.21 | 263.36 | 100% | 271.20 | 0.00 | pass | -| pylsp-mypy | yes | 89.91 | 199.14 | 100% | 6.00 | -265.20 | pass | -| Pyrefly | yes | 91.64 | 364.49 | 100% | 16.00 | -255.20 | pass | +| Ty | yes | 18.87 | 22.52 | 100% | 1000.00 | +728.80 | pass | +| Pyright | yes | 85.15 | 285.03 | 100% | 271.20 | 0.00 | pass | +| Pyrefly | yes | 89.34 | 356.41 | 100% | 16.00 | -255.20 | pass | +| pylsp-mypy | yes | 94.12 | 218.52 | 100% | 6.00 | -265.20 | pass | ### dataframe groupby hover @@ -205,10 +205,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.25 | 0.27 | 100% | 329.00 | -21.00 | pass | -| Pyright | yes | 0.79 | 0.90 | 100% | 350.00 | 0.00 | pass | -| Pyrefly | yes | 2.44 | 2.63 | 100% | 2759.00 | +2409.00 | pass | -| pylsp-mypy | yes | 194.17 | 199.56 | 100% | 301.00 | -49.00 | pass | +| Ty | yes | 0.27 | 0.28 | 100% | 329.00 | -21.00 | pass | +| Pyright | yes | 0.70 | 0.77 | 100% | 350.00 | 0.00 | pass | +| Pyrefly | yes | 2.40 | 2.54 | 100% | 2759.00 | +2409.00 | pass | +| pylsp-mypy | yes | 194.32 | 197.05 | 100% | 301.00 | -49.00 | pass | ### build report definition @@ -216,10 +216,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.23 | 0.29 | 100% | 1.00 | 0.00 | pass | -| Pyrefly | yes | 0.24 | 0.25 | 100% | 1.00 | 0.00 | pass | -| Pyright | yes | 0.45 | 0.54 | 100% | 1.00 | 0.00 | pass | -| pylsp-mypy | yes | 1.09 | 1.14 | 100% | 1.00 | 0.00 | pass | +| Ty | yes | 0.20 | 0.21 | 100% | 1.00 | 0.00 | pass | +| Pyrefly | yes | 0.25 | 0.26 | 100% | 1.00 | 0.00 | pass | +| Pyright | yes | 0.45 | 0.47 | 100% | 1.00 | 0.00 | pass | +| pylsp-mypy | yes | 1.08 | 1.12 | 100% | 1.00 | 0.00 | pass | ### edit dataframe then complete (edit+completion) @@ -227,10 +227,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 16.71 | 17.68 | 100% | 448.00 | +8.00 | pass | -| Pyrefly | yes | 44.10 | 67.19 | 100% | 256.00 | -184.00 | pass | -| pylsp-mypy | yes | 230.56 | 236.24 | 100% | 441.00 | +1.00 | pass | -| Pyright | yes | 809.83 | 1273.60 | 100% | 440.00 | 0.00 | pass | +| Ty | yes | 16.80 | 17.92 | 100% | 448.00 | +8.00 | pass | +| Pyrefly | yes | 41.33 | 59.91 | 100% | 256.00 | -184.00 | pass | +| pylsp-mypy | yes | 244.31 | 249.95 | 100% | 441.00 | +1.00 | pass | +| Pyright | yes | 653.49 | 1370.85 | 100% | 440.00 | 0.00 | pass | ### edit dataframe then hover (edit+hover) @@ -238,10 +238,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.78 | 0.84 | 100% | 943.00 | -3349.00 | pass | -| Ty | yes | 2.84 | 2.96 | 100% | 4441.00 | +149.00 | pass | -| Pyright | yes | 9.57 | 10.78 | 100% | 4292.00 | 0.00 | pass | -| pylsp-mypy | yes | 186.42 | 190.40 | 100% | 232.00 | -4060.00 | pass | +| Ty | yes | 4.90 | 4.93 | 100% | 4441.00 | +149.00 | pass | +| Pyright | yes | 12.38 | 15.05 | 100% | 4292.00 | 0.00 | pass | +| Pyrefly | yes | 26.83 | 83.79 | 100% | 943.00 | -3349.00 | pass | +| pylsp-mypy | yes | 184.52 | 186.72 | 100% | 232.00 | -4060.00 | pass | ### Result Differences @@ -254,10 +254,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 357.80 | 2.48 | 5 | 25 | 100% | 0 | -| Pyrefly | yes | 809.80 | 17.31 | 5 | 25 | 100% | 0 | -| Pyright | yes | 3671.70 | 50.35 | 5 | 25 | 100% | 0 | -| pylsp-mypy | no | 7226.75 | 127.07 | 5 | 25 | 60% | 2 | +| Ty | yes | 359.68 | 2.64 | 5 | 25 | 100% | 0 | +| Pyrefly | yes | 800.39 | 17.20 | 5 | 25 | 100% | 0 | +| Pyright | yes | 3633.40 | 48.44 | 5 | 25 | 100% | 0 | +| pylsp-mypy | no | 7220.44 | 126.02 | 5 | 25 | 60% | 2 | ### query completion @@ -265,10 +265,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 3.31 | 7.32 | 100% | 1.00 | 0.00 | pass | -| Pyright | yes | 7.47 | 13.35 | 100% | 1.00 | 0.00 | pass | -| Pyrefly | yes | 84.05 | 335.21 | 100% | 15.00 | +14.00 | pass | -| pylsp-mypy | yes | 223.34 | 409.40 | 100% | 1.00 | 0.00 | pass | +| Ty | yes | 3.38 | 7.77 | 100% | 1.00 | 0.00 | pass | +| Pyright | yes | 6.78 | 10.93 | 100% | 1.00 | 0.00 | pass | +| Pyrefly | yes | 83.60 | 333.55 | 100% | 15.00 | +14.00 | pass | +| pylsp-mypy | yes | 215.87 | 459.50 | 100% | 1.00 | 0.00 | pass | ### sessionmaker hover @@ -276,10 +276,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.41 | 0.43 | 100% | 10621.00 | +49.00 | pass | -| Pyrefly | yes | 1.06 | 1.13 | 100% | 15232.00 | +4660.00 | pass | -| Pyright | yes | 1.25 | 1.44 | 100% | 10572.00 | 0.00 | pass | -| pylsp-mypy | yes | 331.65 | 338.00 | 100% | 10498.00 | -74.00 | pass | +| Ty | yes | 0.41 | 0.42 | 100% | 10621.00 | +49.00 | pass | +| Pyrefly | yes | 0.95 | 1.01 | 100% | 15232.00 | +4660.00 | pass | +| Pyright | yes | 1.28 | 1.59 | 100% | 10572.00 | 0.00 | pass | +| pylsp-mypy | yes | 332.72 | 340.78 | 100% | 10498.00 | -74.00 | pass | ### mapped class definition @@ -287,10 +287,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.23 | 0.24 | 100% | 2.00 | +1.00 | pass | -| Pyrefly | yes | 0.24 | 0.26 | 100% | 1.00 | 0.00 | pass | -| Pyright | yes | 0.46 | 0.51 | 100% | 1.00 | 0.00 | pass | -| pylsp-mypy | yes | 1.19 | 1.34 | 100% | 1.00 | 0.00 | pass | +| Pyrefly | yes | 0.21 | 0.23 | 100% | 1.00 | 0.00 | pass | +| Ty | yes | 0.22 | 0.23 | 100% | 2.00 | +1.00 | pass | +| Pyright | yes | 0.42 | 0.47 | 100% | 1.00 | 0.00 | pass | +| pylsp-mypy | yes | 1.09 | 1.13 | 100% | 1.00 | 0.00 | pass | ### edit query then complete (edit+completion) @@ -298,10 +298,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.71 | 0.75 | 100% | 17.00 | -21.00 | pass | -| Ty | yes | 4.37 | 4.78 | 100% | 23.00 | -15.00 | pass | -| pylsp-mypy | no | 39.51 | 40.57 | 0% | 0.00 | -38.00 | fail (10) | -| Pyright | yes | 145.39 | 185.92 | 100% | 38.00 | 0.00 | pass | +| Pyrefly | yes | 0.74 | 0.77 | 100% | 17.00 | -21.00 | pass | +| Ty | yes | 4.82 | 5.32 | 100% | 23.00 | -15.00 | pass | +| pylsp-mypy | no | 40.02 | 40.62 | 0% | 0.00 | -38.00 | fail (10) | +| Pyright | yes | 140.86 | 205.00 | 100% | 38.00 | 0.00 | pass | ### edit session then hover (edit+hover) @@ -309,10 +309,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.49 | 0.52 | 100% | 2246.00 | +1346.00 | pass | -| Ty | yes | 4.10 | 4.18 | 100% | 958.00 | +58.00 | pass | -| pylsp-mypy | no | 39.67 | 41.49 | 0% | 0.00 | -900.00 | fail (10) | -| Pyright | yes | 97.16 | 105.77 | 100% | 900.00 | 0.00 | pass | +| Pyrefly | yes | 0.52 | 0.55 | 100% | 2246.00 | +1346.00 | pass | +| Ty | yes | 4.39 | 4.42 | 100% | 958.00 | +58.00 | pass | +| pylsp-mypy | no | 40.38 | 40.53 | 0% | 0.00 | -900.00 | fail (10) | +| Pyright | yes | 92.86 | 108.30 | 100% | 900.00 | 0.00 | pass | ### Result Differences @@ -326,10 +326,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 2730.05 | 4.89 | 5 | 25 | 100% | 0 | -| Pyright | yes | 15913.06 | 114.45 | 5 | 25 | 80% | 0 | -| Pyrefly | yes | 5401.79 | 169.92 | 5 | 25 | 80% | 0 | -| pylsp-mypy | no | 221534.85 | 1587.86 | 5 | 25 | 40% | 2 | +| Ty | yes | 2709.42 | 4.59 | 5 | 25 | 100% | 0 | +| Pyright | yes | 15992.37 | 110.40 | 5 | 25 | 80% | 0 | +| Pyrefly | yes | 5581.13 | 177.48 | 5 | 25 | 80% | 0 | +| pylsp-mypy | no | 184246.25 | 1559.35 | 5 | 25 | 40% | 2 | ### classifier pipeline completion @@ -337,10 +337,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 11.58 | 12.78 | 100% | 776.00 | +653.00 | pass | -| Pyright | yes | 50.67 | 77.69 | 100% | 123.00 | 0.00 | pass | -| pylsp-mypy | yes | 152.87 | 156.82 | 100% | 2.00 | -121.00 | pass | -| Pyrefly | yes | 836.29 | 3344.21 | 100% | 15.00 | -108.00 | pass | +| Ty | yes | 10.80 | 11.98 | 100% | 776.00 | +653.00 | pass | +| Pyright | yes | 52.88 | 84.92 | 100% | 123.00 | 0.00 | pass | +| pylsp-mypy | yes | 146.86 | 152.52 | 100% | 2.00 | -121.00 | pass | +| Pyrefly | yes | 863.10 | 3451.47 | 100% | 15.00 | -108.00 | pass | ### pipeline hover @@ -348,10 +348,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.21 | 0.22 | 100% | 48.00 | +14.00 | pass | +| Pyrefly | yes | 0.22 | 0.22 | 100% | 48.00 | +14.00 | pass | | Ty | yes | 0.23 | 0.26 | 100% | 7.00 | -27.00 | pass | -| Pyright | yes | 0.47 | 0.55 | 100% | 34.00 | 0.00 | pass | -| pylsp-mypy | no | 2846.33 | 2909.71 | 0% | 0.00 | -34.00 | fail (10) | +| Pyright | yes | 0.48 | 0.53 | 100% | 34.00 | 0.00 | pass | +| pylsp-mypy | no | 2770.92 | 2839.83 | 0% | 0.00 | -34.00 | fail (10) | ### auto tokenizer definition @@ -359,10 +359,10 @@ Method: `textDocument/definition` | Server | Success | Mean ms | P95 ms | Non-empty % | Definitions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.22 | 0.23 | 100% | 1.00 | 0.00 | pass | +| Pyrefly | yes | 0.22 | 0.22 | 100% | 1.00 | 0.00 | pass | | Ty | yes | 0.27 | 0.29 | 100% | 1.00 | 0.00 | pass | -| Pyright | yes | 0.48 | 0.67 | 100% | 1.00 | 0.00 | pass | -| pylsp-mypy | yes | 2229.58 | 2274.33 | 100% | 1.00 | 0.00 | pass | +| Pyright | yes | 0.44 | 0.52 | 100% | 1.00 | 0.00 | pass | +| pylsp-mypy | yes | 2224.23 | 2259.46 | 100% | 1.00 | 0.00 | pass | ### edit prediction then complete (edit+completion) @@ -370,10 +370,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| pylsp-mypy | yes | 2.54 | 2.65 | 0% | 0.00 | 0.00 | pass | -| Pyrefly | yes | 6.26 | 17.14 | 0% | 0.00 | 0.00 | pass | -| Ty | yes | 6.75 | 8.02 | 100% | 23.00 | +23.00 | pass | -| Pyright | yes | 7.72 | 9.29 | 0% | 0.00 | 0.00 | pass | +| pylsp-mypy | yes | 2.71 | 2.80 | 0% | 0.00 | 0.00 | pass | +| Ty | yes | 5.94 | 6.06 | 100% | 23.00 | +23.00 | pass | +| Pyright | yes | 6.90 | 8.96 | 0% | 0.00 | 0.00 | pass | +| Pyrefly | yes | 13.52 | 26.37 | 0% | 0.00 | 0.00 | pass | ### edit tokenizer then hover (edit+hover) @@ -381,10 +381,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 5.63 | 5.74 | 100% | 7.00 | -23.00 | pass | -| Pyrefly | yes | 6.61 | 22.64 | 100% | 33.00 | +3.00 | pass | -| Pyright | yes | 512.91 | 546.57 | 100% | 30.00 | 0.00 | pass | -| pylsp-mypy | no | 2707.97 | 2737.51 | 0% | 0.00 | -30.00 | fail (10) | +| Ty | yes | 5.73 | 5.89 | 100% | 7.00 | -23.00 | pass | +| Pyrefly | yes | 10.36 | 28.96 | 100% | 33.00 | +3.00 | pass | +| Pyright | yes | 491.31 | 518.60 | 100% | 30.00 | 0.00 | pass | +| pylsp-mypy | no | 2652.00 | 2674.70 | 0% | 0.00 | -30.00 | fail (10) | ### Result Differences @@ -397,10 +397,10 @@ Method: `textDocument/hover` | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Ty | yes | 321.72 | 2.79 | 5 | 25 | 100% | 0 | -| Pyright | yes | 1579.67 | 9.28 | 5 | 25 | 100% | 0 | -| Pyrefly | yes | 881.55 | 12.92 | 5 | 25 | 100% | 0 | -| pylsp-mypy | yes | 5131.83 | 116.81 | 5 | 25 | 100% | 0 | +| Ty | yes | 427.13 | 3.16 | 5 | 25 | 100% | 0 | +| Pyright | yes | 1560.39 | 9.30 | 5 | 25 | 100% | 0 | +| Pyrefly | yes | 900.20 | 14.26 | 5 | 25 | 100% | 0 | +| pylsp-mypy | yes | 4857.54 | 102.83 | 5 | 25 | 100% | 0 | ### request args completion @@ -408,10 +408,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyright | yes | 6.07 | 10.60 | 100% | 14.00 | 0.00 | pass | -| Ty | yes | 6.25 | 9.07 | 100% | 467.00 | +453.00 | pass | -| Pyrefly | yes | 56.00 | 184.05 | 100% | 487.80 | +473.80 | pass | -| pylsp-mypy | yes | 95.80 | 161.84 | 100% | 1.00 | -13.00 | pass | +| Pyright | yes | 4.69 | 8.81 | 100% | 14.00 | 0.00 | pass | +| Ty | yes | 6.53 | 9.17 | 100% | 467.00 | +453.00 | pass | +| Pyrefly | yes | 63.68 | 183.47 | 100% | 487.80 | +473.80 | pass | +| pylsp-mypy | yes | 68.68 | 116.51 | 100% | 1.00 | -13.00 | pass | ### client session hover @@ -419,10 +419,10 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Ty | yes | 0.22 | 0.24 | 100% | 7.00 | -19.00 | pass | -| Pyright | yes | 0.52 | 0.59 | 100% | 26.00 | 0.00 | pass | -| Pyrefly | yes | 5.34 | 18.56 | 100% | 167.00 | +141.00 | pass | -| pylsp-mypy | yes | 151.61 | 198.46 | 100% | 359.00 | +333.00 | pass | +| Ty | yes | 0.21 | 0.23 | 100% | 7.00 | -19.00 | pass | +| Pyright | yes | 0.52 | 0.62 | 100% | 26.00 | 0.00 | pass | +| Pyrefly | yes | 5.25 | 18.19 | 100% | 167.00 | +141.00 | pass | +| pylsp-mypy | yes | 110.69 | 235.70 | 100% | 359.00 | +333.00 | pass | ### client references @@ -430,10 +430,10 @@ Method: `textDocument/references` | Server | Success | Mean ms | P95 ms | Non-empty % | References found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.32 | 0.34 | 100% | 2.00 | 0.00 | pass | -| Ty | yes | 0.58 | 0.71 | 100% | 2.00 | 0.00 | pass | -| Pyright | yes | 0.79 | 0.95 | 100% | 2.00 | 0.00 | pass | -| pylsp-mypy | yes | 4.08 | 5.08 | 100% | 2.00 | 0.00 | pass | +| Pyrefly | yes | 0.34 | 0.35 | 100% | 2.00 | 0.00 | pass | +| Ty | yes | 0.68 | 0.75 | 100% | 2.00 | 0.00 | pass | +| Pyright | yes | 0.76 | 0.88 | 100% | 2.00 | 0.00 | pass | +| pylsp-mypy | yes | 20.40 | 62.90 | 100% | 2.00 | 0.00 | pass | ### edit response then complete (edit+completion) @@ -441,10 +441,10 @@ Method: `textDocument/completion` | Server | Success | Mean ms | P95 ms | Non-empty % | Completions found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.59 | 0.62 | 100% | 32.00 | -173.00 | pass | -| Ty | yes | 4.44 | 5.19 | 100% | 225.00 | +20.00 | pass | -| Pyright | yes | 4.84 | 6.02 | 100% | 205.00 | 0.00 | pass | -| pylsp-mypy | yes | 94.40 | 96.61 | 100% | 57.00 | -148.00 | pass | +| Pyrefly | yes | 0.56 | 0.57 | 100% | 32.00 | -173.00 | pass | +| Pyright | yes | 4.94 | 5.77 | 100% | 205.00 | 0.00 | pass | +| Ty | yes | 5.07 | 5.77 | 100% | 225.00 | +20.00 | pass | +| pylsp-mypy | yes | 86.27 | 88.97 | 100% | 57.00 | -148.00 | pass | ### edit response then hover (edit+hover) @@ -452,23 +452,23 @@ Method: `textDocument/hover` | Server | Success | Mean ms | P95 ms | Non-empty % | Hover length | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 2.34 | 4.75 | 100% | 9977.00 | +9557.00 | pass | -| Ty | yes | 2.44 | 2.49 | 100% | 1613.00 | +1193.00 | pass | -| Pyright | yes | 34.16 | 38.28 | 100% | 420.00 | 0.00 | pass | -| pylsp-mypy | yes | 238.17 | 245.23 | 100% | 880.00 | +460.00 | pass | +| Pyrefly | yes | 1.48 | 1.51 | 100% | 9977.00 | +9557.00 | pass | +| Ty | yes | 3.31 | 3.33 | 100% | 1555.00 | +1135.00 | pass | +| Pyright | yes | 35.61 | 41.53 | 100% | 420.00 | 0.00 | pass | +| pylsp-mypy | yes | 228.13 | 230.10 | 100% | 880.00 | +460.00 | pass | ### Result Differences - request args completion: result differences detected (1.00, 14.00, 467.00, 487.80). - client session hover: result differences detected (167.00, 26.00, 359.00, 7.00). - edit response then complete (edit+completion): result differences detected (205.00, 225.00, 32.00, 57.00). -- edit response then hover (edit+hover): result differences detected (1613.00, 420.00, 880.00, 9977.00). +- edit response then hover (edit+hover): result differences detected (1555.00, 420.00, 880.00, 9977.00). ## Benchmark: tsp_core | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Pyrefly | no | 223.92 | 0.32 | 8 | 40 | 100% | 2 | +| Pyrefly | no | 221.69 | 0.32 | 8 | 40 | 100% | 2 | ### builtins semantic tokens @@ -484,7 +484,7 @@ Method: `typeServer/getComputedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.21 | 0.22 | 100% | 7.00 | 0.00 | pass | +| Pyrefly | yes | 0.20 | 0.21 | 100% | 7.00 | 0.00 | pass | ### list declared type @@ -492,7 +492,7 @@ Method: `typeServer/getDeclaredType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.24 | 0.25 | 100% | 7.00 | 0.00 | pass | +| Pyrefly | yes | 0.24 | 0.28 | 100% | 7.00 | 0.00 | pass | ### generic specialization computed type @@ -500,7 +500,7 @@ Method: `typeServer/getComputedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.24 | 0.25 | 100% | 7.00 | 0.00 | pass | +| Pyrefly | yes | 0.23 | 0.25 | 100% | 7.00 | 0.00 | pass | ### stdlib path computed type @@ -508,7 +508,7 @@ Method: `typeServer/getComputedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.22 | 0.23 | 100% | 7.00 | 0.00 | pass | +| Pyrefly | yes | 0.25 | 0.29 | 100% | 7.00 | 0.00 | pass | ### function argument expected type @@ -516,13 +516,13 @@ Method: `typeServer/getExpectedType` | Server | Success | Mean ms | P95 ms | Non-empty % | Results found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 0.22 | 0.27 | 100% | 7.00 | 0.00 | pass | +| Pyrefly | yes | 0.24 | 0.26 | 100% | 7.00 | 0.00 | pass | ## Benchmark: tsp_semantic | Server | Success | Wall clock ms | Avg measured ms | Points | Measured requests | Non-empty % | Failed points | | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Pyrefly | yes | 5918.79 | 32.19 | 3 | 15 | 100% | 0 | +| Pyrefly | yes | 6119.76 | 44.02 | 3 | 15 | 100% | 0 | ### django semantic tokens @@ -530,7 +530,7 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 15.31 | 31.68 | 100% | 126.00 | 0.00 | pass | +| Pyrefly | yes | 31.34 | 63.97 | 100% | 126.00 | 0.00 | pass | ### transformers semantic tokens @@ -538,7 +538,7 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 71.02 | 87.82 | 100% | 74.00 | 0.00 | pass | +| Pyrefly | yes | 79.17 | 95.11 | 100% | 74.00 | 0.00 | pass | ### stdlib semantic tokens @@ -546,4 +546,4 @@ Method: semantic token impl using typeServer/getComputedType | Server | Success | Mean ms | P95 ms | Non-empty % | Semantic tokens found | Delta vs Pyright | Validation | | --- | --- | ---: | ---: | ---: | ---: | ---: | --- | -| Pyrefly | yes | 10.25 | 17.16 | 100% | 75.00 | 0.00 | pass | +| Pyrefly | yes | 21.54 | 29.70 | 100% | 75.00 | 0.00 | pass | diff --git a/latest-results/ty-20260917T060626Z-responses.jsonl b/latest-results/ty-20260918T060520Z-responses.jsonl similarity index 80% rename from latest-results/ty-20260917T060626Z-responses.jsonl rename to latest-results/ty-20260918T060520Z-responses.jsonl index 210846a..8fdb426 100644 --- a/latest-results/ty-20260917T060626Z-responses.jsonl +++ b/latest-results/ty-20260918T060520Z-responses.jsonl @@ -1,8 +1,8 @@ -{"suite": "data_science", "label": "dataframe completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 8, "character": 8, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "Literal[False]", "kind": 14, "label": "False", "sortText": " 0"}, {"detail": "None", "kind": 14, "label": "None", "sortText": " 1"}, {"detail": "Literal[True]", "kind": 14, "label": "True", "sortText": " 2"}, {"kind": 14, "label": "and", "sortText": " 3"}, {"kind": 14, "label": "as", "sortText": " 4"}, {"kind": 14, "label": "assert", "sortText": " 5"}, {"kind": 14, "label": "async", "sortText": " 6"}, {"kind": 14, "label": "await", "sortText": " 7"}, {"kind": 14, "label": "break", "sortText": " 8"}, {"kind": 14, "label": "case", "sortText": " 9"}, {"kind": 14, "label": "class", "sortText": " 10"}, {"kind": 14, "label": "continue", "sortText": " 11"}, {"kind": 14, "label": "def", "sortText": " 12"}, {"kind": 14, "label": "del", "sortText": " 13"}, {"kind": 14, "label": "elif", "sortText": " 14"}, {"kind": 14, "label": "else", "sortText": " 15"}, {"kind": 14, "label": "except", "sortText": " 16"}, {"kind": 14, "label": "finally", "sortText": " 17"}, {"kind": 14, "label": "for", "sortText": " 18"}, {"kind": 14, "label": "from", "sortText": " 19"}, {"kind": 14, "label": "global", "sortText": " 20"}, {"kind": 14, 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. 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For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = 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{"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "204"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "205"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "206"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "207"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "208"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "209"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "210"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "211"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "212"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "213"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "214"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "215"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "216"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "217"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "218"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "219"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "220"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "221"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). In-place versions of these functions are often\navailable as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.\nExceptions to this rule are documented.\n"}, "kind": 9, "label": "np", "sortText": " 37"}, {"detail": "", "kind": 9, "label": "pd", "sortText": " 38"}, {"detail": "def summarize(values: list[int]) -> DataFrame", "kind": 3, "label": "summarize", "sortText": " 39"}, {"detail": "DataFrame", "documentation": {"kind": "plaintext", "value": "Two-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), Point(2, 3)])\n x y\n0 0 0\n1 0 3\n2 2 3\n\nConstructing DataFrame from Series/DataFrame:\n\n>>> ser = pd.Series([1, 2, 3], index=[\"a\", \"b\", \"c\"])\n>>> df = pd.DataFrame(data=ser, index=[\"a\", \"c\"])\n>>> df\n 0\na 1\nc 3\n\n>>> df1 = pd.DataFrame([1, 2, 3], index=[\"a\", \"b\", \"c\"], columns=[\"x\"])\n>>> df2 = pd.DataFrame(data=df1, index=[\"a\", \"c\"])\n>>> df2\n x\na 1\nc 3\n"}, "kind": 22, "label": "summary", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 41"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all 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{"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. 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For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = 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"documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "204"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "205"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "206"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "207"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "208"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "209"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "210"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "211"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "212"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "213"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "214"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "215"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "216"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "217"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "218"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "219"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "220"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "221"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). In-place versions of these functions are often\navailable as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.\nExceptions to this rule are documented.\n"}, "kind": 9, "label": "np", "sortText": " 37"}, {"detail": "", "kind": 9, "label": "pd", "sortText": " 38"}, {"detail": "def summarize(values: list[int]) -> DataFrame", "kind": 3, "label": "summarize", "sortText": " 39"}, {"detail": "DataFrame", "documentation": {"kind": "plaintext", "value": "Two-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), 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{"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) 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This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). 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If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), 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"label": "StopAsyncIteration", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "204"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "205"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "206"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "207"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "208"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "209"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "210"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "211"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "212"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "213"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "214"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "215"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "216"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "217"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "218"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "219"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "220"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "221"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). 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If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), 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user.\n"}, "kind": 7, "label": "KeyboardInterrupt", "sortText": " 75"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for lookup errors.\n"}, "kind": 7, "label": "LookupError", "sortText": " 76"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Out of memory.\n"}, "kind": 7, "label": "MemoryError", "sortText": " 77"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Module not found.\n"}, "kind": 7, "label": "ModuleNotFoundError", "sortText": " 78"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Name not found globally.\n"}, "kind": 7, "label": "NameError", "sortText": " 79"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation only works on directories.\n"}, "kind": 7, "label": "NotADirectoryError", "sortText": " 80"}, {"detail": "NotImplementedType", "documentation": {"kind": "plaintext", "value": "The type of the NotImplemented singleton.\n"}, "kind": 22, "label": "NotImplemented", "sortText": " 81"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Method or function hasn't been implemented yet.\n"}, "kind": 7, "label": "NotImplementedError", "sortText": " 82"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "OSError", "sortText": " 83"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Result too large to be represented.\n"}, "kind": 7, "label": "OverflowError", "sortText": " 84"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about features which will be deprecated\nin the future.\n"}, "kind": 7, "label": "PendingDeprecationWarning", "sortText": " 85"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Not enough permissions.\n"}, "kind": 7, "label": "PermissionError", "sortText": " 86"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Process not found.\n"}, "kind": 7, "label": 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"label": "StopAsyncIteration", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "204"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "205"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "206"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "207"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "208"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "209"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "210"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "211"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "212"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "213"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "214"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "215"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "216"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "217"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "218"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "219"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "220"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "221"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). In-place versions of these functions are often\navailable as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.\nExceptions to this rule are documented.\n"}, "kind": 9, "label": "np", "sortText": " 37"}, {"detail": "", "kind": 9, "label": "pd", "sortText": " 38"}, {"detail": "def summarize(values: list[int]) -> DataFrame", "kind": 3, "label": "summarize", "sortText": " 39"}, {"detail": "DataFrame", "documentation": {"kind": "plaintext", "value": "Two-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), Point(2, 3)])\n x y\n0 0 0\n1 0 3\n2 2 3\n\nConstructing DataFrame from Series/DataFrame:\n\n>>> ser = pd.Series([1, 2, 3], index=[\"a\", \"b\", \"c\"])\n>>> df = pd.DataFrame(data=ser, index=[\"a\", \"c\"])\n>>> df\n 0\na 1\nc 3\n\n>>> df1 = pd.DataFrame([1, 2, 3], index=[\"a\", \"b\", \"c\"], columns=[\"x\"])\n>>> df2 = pd.DataFrame(data=df1, index=[\"a\", \"c\"])\n>>> df2\n x\na 1\nc 3\n"}, "kind": 22, "label": "summary", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 41"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all 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{"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. 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"documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "204"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "205"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "206"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "207"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "208"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "209"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "210"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "211"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "212"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "213"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "214"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "215"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "216"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "217"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "218"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "219"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "220"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "221"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). In-place versions of these functions are often\navailable as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.\nExceptions to this rule are documented.\n"}, "kind": 9, "label": "np", "sortText": " 37"}, {"detail": "", "kind": 9, "label": "pd", "sortText": " 38"}, {"detail": "def summarize(values: list[int]) -> DataFrame", "kind": 3, "label": "summarize", "sortText": " 39"}, {"detail": "DataFrame", "documentation": {"kind": "plaintext", "value": "Two-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), 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{"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) 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This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. 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An array object of arbitrary homogeneous items\n 2. Fast mathematical operations over arrays\n 3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage `_.\n\nWe recommend exploring the docstrings using\n`IPython `_, an advanced Python shell with\nTAB-completion and introspection capabilities. See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as ``np``::\n\n >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n >>> x = 42\n >>> x = x + 1\n\nUse the built-in ``help`` function to view a function's docstring::\n\n >>> help(np.sort)\n ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help. This is\nparticularly true if you see the line \"Help on ufunc object:\" at the top\nof the help() page. Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nAvailable subpackages\n---------------------\nlib\n Basic functions used by several sub-packages.\nrandom\n Core Random Tools\nlinalg\n Core Linear Algebra Tools\nfft\n Core FFT routines\npolynomial\n Polynomial tools\ntesting\n NumPy testing tools\n\nUtilities\n---------\ntest\n Run numpy unittests\nshow_config\n Show numpy build configuration\n__version__\n NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\n\nStart IPython and import `numpy` usually under the alias ``np``: `import\nnumpy as np`. Then, directly past or use the ``%cpaste`` magic to paste\nexamples into the shell. To see which functions are available in `numpy`,\ntype ``np.`` (where ```` refers to the TAB key), or use\n``np.*cos*?`` (where ```` refers to the ENTER key) to narrow\ndown the list. To view the docstring for a function, use\n``np.cos?`` (to view the docstring) and ``np.cos??`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`). 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If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = 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"label": "StopAsyncIteration", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "111"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "112"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "113"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "114"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "115"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "116"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "117"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "118"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "119"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "121"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "122"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "123"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "124"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "125"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "127"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "128"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "129"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "130"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "131"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "132"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "133"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "134"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "135"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "136"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "137"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "138"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "139"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "140"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "142"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "143"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "144"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "145"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "146"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "147"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "148"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "149"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "150"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "151"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "152"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "153"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "154"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "155"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "156"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "157"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "159"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "162"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "163"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "164"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "165"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "166"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "167"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "168"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "169"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "170"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "172"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "174"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "176"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "178"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "180"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "181"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "183"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "185"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "187"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "188"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "189"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "190"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "191"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "192"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "193"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "194"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "195"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "196"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "197"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "198"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "199"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "200"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "201"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "202"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "203"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "204"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "205"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "206"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "207"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "208"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "209"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "210"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "211"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "212"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "213"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "214"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "215"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "216"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "217"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "218"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "219"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "220"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "221"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__warningregistry__", "sortText": "222"}]}} {"suite": "data_science", "label": "dataframe describe hover", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 6, "character": 19, "iteration": 1, "result": {"contents": {"kind": "plaintext", "value": "class DataFrame(\n data=None,\n index: ExtensionArray | ndarray[_AnyShape, dtype[Any]] | Index | ... omitted 4 union elements = None,\n columns: ExtensionArray | ndarray[_AnyShape, dtype[Any]] | Index | ... omitted 4 union elements = None,\n dtype: ExtensionDtype | str | dtype[Any] | type | None = None,\n copy: bool | None = None\n)\n---------------------------------------------\nTwo-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), Point(2, 3)])\n x y\n0 0 0\n1 0 3\n2 2 3\n\nConstructing DataFrame from Series/DataFrame:\n\n>>> ser = pd.Series([1, 2, 3], index=[\"a\", \"b\", \"c\"])\n>>> df = pd.DataFrame(data=ser, index=[\"a\", \"c\"])\n>>> df\n 0\na 1\nc 3\n\n>>> df1 = pd.DataFrame([1, 2, 3], index=[\"a\", \"b\", \"c\"], columns=[\"x\"])\n>>> df2 = pd.DataFrame(data=df1, index=[\"a\", \"c\"])\n>>> df2\n x\na 1\nc 3\n"}, "range": {"end": {"character": 24, "line": 6}, "start": {"character": 15, "line": 6}}}} {"suite": "data_science", "label": "dataframe describe hover", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 6, "character": 19, "iteration": 2, "result": {"contents": {"kind": "plaintext", "value": "class DataFrame(\n data=None,\n index: ExtensionArray | ndarray[_AnyShape, dtype[Any]] | Index | ... omitted 4 union elements = None,\n columns: ExtensionArray | ndarray[_AnyShape, dtype[Any]] | Index | ... omitted 4 union elements = None,\n dtype: ExtensionDtype | str | dtype[Any] | type | None = None,\n copy: bool | None = None\n)\n---------------------------------------------\nTwo-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), Point(2, 3)])\n x y\n0 0 0\n1 0 3\n2 2 3\n\nConstructing DataFrame from Series/DataFrame:\n\n>>> ser = pd.Series([1, 2, 3], index=[\"a\", \"b\", \"c\"])\n>>> df = pd.DataFrame(data=ser, index=[\"a\", \"c\"])\n>>> df\n 0\na 1\nc 3\n\n>>> df1 = pd.DataFrame([1, 2, 3], index=[\"a\", \"b\", \"c\"], columns=[\"x\"])\n>>> df2 = pd.DataFrame(data=df1, index=[\"a\", \"c\"])\n>>> df2\n x\na 1\nc 3\n"}, "range": {"end": {"character": 24, "line": 6}, "start": {"character": 15, "line": 6}}}} {"suite": "data_science", "label": "dataframe describe hover", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 6, "character": 19, "iteration": 3, "result": {"contents": {"kind": "plaintext", "value": "class DataFrame(\n data=None,\n index: ExtensionArray | ndarray[_AnyShape, dtype[Any]] | Index | ... omitted 4 union elements = None,\n columns: ExtensionArray | ndarray[_AnyShape, dtype[Any]] | Index | ... omitted 4 union elements = None,\n dtype: ExtensionDtype | str | dtype[Any] | type | None = None,\n copy: bool | None = None\n)\n---------------------------------------------\nTwo-dimensional, size-mutable, potentially heterogeneous tabular data.\n\nData structure also contains labeled axes (rows and columns).\nArithmetic operations align on both row and column labels. Can be\nthought of as a dict-like container for Series objects. The primary\npandas data structure.\n\nParameters\n----------\ndata : ndarray (structured or homogeneous), Iterable, dict, or DataFrame\n Dict can contain Series, arrays, constants, dataclass or list-like objects. If\n data is a dict, column order follows insertion-order. If a dict contains Series\n which have an index defined, it is aligned by its index. This alignment also\n occurs if data is a Series or a DataFrame itself. Alignment is done on\n Series/DataFrame inputs.\n\n If data is a list of dicts, column order follows insertion-order.\n\nindex : Index or array-like\n Index to use for resulting frame. Will default to RangeIndex if\n no indexing information part of input data and no index provided.\ncolumns : Index or array-like\n Column labels to use for resulting frame when data does not have them,\n defaulting to RangeIndex(0, 1, 2, ..., n). If data contains column labels,\n will perform column selection instead.\ndtype : dtype, default None\n Data type to force. Only a single dtype is allowed. If None, infer.\ncopy : bool or None, default None\n Copy data from inputs.\n For dict data, the default of None behaves like ``copy=True``. For DataFrame\n or 2d ndarray input, the default of None behaves like ``copy=False``.\n If data is a dict containing one or more Series (possibly of different dtypes),\n ``copy=False`` will ensure that these inputs are not copied.\n\n .. versionchanged:: 1.3.0\n\nSee Also\n--------\nDataFrame.from_records : Constructor from tuples, also record arrays.\nDataFrame.from_dict : From dicts of Series, arrays, or dicts.\nread_csv : Read a comma-separated values (csv) file into DataFrame.\nread_table : Read general delimited file into DataFrame.\nread_clipboard : Read text from clipboard into DataFrame.\n\nNotes\n-----\nPlease reference the :ref:`User Guide ` for more information.\n\nExamples\n--------\nConstructing DataFrame from a dictionary.\n\n>>> d = {'col1': [1, 2], 'col2': [3, 4]}\n>>> df = pd.DataFrame(data=d)\n>>> df\n col1 col2\n0 1 3\n1 2 4\n\nNotice that the inferred dtype is int64.\n\n>>> df.dtypes\ncol1 int64\ncol2 int64\ndtype: object\n\nTo enforce a single dtype:\n\n>>> df = pd.DataFrame(data=d, dtype=np.int8)\n>>> df.dtypes\ncol1 int8\ncol2 int8\ndtype: object\n\nConstructing DataFrame from a dictionary including Series:\n\n>>> d = {'col1': [0, 1, 2, 3], 'col2': pd.Series([2, 3], index=[2, 3])}\n>>> pd.DataFrame(data=d, index=[0, 1, 2, 3])\n col1 col2\n0 0 NaN\n1 1 NaN\n2 2 2.0\n3 3 3.0\n\nConstructing DataFrame from numpy ndarray:\n\n>>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),\n... columns=['a', 'b', 'c'])\n>>> df2\n a b c\n0 1 2 3\n1 4 5 6\n2 7 8 9\n\nConstructing DataFrame from a numpy ndarray that has labeled columns:\n\n>>> data = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)],\n... dtype=[(\"a\", \"i4\"), (\"b\", \"i4\"), (\"c\", \"i4\")])\n>>> df3 = pd.DataFrame(data, columns=['c', 'a'])\n...\n>>> df3\n c a\n0 3 1\n1 6 4\n2 9 7\n\nConstructing DataFrame from dataclass:\n\n>>> from dataclasses import make_dataclass\n>>> Point = make_dataclass(\"Point\", [(\"x\", int), (\"y\", int)])\n>>> pd.DataFrame([Point(0, 0), Point(0, 3), Point(2, 3)])\n x y\n0 0 0\n1 0 3\n2 2 3\n\nConstructing DataFrame from Series/DataFrame:\n\n>>> ser = pd.Series([1, 2, 3], index=[\"a\", \"b\", \"c\"])\n>>> df = pd.DataFrame(data=ser, index=[\"a\", \"c\"])\n>>> df\n 0\na 1\nc 3\n\n>>> df1 = pd.DataFrame([1, 2, 3], index=[\"a\", \"b\", \"c\"], columns=[\"x\"])\n>>> df2 = pd.DataFrame(data=df1, index=[\"a\", \"c\"])\n>>> df2\n x\na 1\nc 3\n"}, "range": {"end": {"character": 24, "line": 6}, "start": {"character": 15, "line": 6}}}} @@ -13,11 +13,11 @@ {"suite": "data_science", "label": "summarize definition", "method": "textDocument/definition", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 15, "iteration": 3, "result": [{"range": {"end": {"character": 13, "line": 4}, "start": {"character": 4, "line": 4}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py"}]} {"suite": "data_science", "label": "summarize definition", "method": "textDocument/definition", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 15, "iteration": 4, "result": [{"range": {"end": {"character": 13, "line": 4}, "start": {"character": 4, "line": 4}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py"}]} {"suite": "data_science", "label": "summarize definition", "method": "textDocument/definition", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 15, "iteration": 5, "result": [{"range": {"end": {"character": 13, "line": 4}, "start": {"character": 4, "line": 4}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py"}]} -{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].diagonal(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].nonzero() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tolist() -> Any", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__iter__() -> Iterator[Any]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} -{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 2, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].diagonal(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].nonzero() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tolist() -> Any", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__iter__() -> Iterator[Any]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} -{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 3, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].diagonal(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].nonzero() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tolist() -> Any", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__iter__() -> Iterator[Any]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} -{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 4, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].diagonal(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].nonzero() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tolist() -> Any", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__iter__() -> Iterator[Any]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} -{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 5, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].diagonal(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].nonzero() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tolist() -> Any", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__iter__() -> Iterator[Any]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} +{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "Overload[[DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int], DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int, int], DTypeT], (offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "Overload[() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _2Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _3Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "Overload[[T]() -> Any, [T]() -> T, [T]() -> list[T], [T]() -> list[list[T]], [T]() -> list[list[list[T]]], () -> Any]", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "Overload[() -> Iterator[Any], [ScalarT]() -> Iterator[ScalarT], [DTypeT]() -> Iterator[ndarray[_AnyShape, DTypeT]], () -> Iterator[Any]]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} +{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 2, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "Overload[[DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int], DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int, int], DTypeT], (offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "Overload[() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _2Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _3Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "Overload[[T]() -> Any, [T]() -> T, [T]() -> list[T], [T]() -> list[list[T]], [T]() -> list[list[list[T]]], () -> Any]", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "Overload[() -> Iterator[Any], [ScalarT]() -> Iterator[ScalarT], [DTypeT]() -> Iterator[ndarray[_AnyShape, DTypeT]], () -> Iterator[Any]]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} +{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 3, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "Overload[[DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int], DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int, int], DTypeT], (offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "Overload[() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _2Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _3Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "Overload[[T]() -> Any, [T]() -> T, [T]() -> list[T], [T]() -> list[list[T]], [T]() -> list[list[list[T]]], () -> Any]", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "Overload[() -> Iterator[Any], [ScalarT]() -> Iterator[ScalarT], [DTypeT]() -> Iterator[ndarray[_AnyShape, DTypeT]], () -> Iterator[Any]]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} +{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 4, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "Overload[[DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int], DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int, int], DTypeT], (offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "Overload[() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _2Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _3Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "Overload[[T]() -> Any, [T]() -> T, [T]() -> list[T], [T]() -> list[list[T]], [T]() -> list[list[list[T]]], () -> Any]", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "Overload[() -> Iterator[Any], [ScalarT]() -> Iterator[ScalarT], [DTypeT]() -> Iterator[ndarray[_AnyShape, DTypeT]], () -> Iterator[Any]]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (lhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (lhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__rdivmod__", "sortText": "143"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "144"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "145"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "146"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rfloordiv__", "sortText": "147"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rlshift__", "sortText": "148"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmatmul__", "sortText": "149"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmod__", "sortText": "150"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rmul__", "sortText": "151"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__ror__", "sortText": "152"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rshift__", "sortText": "155"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} +{"suite": "data_science", "label": "edit array then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 31, "iteration": 5, "result": {"isIncomplete": true, "items": [{"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "T", "sortText": " 0"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "all", "sortText": " 1"}, {"detail": "Overload[(axis: None = None, out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> numpy.bool[builtins.bool], (axis: int | tuple[int, ...], out: None = None, keepdims: Literal[False] = False, *, where: _ArrayLikeBool_co = True) -> NDArray[numpy.bool[builtins.bool]], (axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co = True) -> ndarray[_AnyShape, dtype[numpy.bool[builtins.bool]]], [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: builtins.bool = False, where: _ArrayLikeBool_co = True) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, out: ArrayT, keepdims: builtins.bool = False, *, where: _ArrayLikeBool_co = True) -> ArrayT]", "kind": 2, "label": "any", "sortText": " 2"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmax", "sortText": " 3"}, {"detail": "Overload[(axis: SupportsIndex, out: None = None, *, keepdims: Literal[False] = False) -> NDArray[signedinteger[_NBitIntP]], (axis: SupportsIndex | None = None, out: None = None, *, keepdims: Literal[True]) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], [ArrayT](axis: SupportsIndex | None = None, *, out: ArrayT, keepdims: bool = False) -> ArrayT, [ArrayT](axis: SupportsIndex | None, out: ArrayT, *, keepdims: bool = False) -> ArrayT]", "kind": 2, "label": "argmin", "sortText": " 4"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: None, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[tuple[int], dtype[signedinteger[_NBitIntP]]], (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]]]", "kind": 2, "label": "argpartition", "sortText": " 5"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].argsort(axis: SupportsIndex | None = ..., kind: _SortKind | None = ..., order: Sequence[str] | None = ..., *, stable: bool | None = ..., descending: bool | None = ...) -> NDArray[signedinteger[_NBitIntP]]", "kind": 2, "label": "argsort", "sortText": " 6"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[ScalarT]], (dtype: DTypeLike | None, order: _OrderKACF = ..., casting: _CastingKind = ..., subok: bool = ..., copy: bool | _CopyMode = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "astype", "sortText": " 7"}, {"detail": "NDArray[Any] | None", "kind": 22, "label": "base", "sortText": " 8"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].byteswap(inplace: bool = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "byteswap", "sortText": " 9"}, {"detail": "Overload[(choices: ArrayLike, out: None = None, mode: _ModeKind = \"raise\") -> NDArray[Any], [ArrayT](choices: ArrayLike, out: ArrayT, mode: _ModeKind = \"raise\") -> ArrayT]", "kind": 2, "label": "choose", "sortText": " 10"}, {"detail": "Overload[(min: ArrayLike, max: ArrayLike | None = None, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], (min: None = None, *, max: ArrayLike, out: None = None, **kwargs: Any) -> NDArray[Any], [ArrayT](min: ArrayLike, max: ArrayLike | None, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: ArrayLike, max: ArrayLike | None = None, *, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT, [ArrayT](min: None = None, *, max: ArrayLike, out: ArrayT, **kwargs: Any) -> ArrayT]", "kind": 2, "label": "clip", "sortText": " 11"}, {"detail": "Overload[(condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, out: None = None) -> NDArray[Any], [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None, out: ArrayT) -> ArrayT, [ArrayT](condition: _ArrayLikeInt_co, axis: SupportsIndex | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "compress", "sortText": " 12"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conj() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conj", "sortText": " 13"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].conjugate() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "conjugate", "sortText": " 14"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].copy(order: _OrderKACF = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "copy", "sortText": " 15"}, {"detail": "_ctypes[int]", "kind": 22, "label": "ctypes", "sortText": " 16"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumprod", "sortText": " 17"}, {"detail": "Overload[(axis: None = None, dtype: None = None, out: None = None) -> ndarray[_1D, dtype[signedinteger[_NBitIntP]]], [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None = None, *, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ScalarT](axis: None, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[_1D, dtype[ScalarT]], (axis: None, dtype: DTypeLike, out: None = None) -> ndarray[_1D, dtype[Any]], [ArrayT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ArrayT, [ShapeT](axis: SupportsIndex, dtype: None = None, out: None = None) -> ndarray[ShapeT, dtype[signedinteger[_NBitIntP]]], [ShapeT, ScalarT](axis: SupportsIndex, dtype: _DTypeLike[ScalarT], out: None = None) -> ndarray[ShapeT, dtype[ScalarT]], [ShapeT](axis: SupportsIndex, dtype: DTypeLike, out: None = None) -> ndarray[ShapeT, dtype[Any]], [ArrayT](axis: SupportsIndex | None, dtype: DTypeLike | None, out: ArrayT) -> ArrayT, [ArrayT](axis: SupportsIndex | None = None, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "cumsum", "sortText": " 18"}, {"detail": "memoryview[int]", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 22, "label": "data", "sortText": " 19"}, {"detail": "Literal[\"cpu\"]", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 12, "label": "device", "sortText": " 20"}, {"detail": "Overload[[DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int], DTypeT], [DTypeT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[tuple[int, int], DTypeT], (offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "diagonal", "sortText": " 21"}, {"detail": "Overload[(b: _ScalarLike_co, /, out: None = None) -> NDArray[Any], (b: ArrayLike, /, out: None = None) -> Any, [ArrayT](b: ArrayLike, /, out: ArrayT) -> ArrayT]", "kind": 2, "label": "dot", "sortText": " 22"}, {"detail": "dtype[Unknown]", "kind": 22, "label": "dtype", "sortText": " 23"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dump(file: str | bytes | PathLike[str] | PathLike[bytes] | SupportsWrite[bytes]) -> None", "kind": 2, "label": "dump", "sortText": " 24"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].dumps() -> bytes", "kind": 2, "label": "dumps", "sortText": " 25"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].fill(value: Any) -> None", "kind": 2, "label": "fill", "sortText": " 26"}, {"detail": "flagsobj", "kind": 22, "label": "flags", "sortText": " 27"}, {"detail": "flatiter[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 22, "label": "flat", "sortText": " 28"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].flatten(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "flatten", "sortText": " 29"}, {"detail": "Overload[[ScalarT](dtype: _DTypeLike[ScalarT], offset: SupportsIndex = 0) -> NDArray[ScalarT], (dtype: DTypeLike, offset: SupportsIndex = 0) -> NDArray[Any]]", "kind": 2, "label": "getfield", "sortText": " 30"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "imag", "sortText": " 31"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].item[T](i0: SupportsIndex | tuple[SupportsIndex, ...] = ..., /, *args: SupportsIndex) -> T", "kind": 2, "label": "item", "sortText": " 32"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "itemsize", "sortText": " 33"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "mT", "sortText": " 34"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "max", "sortText": " 35"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "mean", "sortText": " 36"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ArrayT](axis: int | tuple[int, ...] | None = None, *, out: ArrayT, keepdims: numpy.bool[builtins.bool] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT]", "kind": 2, "label": "min", "sortText": " 37"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "nbytes", "sortText": " 38"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "ndim", "sortText": " 39"}, {"detail": "Overload[() -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _2Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> _3Tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]]], () -> tuple[ndarray[_1D, dtype[signedinteger[_NBitIntP]]], ...]]", "kind": 2, "label": "nonzero", "sortText": " 40"}, {"detail": "Overload[(kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: None = None) -> None, (kth: _ArrayLikeInt, /, axis: SupportsIndex = -1, kind: _PartitionKind = \"introselect\", order: Sequence[str] | None = None) -> None]", "kind": 2, "label": "partition", "sortText": " 41"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "prod", "sortText": " 42"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].put(indices: _ArrayLikeInt_co, values: ArrayLike, /, mode: _ModeKind = \"raise\") -> None", "kind": 2, "label": "put", "sortText": " 43"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].ravel(order: _OrderKACF = \"C\") -> ndarray[tuple[int], dtype[Unknown]]", "kind": 2, "label": "ravel", "sortText": " 44"}, {"detail": "ndarray[_AnyShape, dtype[Unknown]]", "kind": 22, "label": "real", "sortText": " 45"}, {"detail": "Overload[(repeats: _ArrayLikeInt_co, /, axis: None = None) -> ndarray[tuple[int], dtype[Unknown]], (repeats: _ArrayLikeInt_co, /, axis: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "repeat", "sortText": " 46"}, {"detail": "Overload[(shape: None, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[Never], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[()], dtype[Unknown]], [AnyShapeT](shape: AnyShapeT, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[AnyShapeT, dtype[Unknown]], (size1: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int], dtype[Unknown]], (size1: SupportsIndex, size2: SupportsIndex, size3: SupportsIndex, size4: SupportsIndex, /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[tuple[int, int, int, int], dtype[Unknown]], (size0: SupportsIndex, /, *shape: SupportsIndex, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], (shape: Sequence[SupportsIndex], /, *, order: _OrderACF = \"C\", copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "reshape", "sortText": " 47"}, {"detail": "Overload[(new_shape: _ShapeLike, /, *, refcheck: bool = True) -> None, (*new_shape: SupportsIndex, refcheck: bool = True) -> None]", "kind": 2, "label": "resize", "sortText": " 48"}, {"detail": "Overload[(decimals: SupportsIndex = 0, out: None = None) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](decimals: SupportsIndex, out: ArrayT) -> ArrayT, [ArrayT](decimals: SupportsIndex = 0, *, out: ArrayT) -> ArrayT]", "kind": 2, "label": "round", "sortText": " 49"}, {"detail": "Overload[(v: _ScalarLike_co, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> signedinteger[_NBitIntP], (v: ArrayLike, /, side: _SortSide = \"left\", sorter: _ArrayLikeInt_co | None = None) -> NDArray[signedinteger[_NBitIntP]]]", "kind": 2, "label": "searchsorted", "sortText": " 50"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setfield(val: ArrayLike, /, dtype: DTypeLike, offset: SupportsIndex = 0) -> None", "kind": 2, "label": "setfield", "sortText": " 51"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].setflags(*, write: bool | None = None, align: bool | None = None, uic: bool | None = None) -> None", "kind": 2, "label": "setflags", "sortText": " 52"}, {"detail": "_AnyShape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "shape", "sortText": " 53"}, {"detail": "int", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 22, "label": "size", "sortText": " 54"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].sort(axis: SupportsIndex = -1, kind: _SortKind | None = None, order: Sequence[str] | None = None, *, stable: bool | None = None, descending: bool | None = None) -> None", "kind": 2, "label": "sort", "sortText": " 55"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].squeeze(axis: SupportsIndex | tuple[SupportsIndex, ...] | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "squeeze", "sortText": " 56"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "std", "sortText": " 57"}, {"detail": "_Shape", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 22, "label": "strides", "sortText": " 58"}, {"detail": "Overload[[ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> signedinteger[_NBitIntP], (axis: int | tuple[int, ...], dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[signedinteger[_NBitIntP]], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, *, keepdims: Literal[True], initial: _IntLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[signedinteger[_NBitIntP]]], (axis: None = None, dtype: None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, [ArrayT](axis: int | tuple[int, ...] | None, dtype: DTypeLike | None, out: ArrayT, *, keepdims: bool | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[False] | _NoValueType = ..., initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, *, keepdims: Literal[True], initial: _NumberLike_co | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "sum", "sortText": " 59"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].swapaxes(axis1: SupportsIndex, axis2: SupportsIndex, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "swapaxes", "sortText": " 60"}, {"detail": "Overload[[ScalarT](indices: _IntLike_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ScalarT, (indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., out: None = None, mode: _ModeKind = ...) -> ndarray[_AnyShape, dtype[Unknown]], [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None = ..., *, out: ArrayT, mode: _ModeKind = ...) -> ArrayT, [ArrayT](indices: _ArrayLikeInt_co, /, axis: SupportsIndex | None, out: ArrayT, mode: _ModeKind = ...) -> ArrayT]", "kind": 2, "label": "take", "sortText": " 61"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].to_device(device: Literal[\"cpu\"], /, *, stream: int | Any | None = ...) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "to_device", "sortText": " 62"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tobytes(order: _OrderKACF = ...) -> bytes", "kind": 2, "label": "tobytes", "sortText": " 63"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].tofile(fid: str | bytes | PathLike[str] | PathLike[bytes] | _SupportsFileMethods, /, sep: str = \"\", format: str = \"%s\") -> None", "kind": 2, "label": "tofile", "sortText": " 64"}, {"detail": "Overload[[T]() -> Any, [T]() -> T, [T]() -> list[T], [T]() -> list[list[T]], [T]() -> list[list[list[T]]], () -> Any]", "kind": 2, "label": "tolist", "sortText": " 65"}, {"detail": "Overload[(offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, out: None = None) -> Any, [ArrayT](offset: SupportsIndex = 0, axis1: SupportsIndex = 0, axis2: SupportsIndex = 1, dtype: DTypeLike | None = None, *, out: ArrayT) -> ArrayT, [ArrayT](offset: SupportsIndex, axis1: SupportsIndex, axis2: SupportsIndex, dtype: DTypeLike | None, out: ArrayT) -> ArrayT]", "kind": 2, "label": "trace", "sortText": " 66"}, {"detail": "Overload[(axes: _ShapeLike | None, /) -> ndarray[_AnyShape, dtype[Unknown]], (*axes: SupportsIndex) -> ndarray[_AnyShape, dtype[Unknown]]]", "kind": 2, "label": "transpose", "sortText": " 67"}, {"detail": "Overload[(axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[float64], (axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[float64]], [ScalarT](axis: None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...], dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, [ScalarT](axis: None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ScalarT, [ScalarT](axis: int | tuple[int, ...] | None = None, *, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...] | None, dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](axis: int | tuple[int, ...], dtype: _DTypeLike[ScalarT], out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> NDArray[ScalarT], [ArrayT](axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, *, out: ArrayT, ddof: float = 0, keepdims: bool | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ArrayT, (axis: None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> Any, (axis: int | tuple[int, ...], dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[False] | _NoValueType = ..., where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]], (axis: int | tuple[int, ...] | None = None, dtype: DTypeLike | None = None, out: None = None, ddof: float = 0, *, keepdims: Literal[True], where: _ArrayLikeBool_co | _NoValueType = ..., mean: _ArrayLikeNumber_co | _NoValueType = ..., correction: float | _NoValueType = ...) -> ndarray[_AnyShape, dtype[Any]]]", "kind": 2, "label": "var", "sortText": " 68"}, {"detail": "Overload[() -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT | _HasDType[DTypeT]) -> ndarray[_AnyShape, DTypeT], [ScalarT](dtype: _DTypeLike[ScalarT]) -> ndarray[_AnyShape, dtype[ScalarT]], [ArrayT](*, type: type[ArrayT]) -> ArrayT, [ArrayT](dtype: type[ArrayT]) -> ArrayT, (dtype: DTypeLike) -> ndarray[_AnyShape, dtype[Any]], [ArrayT](dtype: DTypeLike, type: type[ArrayT]) -> ArrayT]", "kind": 2, "label": "view", "sortText": " 69"}, {"detail": "Overload[[ShapeT, NBitT]() -> ndarray[ShapeT, dtype[floating[NBitT]]], [ArrayT]() -> ArrayT]", "kind": 2, "label": "__abs__", "sortText": " 70"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__add__", "sortText": " 71"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__and__", "sortText": " 72"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": " 73"}, {"detail": "Overload[(dtype: None = None, /, *, copy: bool | None = None) -> ndarray[_AnyShape, dtype[Unknown]], [DTypeT](dtype: DTypeT, /, *, copy: bool | None = None) -> ndarray[_AnyShape, DTypeT]]", "kind": 2, "label": "__array__", "sortText": " 74"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_finalize__(obj: NDArray[Any] | None, /) -> None", "kind": 2, "label": "__array_finalize__", "sortText": " 75"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_function__(func: (...) -> Any, types: Iterable[type], args: Iterable[Any], kwargs: Mapping[str, Any]) -> Any", "kind": 2, "label": "__array_function__", "sortText": " 76"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__array_interface__", "sortText": " 77"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_namespace__(*, api_version: _ArrayAPIVersion | None = None) -> ModuleType", "kind": 2, "label": "__array_namespace__", "sortText": " 78"}, {"detail": "float", "kind": 22, "label": "__array_priority__", "sortText": " 79"}, {"detail": "CapsuleType", "documentation": {"kind": "plaintext", "value": "Capsule objects let you wrap a C \"void *\" pointer in a Python\nobject. They're a way of passing data through the Python interpreter\nwithout creating your own custom type.\n\nCapsules are used for communication between extension modules.\nThey provide a way for an extension module to export a C interface\nto other extension modules, so that extension modules can use the\nPython import mechanism to link to one another.\n"}, "kind": 22, "label": "__array_struct__", "sortText": " 80"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_ufunc__(ufunc: ufunc, method: Literal[\"__call__\", \"reduce\", \"reduceat\", \"accumulate\", \"outer\", \"at\"], /, *inputs: Any, **kwargs: Any) -> Any", "kind": 2, "label": "__array_ufunc__", "sortText": " 81"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__array_wrap__[ShapeT, DTypeT](array: ndarray[ShapeT, DTypeT], context: tuple[ufunc, tuple[Any, ...], int] | None = ..., return_scalar: bool = ..., /) -> ndarray[ShapeT, DTypeT]", "kind": 2, "label": "__array_wrap__", "sortText": " 82"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__bool__() -> bool", "kind": 2, "label": "__bool__", "sortText": " 83"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__buffer__(flags: int, /) -> memoryview[int]", "kind": 2, "label": "__buffer__", "sortText": " 84"}, {"detail": "type[ndarray[_AnyShape, dtype[Unknown]]]", "kind": 7, "label": "__class__", "sortText": " 85"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__class_getitem__(item: Any, /) -> GenericAlias", "kind": 2, "label": "__class_getitem__", "sortText": " 86"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__complex__() -> complex", "kind": 2, "label": "__complex__", "sortText": " 87"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__contains__(value: object, /) -> bool", "kind": 2, "label": "__contains__", "sortText": " 88"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__copy__() -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__copy__", "sortText": " 89"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__deepcopy__(memo: dict[int, Any] | None, /) -> ndarray[_AnyShape, dtype[Unknown]]", "kind": 2, "label": "__deepcopy__", "sortText": " 90"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": " 91"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": " 92"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": " 93"}, {"detail": "Overload[[ScalarT](rhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](rhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (rhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (rhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (rhs: _ArrayLikeInt_co, /) -> _2Tuple[NDArray[signedinteger[Any]]], (rhs: _ArrayLikeFloat_co, /) -> _2Tuple[NDArray[floating[Any]]], (rhs: _ArrayLike[timedelta64[Any]], /) -> tuple[NDArray[signedinteger[_64Bit]], NDArray[timedelta64[Any]]]]", "kind": 2, "label": "__divmod__", "sortText": " 94"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack__(*, stream: int | Any | None = None, max_version: tuple[int, int] | None = None, dl_device: tuple[int, int] | None = None, copy: bool | None = None) -> CapsuleType", "kind": 2, "label": "__dlpack__", "sortText": " 95"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__dlpack_device__() -> tuple[Literal[1], Literal[0]]", "kind": 2, "label": "__dlpack_device__", "sortText": " 96"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": " 97"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__eq__(other: Any, /) -> Any", "kind": 2, "label": "__eq__", "sortText": " 98"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__float__() -> float", "kind": 2, "label": "__float__", "sortText": " 99"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[signedinteger[_64Bit]], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__floordiv__", "sortText": "100"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "101"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__ge__", "sortText": "102"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "103"}, {"detail": "Overload[(key: _ArrayInt_co | tuple[_ArrayInt_co, ...], /) -> ndarray[_AnyShape, dtype[Unknown]], (key: SupportsIndex | tuple[SupportsIndex, ...], /) -> Any, (key: _ToIndices, /) -> ndarray[_AnyShape, dtype[Unknown]], (key: str, /) -> ndarray[_AnyShape, dtype[Any]], (key: list[str], /) -> ndarray[_AnyShape, dtype[void]]]", "kind": 2, "label": "__getitem__", "sortText": "104"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "105"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__gt__", "sortText": "106"}, {"detail": "None", "documentation": {"kind": "plaintext", "value": "The type of the None singleton.\n"}, "kind": 22, "label": "__hash__", "sortText": "107"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeBytes_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iadd__", "sortText": "108"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__iand__", "sortText": "109"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ifloordiv__", "sortText": "110"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ilshift__", "sortText": "111"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imatmul__", "sortText": "112"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLike[timedelta64[Any]], /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imod__", "sortText": "113"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__imul__", "sortText": "114"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__index__() -> int", "kind": 2, "label": "__index__", "sortText": "115"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__init__() -> None", "kind": 2, "label": "__init__", "sortText": "116"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "117"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__int__() -> int", "kind": 2, "label": "__int__", "sortText": "118"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__invert__[ArrayT]() -> ArrayT", "kind": 2, "label": "__invert__", "sortText": "119"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ior__", "sortText": "120"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ipow__", "sortText": "121"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__irshift__", "sortText": "122"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeTD64_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__isub__", "sortText": "123"}, {"detail": "Overload[() -> Iterator[Any], [ScalarT]() -> Iterator[ScalarT], [DTypeT]() -> Iterator[ndarray[_AnyShape, DTypeT]], () -> Iterator[Any]]", "kind": 2, "label": "__iter__", "sortText": "124"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeComplex_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeFloat_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__itruediv__", "sortText": "125"}, {"detail": "Overload[[ArrayT](other: _ArrayLikeBool_co, /) -> ArrayT, [ArrayT](other: _ArrayLikeInt_co, /) -> ArrayT, [ArrayT](other: object, /) -> ArrayT]", "kind": 2, "label": "__ixor__", "sortText": "126"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__le__", "sortText": "127"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__len__() -> int", "kind": 2, "label": "__len__", "sortText": "128"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__lshift__", "sortText": "129"}, {"detail": "Overload[(other: _ArrayLikeNumber_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeTD64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeDT64_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeBytes_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeStr_co | _ArrayLikeString_co, /) -> NDArray[bool[bool]], (other: object, /) -> NDArray[bool[bool]], (other: _ArrayLikeObject_co, /) -> NDArray[bool[bool]]]", "kind": 2, "label": "__lt__", "sortText": "130"}, {"detail": "Overload[[ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__matmul__", "sortText": "131"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mod__", "sortText": "132"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "133"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeInt, /) -> ndarray[tuple[Any, ...], dtype[Unknown]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__mul__", "sortText": "134"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__ne__(other: Any, /) -> Any", "kind": 2, "label": "__ne__", "sortText": "135"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__neg__[ArrayT]() -> ArrayT", "kind": 2, "label": "__neg__", "sortText": "136"}, {"detail": "def __new__[Self](cls, shape: _ShapeLike, dtype: DTypeLike | None = ..., buffer: Unknown | None = ..., offset: SupportsIndex = ..., strides: _ShapeLike | None = ..., order: _OrderKACF = ...) -> Self", "kind": 3, "label": "__new__", "sortText": "137"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__or__", "sortText": "138"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__pos__[ArrayT]() -> ArrayT", "kind": 2, "label": "__pos__", "sortText": "139"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], mod: None = None, /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, mod: None = None, /) -> NDArray[signedinteger[_8Bit]], [ScalarT](other: _ArrayLike[ScalarT], mod: None = None, /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, mod: None = None, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], mod: None = None, /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, mod: None = None, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], mod: None = None, /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, mod: None = None, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, mod: None = None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__pow__", "sortText": "140"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> NDArray[numpy.bool[builtins.bool]], [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeBytes_co, /) -> NDArray[bytes_], (other: _ArrayLikeStr_co, /) -> NDArray[str_], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__radd__", "sortText": "141"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rand__", "sortText": "142"}, {"detail": "Overload[[ScalarT](lhs: int | numpy.bool[builtins.bool], /) -> _2Tuple[ndarray[_AnyShape, dtype[ScalarT]]], [ScalarT](lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeBool_co, /) -> _2Tuple[NDArray[signedinteger[_8Bit]]], [ScalarT](lhs: _ArrayLike[ScalarT], /) -> _2Tuple[NDArray[ScalarT]], (lhs: _ArrayLikeFloat64_co, /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLike[floating[_64Bit]], /) -> _2Tuple[NDArray[float64]], (lhs: _ArrayLikeUInt_co, /) -> _2Tuple[NDArray[unsignedinteger[Any]]], (lhs: _ArrayLikeInt_co, /) -> 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None, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, mod: None = None, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, mod: None = None, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, mod: None = None, /) -> NDArray[number[Any, Any]], (other: Any, mod: None = None, /) -> Any, (other: _ArrayLikeObject_co, mod: None = None, /) -> Any]", "kind": 2, "label": "__rpow__", "sortText": "153"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rrshift__", "sortText": "154"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[signedinteger[_8Bit]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> 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NDArray[timedelta64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rsub__", "sortText": "156"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rtruediv__", "sortText": "157"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__rxor__", "sortText": "158"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "159"}, {"detail": "Overload[(key: _ToIndices, value: object, /) -> None, (key: _ToIndices, value: _ConvertibleToInt | _NestedSequence[_ConvertibleToInt] | _ArrayLikeInt_co, /) -> None, (key: _ToIndices, value: _ConvertibleToFloat | _NestedSequence[_ConvertibleToFloat | None] | _ArrayLikeFloat_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToComplex | _NestedSequence[_ConvertibleToComplex | None] | _ArrayLikeNumber_co | None, /) -> None, (key: _ToIndices, value: _ConvertibleToTD64 | _NestedSequence[_ConvertibleToTD64], /) -> None, (key: _ToIndices, value: _ConvertibleToDT64 | _NestedSequence[_ConvertibleToDT64], /) -> None, (key: str | list[str], value: object, /) -> None, (key: _ToIndices, value: ArrayLike, /) -> None]", "kind": 2, "label": "__setitem__", "sortText": "160"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__setstate__[_DTypeT_co](state: tuple[SupportsIndex, _ShapeLike, _DTypeT_co, bool[bool], bytes | list[Any]], /) -> None", "kind": 2, "label": "__setstate__", "sortText": "161"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "162"}, {"detail": "bound method ndarray[_AnyShape, dtype[Unknown]].__str__() -> str", "kind": 2, "label": "__str__", "sortText": "163"}, {"detail": "Overload[[ScalarT](other: int | numpy.bool[builtins.bool], /) -> ndarray[_AnyShape, dtype[ScalarT]], [ScalarT](other: _ArrayLikeBool_co, /) -> NDArray[ScalarT], (other: _ArrayLikeBool_co, /) -> Never, [ScalarT](other: _ArrayLike[ScalarT], /) -> NDArray[ScalarT], (other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLikeComplex_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[timedelta64[Any]], (other: _ArrayLikeTD64_co, /) -> NDArray[datetime64[Any]], (other: _ArrayLikeDT64_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__sub__", "sortText": "164"}, {"detail": "bound method type[ndarray[_AnyShape, dtype[Unknown]]].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "165"}, {"detail": "Overload[(other: _ArrayLikeFloat64_co, /) -> NDArray[float64], (other: _ArrayLikeInt_co | _ArrayLike[floating[_64Bit]], /) -> NDArray[float64], (other: _ArrayLikeComplex128_co, /) -> NDArray[complex128], (other: _ArrayLike[complexfloating[_64Bit, _64Bit]], /) -> NDArray[complex128], (other: _ArrayLikeFloat_co, /) -> NDArray[floating[Any]], (other: _ArrayLike[floating[Any]], /) -> NDArray[floating[Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLike[complexfloating[Any, Any]], /) -> NDArray[complexfloating[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[inexact[Any, Any]], (other: _ArrayLikeNumber_co, /) -> NDArray[number[Any, Any]], (other: _ArrayLike[timedelta64[Any]], /) -> NDArray[float64], (other: _ArrayLikeBool_co, /) -> Never, (other: _ArrayLikeFloat_co, /) -> NDArray[timedelta64[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__truediv__", "sortText": "166"}, {"detail": "Overload[(other: _ArrayLikeBool_co, /) -> NDArray[bool[bool]], (other: _ArrayLikeUInt_co, /) -> NDArray[unsignedinteger[Any]], (other: _ArrayLikeInt_co, /) -> NDArray[signedinteger[Any]], (other: Any, /) -> Any, (other: _ArrayLikeObject_co, /) -> Any]", "kind": 2, "label": "__xor__", "sortText": "167"}]}} {"suite": "data_science", "label": "edit array then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 15, "iteration": 1, "result": {"contents": {"kind": "plaintext", "value": "def array(\n object: Any,\n dtype: DTypeLike | None = None,\n *,\n copy: bool | _CopyMode | None = True,\n order: _OrderKACF = \"K\",\n subok: bool = False,\n ndmin: int = 0,\n ndmax: int = 0,\n like: _SupportsArrayFunc | None = None\n) -> NDArray[Any]"}, "range": {"end": {"character": 19, "line": 10}, "start": {"character": 14, "line": 10}}}} {"suite": "data_science", "label": "edit array then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 15, "iteration": 2, "result": {"contents": {"kind": "plaintext", "value": "def array(\n object: Any,\n dtype: DTypeLike | None = None,\n *,\n copy: bool | _CopyMode | None = True,\n order: _OrderKACF = \"K\",\n subok: bool = False,\n ndmin: int = 0,\n ndmax: int = 0,\n like: _SupportsArrayFunc | None = None\n) -> NDArray[Any]"}, "range": {"end": {"character": 19, "line": 10}, "start": {"character": 14, "line": 10}}}} {"suite": "data_science", "label": "edit array then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/src/analysis.py", "line": 10, "character": 15, "iteration": 3, "result": {"contents": {"kind": "plaintext", "value": "def array(\n object: Any,\n dtype: DTypeLike | None = None,\n *,\n copy: bool | _CopyMode | None = True,\n order: _OrderKACF = \"K\",\n subok: bool = False,\n ndmin: int = 0,\n ndmax: int = 0,\n like: _SupportsArrayFunc | None = None\n) -> NDArray[Any]"}, "range": {"end": {"character": 19, "line": 10}, "start": {"character": 14, "line": 10}}}} @@ -98,11 +98,11 @@ {"suite": "sqlalchemy", "label": "edit session then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/sqlalchemy/src/models.py", "line": 18, "character": 24, "iteration": 3, "result": {"contents": {"kind": "plaintext", "value": "def scalars[_T](\n statement: TypedReturnsRows[tuple[_T]],\n params: Sequence[Mapping[str, Any]] | Mapping[str, Any] | None = None,\n *,\n execution_options: _OrmKnownExecutionOptions | Mapping[str, Any] = ...,\n bind_arguments: dict[str, Any] | None = None,\n **kw: Any\n) -> ScalarResult[_T]\n---------------------------------------------\nExecute a statement and return the results as scalars.\n\nUsage and parameters are the same as that of\n:meth:`_orm.Session.execute`; the return result is a\n:class:`_result.ScalarResult` filtering object which\nwill return single elements rather than :class:`_row.Row` objects.\n\n:return: a :class:`_result.ScalarResult` object\n\n.. versionadded:: 1.4.24 Added :meth:`_orm.Session.scalars`\n\n.. versionadded:: 1.4.26 Added :meth:`_orm.scoped_session.scalars`\n\n.. seealso::\n\n :ref:`orm_queryguide_select_orm_entities` - contrasts the behavior\n of :meth:`_orm.Session.execute` to :meth:`_orm.Session.scalars`\n"}, "range": {"end": {"character": 28, "line": 18}, "start": {"character": 21, "line": 18}}}} {"suite": "sqlalchemy", "label": "edit session then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/sqlalchemy/src/models.py", "line": 18, "character": 24, "iteration": 4, "result": {"contents": {"kind": "plaintext", "value": "def scalars[_T](\n statement: TypedReturnsRows[tuple[_T]],\n params: Sequence[Mapping[str, Any]] | Mapping[str, Any] | None = None,\n *,\n execution_options: _OrmKnownExecutionOptions | Mapping[str, Any] = ...,\n bind_arguments: dict[str, Any] | None = None,\n **kw: Any\n) -> ScalarResult[_T]\n---------------------------------------------\nExecute a statement and return the results as scalars.\n\nUsage and parameters are the same as that of\n:meth:`_orm.Session.execute`; the return result is a\n:class:`_result.ScalarResult` filtering object which\nwill return single elements rather than :class:`_row.Row` objects.\n\n:return: a :class:`_result.ScalarResult` object\n\n.. versionadded:: 1.4.24 Added :meth:`_orm.Session.scalars`\n\n.. versionadded:: 1.4.26 Added :meth:`_orm.scoped_session.scalars`\n\n.. seealso::\n\n :ref:`orm_queryguide_select_orm_entities` - contrasts the behavior\n of :meth:`_orm.Session.execute` to :meth:`_orm.Session.scalars`\n"}, "range": {"end": {"character": 28, "line": 18}, "start": {"character": 21, "line": 18}}}} {"suite": "sqlalchemy", "label": "edit session then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/sqlalchemy/src/models.py", "line": 18, "character": 24, "iteration": 5, "result": {"contents": {"kind": "plaintext", "value": "def scalars[_T](\n statement: TypedReturnsRows[tuple[_T]],\n params: Sequence[Mapping[str, Any]] | Mapping[str, Any] | None = None,\n *,\n execution_options: _OrmKnownExecutionOptions | Mapping[str, Any] = ...,\n bind_arguments: dict[str, Any] | None = None,\n **kw: Any\n) -> ScalarResult[_T]\n---------------------------------------------\nExecute a statement and return the results as scalars.\n\nUsage and parameters are the same as that of\n:meth:`_orm.Session.execute`; the return result is a\n:class:`_result.ScalarResult` filtering object which\nwill return single elements rather than :class:`_row.Row` objects.\n\n:return: a :class:`_result.ScalarResult` object\n\n.. versionadded:: 1.4.24 Added :meth:`_orm.Session.scalars`\n\n.. versionadded:: 1.4.26 Added :meth:`_orm.scoped_session.scalars`\n\n.. seealso::\n\n :ref:`orm_queryguide_select_orm_entities` - contrasts the behavior\n of :meth:`_orm.Session.execute` to :meth:`_orm.Session.scalars`\n"}, "range": {"end": {"character": 28, "line": 18}, "start": {"character": 21, "line": 18}}}} -{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BitForImageClassification", "kind": 7, "label": "BitForImageClassification (import transformers)", "sortText": " 62"}, {"additionalTextEdits": [{"newText": ", BloomForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForSequenceClassification", "kind": 7, "label": "BloomForSequenceClassification (import transformers)", "sortText": " 63"}, {"additionalTextEdits": [{"newText": ", BloomForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForTokenClassification", "kind": 7, "label": "BloomForTokenClassification (import transformers)", "sortText": " 64"}, {"additionalTextEdits": [{"newText": ", BrosForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosForTokenClassification", "kind": 7, "label": "BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, 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{"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DynamicClassAttribute", "kind": 7, "label": "DynamicClassAttribute (import types)", "sortText": "119"}, {"additionalTextEdits": [{"newText": ", EfficientFormerForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientFormerForImageClassification", "kind": 7, "label": "EfficientFormerForImageClassification (import transformers)", "sortText": "120"}, {"additionalTextEdits": [{"newText": ", EfficientFormerForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientFormerForImageClassificationWithTeacher", "kind": 7, "label": "EfficientFormerForImageClassificationWithTeacher (import transformers)", "sortText": "121"}, {"additionalTextEdits": [{"newText": ", EfficientNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientNetForImageClassification", "kind": 7, "label": "EfficientNetForImageClassification (import transformers)", "sortText": "122"}, {"additionalTextEdits": [{"newText": ", ElectraForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ElectraForSequenceClassification", "kind": 7, "label": "ElectraForSequenceClassification (import transformers)", "sortText": "123"}, {"additionalTextEdits": [{"newText": ", ElectraForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ElectraForTokenClassification", "kind": 7, "label": "ElectraForTokenClassification (import transformers)", "sortText": "124"}, {"additionalTextEdits": [{"newText": ", ErnieForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForSequenceClassification", "kind": 7, "label": "ErnieForSequenceClassification (import transformers)", "sortText": "125"}, {"additionalTextEdits": [{"newText": ", ErnieForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForTokenClassification", "kind": 7, "label": "ErnieForTokenClassification (import transformers)", "sortText": "126"}, {"additionalTextEdits": [{"newText": ", ErnieMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForSequenceClassification", "kind": 7, "label": "ErnieMForSequenceClassification (import transformers)", "sortText": "127"}, {"additionalTextEdits": [{"newText": ", ErnieMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForTokenClassification", "kind": 7, "label": "ErnieMForTokenClassification (import 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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"kind": 21, "label": "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "137"}, {"additionalTextEdits": [{"newText": ", FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "138"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "139"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "140"}, {"additionalTextEdits": [{"newText": ", FNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForSequenceClassification", "kind": 7, "label": "FNetForSequenceClassification (import transformers)", "sortText": "141"}, {"additionalTextEdits": [{"newText": ", FNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForTokenClassification", "kind": 7, "label": "FNetForTokenClassification (import transformers)", "sortText": "142"}, {"additionalTextEdits": [{"newText": ", FalconForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForSequenceClassification", "kind": 7, "label": "FalconForSequenceClassification (import transformers)", "sortText": "143"}, {"additionalTextEdits": [{"newText": ", FalconForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForTokenClassification", "kind": 7, "label": "FalconForTokenClassification (import transformers)", "sortText": "144"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import FixMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FixMetaclass", "kind": 7, "label": "FixMetaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "145"}, {"additionalTextEdits": [{"newText": ", FlaubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForSequenceClassification", "kind": 7, "label": "FlaubertForSequenceClassification (import transformers)", "sortText": "146"}, {"additionalTextEdits": [{"newText": ", FlaubertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForTokenClassification", "kind": 7, "label": "FlaubertForTokenClassification (import transformers)", "sortText": "147"}, {"additionalTextEdits": [{"newText": ", FlaxAlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAlbertForSequenceClassification", "kind": 7, "label": "FlaxAlbertForSequenceClassification (import transformers)", "sortText": "148"}, {"additionalTextEdits": [{"newText": ", FlaxAlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAlbertForTokenClassification", "kind": 7, "label": "FlaxAlbertForTokenClassification (import transformers)", "sortText": "149"}, {"additionalTextEdits": [{"newText": ", 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"GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 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0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"sortText": "434"}, {"additionalTextEdits": [{"newText": "from transformers.models.starcoder2.modular_starcoder2 import Starcoder2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Starcoder2ForSequenceClassification", "kind": 7, "label": "Starcoder2ForSequenceClassification (import transformers.models.starcoder2.modular_starcoder2)", "sortText": "435"}, {"additionalTextEdits": [{"newText": ", Starcoder2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Starcoder2ForTokenClassification", "kind": 7, "label": "Starcoder2ForTokenClassification (import transformers)", "sortText": "436"}, {"additionalTextEdits": [{"newText": "from transformers.models.starcoder2.modular_starcoder2 import Starcoder2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "540"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "541"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "542"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKENIZER_CLASSES", "kind": 21, "label": "TOKENIZER_CLASSES (import transformers.convert_slow_tokenizers_checkpoints_to_fast)", "sortText": "546"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "547"}, {"additionalTextEdits": [{"newText": ", TapasForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TapasForSequenceClassification", "kind": 7, "label": "TapasForSequenceClassification (import transformers)", "sortText": "548"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": 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{"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": 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{"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 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"insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "601"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers)", "sortText": "602"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "603"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} -{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 2, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import 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"AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BitForImageClassification", "kind": 7, "label": "BitForImageClassification (import transformers)", "sortText": " 62"}, {"additionalTextEdits": [{"newText": ", BloomForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForSequenceClassification", "kind": 7, "label": "BloomForSequenceClassification (import transformers)", "sortText": " 63"}, {"additionalTextEdits": [{"newText": ", BloomForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForTokenClassification", "kind": 7, "label": "BloomForTokenClassification (import transformers)", "sortText": " 64"}, {"additionalTextEdits": [{"newText": ", BrosForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosForTokenClassification", "kind": 7, "label": "BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", 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{"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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"kind": 21, "label": "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "137"}, {"additionalTextEdits": [{"newText": ", FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "138"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "139"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "140"}, {"additionalTextEdits": [{"newText": ", FNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForSequenceClassification", "kind": 7, "label": "FNetForSequenceClassification (import transformers)", "sortText": "141"}, {"additionalTextEdits": [{"newText": ", FNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForTokenClassification", "kind": 7, "label": "FNetForTokenClassification (import transformers)", "sortText": "142"}, {"additionalTextEdits": [{"newText": ", FalconForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForSequenceClassification", "kind": 7, "label": "FalconForSequenceClassification (import transformers)", "sortText": "143"}, {"additionalTextEdits": [{"newText": ", FalconForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForTokenClassification", "kind": 7, "label": "FalconForTokenClassification (import transformers)", "sortText": "144"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import FixMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FixMetaclass", "kind": 7, "label": "FixMetaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "145"}, {"additionalTextEdits": [{"newText": ", FlaubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForSequenceClassification", "kind": 7, "label": "FlaubertForSequenceClassification (import transformers)", 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FlaxAutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForImageClassification", "kind": 7, "label": "FlaxAutoModelForImageClassification (import transformers)", "sortText": "150"}, {"additionalTextEdits": [{"newText": ", FlaxAutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForSequenceClassification", "kind": 7, "label": "FlaxAutoModelForSequenceClassification (import transformers)", "sortText": "151"}, {"additionalTextEdits": [{"newText": ", FlaxAutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForTokenClassification", "kind": 7, "label": "FlaxAutoModelForTokenClassification (import transformers)", "sortText": "152"}, {"additionalTextEdits": [{"newText": ", FlaxBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBartForSequenceClassification", "kind": 7, "label": "FlaxBartForSequenceClassification (import transformers)", "sortText": "153"}, {"additionalTextEdits": [{"newText": ", FlaxBeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBeitForImageClassification", "kind": 7, "label": "FlaxBeitForImageClassification (import transformers)", "sortText": "154"}, {"additionalTextEdits": [{"newText": ", FlaxBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBertForSequenceClassification", "kind": 7, "label": "FlaxBertForSequenceClassification (import transformers)", "sortText": "155"}, {"additionalTextEdits": [{"newText": ", FlaxBertForTokenClassification", "range": {"end": {"character": 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1}}}], "insertText": "FlaxDinov2ForImageClassification", "kind": 7, "label": "FlaxDinov2ForImageClassification (import transformers)", "sortText": "159"}, {"additionalTextEdits": [{"newText": ", FlaxDistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxDistilBertForSequenceClassification", "kind": 7, "label": "FlaxDistilBertForSequenceClassification (import transformers)", "sortText": "160"}, {"additionalTextEdits": [{"newText": ", FlaxDistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxDistilBertForTokenClassification", "kind": 7, "label": "FlaxDistilBertForTokenClassification (import transformers)", "sortText": "161"}, {"additionalTextEdits": [{"newText": ", FlaxElectraForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxElectraForSequenceClassification", "kind": 7, "label": "FlaxElectraForSequenceClassification (import transformers)", "sortText": "162"}, {"additionalTextEdits": [{"newText": ", FlaxElectraForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxElectraForTokenClassification", "kind": 7, "label": "FlaxElectraForTokenClassification (import transformers)", "sortText": "163"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flax_outputs import FlaxImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FlaxImageClassifierOutputWithNoAttention", "kind": 7, "label": "FlaxImageClassifierOutputWithNoAttention (import transformers.modeling_flax_outputs)", "sortText": "164"}, {"additionalTextEdits": [{"newText": ", FlaxMBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxMBartForSequenceClassification", "kind": 7, "label": "FlaxMBartForSequenceClassification (import transformers)", "sortText": "165"}, {"additionalTextEdits": [{"newText": ", FlaxRegNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRegNetForImageClassification", "kind": 7, "label": "FlaxRegNetForImageClassification (import transformers)", "sortText": "166"}, {"additionalTextEdits": [{"newText": ", FlaxResNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxResNetForImageClassification", "kind": 7, "label": "FlaxResNetForImageClassification (import transformers)", "sortText": "167"}, {"additionalTextEdits": [{"newText": ", FlaxRoFormerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRoFormerForSequenceClassification", "kind": 7, "label": "FlaxRoFormerForSequenceClassification (import transformers)", "sortText": "168"}, {"additionalTextEdits": [{"newText": ", FlaxRoFormerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRoFormerForTokenClassification", "kind": 7, "label": "FlaxRoFormerForTokenClassification (import transformers)", "sortText": "169"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaForSequenceClassification", "kind": 7, "label": "FlaxRobertaForSequenceClassification (import transformers)", "sortText": "170"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaForTokenClassification", "kind": 7, "label": "FlaxRobertaForTokenClassification (import transformers)", "sortText": "171"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaPreLayerNormForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaPreLayerNormForSequenceClassification", "kind": 7, "label": "FlaxRobertaPreLayerNormForSequenceClassification (import transformers)", "sortText": "172"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaPreLayerNormForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaPreLayerNormForTokenClassification", "kind": 7, "label": "FlaxRobertaPreLayerNormForTokenClassification (import transformers)", "sortText": "173"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flax_outputs import FlaxSeq2SeqSequenceClassifierOutput\n", "range": {"end": 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"line": 0}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "198"}, {"additionalTextEdits": [{"newText": ", Gemma2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers)", "sortText": "199"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "200"}, {"additionalTextEdits": [{"newText": ", Gemma3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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Gemma3TextForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "204"}, {"additionalTextEdits": [{"newText": ", GemmaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers)", "sortText": "205"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers.models.gemma.modular_gemma)", "sortText": "206"}, {"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import 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"GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForTokenClassification", "kind": 7, "label": "MegatronBertForTokenClassification (import transformers)", "sortText": "301"}, {"additionalTextEdits": [{"newText": "from transformers.models.metaclip_2 import MetaClip2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MetaClip2ForImageClassification", "kind": 7, "label": "MetaClip2ForImageClassification (import transformers.models.metaclip_2)", "sortText": "302"}, {"additionalTextEdits": [{"newText": "from transformers.models.metaclip_2.modular_metaclip_2 import MetaClip2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MetaClip2ForImageClassification", "kind": 7, "label": "MetaClip2ForImageClassification (import transformers.models.metaclip_2.modular_metaclip_2)", "sortText": "303"}, {"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers.models.ministral.modular_ministral)", "sortText": "309"}, {"additionalTextEdits": [{"newText": ", MinistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers)", "sortText": "310"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers.models.ministral.modular_ministral)", "sortText": "311"}, {"additionalTextEdits": [{"newText": ", MistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MistralForSequenceClassification", "kind": 7, "label": "MistralForSequenceClassification (import transformers)", "sortText": "312"}, {"additionalTextEdits": [{"newText": "from transformers.models.mistral.modular_mistral import MistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForSequenceClassification", "kind": 7, "label": "MistralForSequenceClassification (import transformers.models.mistral.modular_mistral)", "sortText": "313"}, {"additionalTextEdits": [{"newText": ", MistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers)", "sortText": "314"}, {"additionalTextEdits": [{"newText": "from transformers.models.mistral.modular_mistral import MistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers.models.mistral.modular_mistral)", "sortText": "315"}, {"additionalTextEdits": [{"newText": ", MixtralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers)", "sortText": "316"}, {"additionalTextEdits": [{"newText": "from transformers.models.mixtral.modular_mixtral import MixtralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers.models.mixtral.modular_mixtral)", "sortText": 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKENIZER_CLASSES", "kind": 21, "label": "TOKENIZER_CLASSES (import transformers.convert_slow_tokenizers_checkpoints_to_fast)", "sortText": "546"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "547"}, {"additionalTextEdits": [{"newText": ", TapasForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TapasForSequenceClassification", "kind": 7, "label": "TapasForSequenceClassification (import transformers)", "sortText": "548"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationParameters", "kind": 6, "label": "TextClassificationParameters (import huggingface_hub)", "sortText": "552"}, {"additionalTextEdits": [{"newText": ", TextClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextClassificationPipeline", "kind": 6, "label": "TextClassificationPipeline (import transformers)", "sortText": "553"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import TextClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationPipeline", "kind": 7, "label": "TextClassificationPipeline (import transformers.pipelines.text_classification)", "sortText": "554"}, {"additionalTextEdits": [{"newText": ", TextNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextNetForImageClassification", "kind": 7, "label": "TextNetForImageClassification (import transformers)", "sortText": "555"}, {"additionalTextEdits": [{"newText": ", TimesformerForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TimesformerForVideoClassification", "kind": 7, "label": "TimesformerForVideoClassification (import transformers)", "sortText": "556"}, {"additionalTextEdits": [{"newText": ", TimmWrapperForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TimmWrapperForImageClassification", "kind": 7, "label": "TimmWrapperForImageClassification (import transformers)", "sortText": "557"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationAggregationStrategy\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TvltForAudioVisualClassification", "kind": 7, "label": "TvltForAudioVisualClassification (import transformers)", "sortText": "567"}, {"additionalTextEdits": [{"newText": ", UMT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForSequenceClassification", "kind": 7, "label": "UMT5ForSequenceClassification (import transformers)", "sortText": "568"}, {"additionalTextEdits": [{"newText": ", UMT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForTokenClassification", "kind": 7, "label": "UMT5ForTokenClassification (import transformers)", "sortText": "569"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import UNROLL_KWARGS_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": 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{"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 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"insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import 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transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import 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transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} -{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 3, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, 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"BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge)", "sortText": "116"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge.modular_doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge.modular_doge)", "sortText": "117"}, {"additionalTextEdits": [{"newText": ", DonutSwinForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DonutSwinForImageClassification", "kind": 7, "label": "DonutSwinForImageClassification (import transformers)", "sortText": "118"}, {"additionalTextEdits": [{"newText": "from types import DynamicClassAttribute\n", "range": {"end": 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"insertText": "GPTBigCodeForTokenClassification", "kind": 7, "label": "GPTBigCodeForTokenClassification (import transformers)", "sortText": "189"}, {"additionalTextEdits": [{"newText": ", GPTJForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GPTJForSequenceClassification", "kind": 7, "label": "GPTJForSequenceClassification (import transformers)", "sortText": "190"}, {"additionalTextEdits": [{"newText": ", GPTNeoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GPTNeoForSequenceClassification", "kind": 7, "label": "GPTNeoForSequenceClassification (import transformers)", "sortText": "191"}, {"additionalTextEdits": [{"newText": ", GPTNeoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GPTNeoForTokenClassification", "kind": 7, "label": 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"kind": 7, "label": "GPTNeoXForTokenClassification (import transformers)", "sortText": "195"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_neox.modular_gpt_neox import GPTNeoXForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GPTNeoXForTokenClassification", "kind": 7, "label": "GPTNeoXForTokenClassification (import transformers.models.gpt_neox.modular_gpt_neox)", "sortText": "196"}, {"additionalTextEdits": [{"newText": ", Gemma2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers)", "sortText": "197"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "198"}, {"additionalTextEdits": [{"newText": ", Gemma2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers)", "sortText": "199"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "200"}, {"additionalTextEdits": [{"newText": ", Gemma3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma3ForSequenceClassification", "kind": 7, "label": "Gemma3ForSequenceClassification (import transformers)", "sortText": "201"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma3.modular_gemma3 import Gemma3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3ForSequenceClassification", "kind": 7, "label": "Gemma3ForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "202"}, {"additionalTextEdits": [{"newText": ", Gemma3TextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers)", "sortText": "203"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma3.modular_gemma3 import Gemma3TextForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "204"}, {"additionalTextEdits": [{"newText": ", GemmaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers)", "sortText": "205"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers.models.gemma.modular_gemma)", "sortText": "206"}, {"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import transformers.modeling_layers)", "sortText": "209"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForTokenClassification", "kind": 7, "label": "GenericForTokenClassification (import transformers.modeling_layers)", "sortText": "210"}, {"additionalTextEdits": [{"newText": ", Glm4ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Glm4ForSequenceClassification", "kind": 7, "label": "Glm4ForSequenceClassification (import transformers)", "sortText": "211"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm4.modular_glm4 import Glm4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Glm4ForSequenceClassification", "kind": 7, "label": "Glm4ForSequenceClassification (import transformers.models.glm4.modular_glm4)", "sortText": "212"}, {"additionalTextEdits": [{"newText": ", Glm4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers)", "sortText": "213"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm4.modular_glm4 import Glm4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers.models.glm4.modular_glm4)", "sortText": "214"}, {"additionalTextEdits": [{"newText": ", GlmForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", 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MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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{"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": 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"insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": 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{"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TvltForAudioVisualClassification", "kind": 7, "label": "TvltForAudioVisualClassification (import transformers)", "sortText": "567"}, {"additionalTextEdits": [{"newText": ", UMT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForSequenceClassification", "kind": 7, "label": "UMT5ForSequenceClassification (import transformers)", "sortText": "568"}, {"additionalTextEdits": [{"newText": ", UMT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForTokenClassification", "kind": 7, "label": "UMT5ForTokenClassification (import transformers)", "sortText": "569"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import UNROLL_KWARGS_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers.models.unispeech.modular_unispeech)", "sortText": "575"}, {"additionalTextEdits": [{"newText": ", UniSpeechSatForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechSatForAudioFrameClassification", "kind": 7, "label": "UniSpeechSatForAudioFrameClassification (import transformers)", "sortText": "576"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech_sat.modular_unispeech_sat import UniSpeechSatForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechSatForAudioFrameClassification", "kind": 7, "label": "UniSpeechSatForAudioFrameClassification (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "577"}, {"additionalTextEdits": [{"newText": ", UniSpeechSatForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers)", "sortText": "578"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech_sat.modular_unispeech_sat import UniSpeechSatForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "579"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import VIDEO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VIDEO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "VIDEO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "580"}, {"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTHybridForImageClassification", "kind": 7, "label": "ViTHybridForImageClassification (import transformers)", "sortText": "584"}, {"additionalTextEdits": [{"newText": ", ViTMSNForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTMSNForImageClassification", "kind": 7, "label": "ViTMSNForImageClassification (import transformers)", "sortText": "585"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationInput", "kind": 6, "label": "VideoClassificationInput (import huggingface_hub)", "sortText": "586"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForImagesAndTextClassification", "kind": 7, "label": "ViltForImagesAndTextClassification (import transformers)", "sortText": "593"}, {"additionalTextEdits": [{"newText": ", ViltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForTokenClassification", "kind": 7, "label": "ViltForTokenClassification (import transformers)", "sortText": "594"}, {"additionalTextEdits": [{"newText": ", VivitForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VivitForVideoClassification", "kind": 7, "label": "VivitForVideoClassification (import transformers)", "sortText": "595"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 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[{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} -{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 4, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, 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{"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": 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1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge)", "sortText": "116"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge.modular_doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge.modular_doge)", "sortText": "117"}, {"additionalTextEdits": [{"newText": ", DonutSwinForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DonutSwinForImageClassification", "kind": 7, "label": "DonutSwinForImageClassification (import transformers)", "sortText": "118"}, {"additionalTextEdits": [{"newText": "from types import DynamicClassAttribute\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DynamicClassAttribute", "kind": 7, "label": "DynamicClassAttribute (import types)", "sortText": "119"}, {"additionalTextEdits": [{"newText": ", EfficientFormerForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientFormerForImageClassification", "kind": 7, "label": "EfficientFormerForImageClassification (import transformers)", "sortText": "120"}, {"additionalTextEdits": [{"newText": ", EfficientFormerForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientFormerForImageClassificationWithTeacher", "kind": 7, "label": "EfficientFormerForImageClassificationWithTeacher (import transformers)", "sortText": "121"}, {"additionalTextEdits": [{"newText": ", EfficientNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientNetForImageClassification", "kind": 7, "label": "EfficientNetForImageClassification (import transformers)", "sortText": "122"}, {"additionalTextEdits": [{"newText": ", ElectraForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ElectraForSequenceClassification", "kind": 7, "label": "ElectraForSequenceClassification (import transformers)", "sortText": "123"}, {"additionalTextEdits": [{"newText": ", ElectraForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ElectraForTokenClassification", "kind": 7, "label": "ElectraForTokenClassification (import transformers)", "sortText": "124"}, {"additionalTextEdits": [{"newText": ", ErnieForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForSequenceClassification", "kind": 7, "label": "ErnieForSequenceClassification (import transformers)", "sortText": "125"}, {"additionalTextEdits": [{"newText": ", ErnieForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForTokenClassification", "kind": 7, "label": "ErnieForTokenClassification (import transformers)", "sortText": "126"}, {"additionalTextEdits": [{"newText": ", ErnieMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForSequenceClassification", "kind": 7, "label": "ErnieMForSequenceClassification (import transformers)", "sortText": "127"}, {"additionalTextEdits": [{"newText": ", ErnieMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForTokenClassification", "kind": 7, "label": "ErnieMForTokenClassification (import 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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{"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import 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"Glm4ForSequenceClassification (import transformers.models.glm4.modular_glm4)", "sortText": "212"}, {"additionalTextEdits": [{"newText": ", Glm4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers)", "sortText": "213"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm4.modular_glm4 import Glm4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers.models.glm4.modular_glm4)", "sortText": "214"}, {"additionalTextEdits": [{"newText": ", GlmForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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{"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers.models.ministral.modular_ministral)", "sortText": "309"}, {"additionalTextEdits": [{"newText": ", MinistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers)", "sortText": "310"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers.models.ministral.modular_ministral)", "sortText": "311"}, {"additionalTextEdits": [{"newText": ", MistralForSequenceClassification", "range": {"end": {"character": 33, 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MistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers.models.mistral.modular_mistral)", "sortText": "315"}, {"additionalTextEdits": [{"newText": ", MixtralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers)", "sortText": "316"}, {"additionalTextEdits": [{"newText": "from transformers.models.mixtral.modular_mixtral import MixtralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers.models.mixtral.modular_mixtral)", "sortText": 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", MobileViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MobileViTForImageClassification", "kind": 7, "label": "MobileViTForImageClassification (import transformers)", "sortText": "324"}, {"additionalTextEdits": [{"newText": ", MobileViTV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MobileViTV2ForImageClassification", "kind": 7, "label": "MobileViTV2ForImageClassification (import transformers)", "sortText": "325"}, {"additionalTextEdits": [{"newText": ", ModernBertDecoderForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ModernBertDecoderForSequenceClassification", "kind": 7, "label": "ModernBertDecoderForSequenceClassification (import transformers)", "sortText": "326"}, {"additionalTextEdits": [{"newText": "from transformers.models.modernbert_decoder.modular_modernbert_decoder import ModernBertDecoderForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ModernBertDecoderForSequenceClassification", "kind": 7, "label": "ModernBertDecoderForSequenceClassification (import transformers.models.modernbert_decoder.modular_modernbert_decoder)", "sortText": "327"}, {"additionalTextEdits": [{"newText": ", ModernBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ModernBertForSequenceClassification", "kind": 7, "label": "ModernBertForSequenceClassification (import transformers)", "sortText": "328"}, {"additionalTextEdits": [{"newText": "from transformers.models.modernbert.modular_modernbert import ModernBertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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[{"newText": ", NemotronForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NemotronForSequenceClassification", "kind": 7, "label": "NemotronForSequenceClassification (import transformers)", "sortText": "339"}, {"additionalTextEdits": [{"newText": ", NemotronForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NemotronForTokenClassification", "kind": 7, "label": "NemotronForTokenClassification (import transformers)", "sortText": "340"}, {"additionalTextEdits": [{"newText": ", NezhaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NezhaForSequenceClassification", "kind": 7, "label": "NezhaForSequenceClassification (import transformers)", "sortText": "341"}, {"additionalTextEdits": [{"newText": ", NezhaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NezhaForTokenClassification", "kind": 7, "label": "NezhaForTokenClassification (import transformers)", "sortText": "342"}, {"additionalTextEdits": [{"newText": ", NystromformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NystromformerForSequenceClassification", "kind": 7, "label": "NystromformerForSequenceClassification (import transformers)", "sortText": "343"}, {"additionalTextEdits": [{"newText": ", NystromformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NystromformerForTokenClassification", "kind": 7, "label": "NystromformerForTokenClassification (import transformers)", "sortText": "344"}, {"additionalTextEdits": [{"newText": ", OPTForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "OPTForSequenceClassification", "kind": 7, "label": "OPTForSequenceClassification (import transformers)", "sortText": "345"}, {"additionalTextEdits": [{"newText": ", OpenAIGPTForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "OpenAIGPTForSequenceClassification", "kind": 7, "label": "OpenAIGPTForSequenceClassification (import transformers)", "sortText": "346"}, {"additionalTextEdits": [{"newText": ", OpenLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "OpenLlamaForSequenceClassification", "kind": 7, "label": "OpenLlamaForSequenceClassification (import transformers)", "sortText": "347"}, {"additionalTextEdits": [{"newText": ", PLBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PLBartForSequenceClassification", "kind": 7, "label": "PLBartForSequenceClassification (import transformers)", "sortText": "348"}, {"additionalTextEdits": [{"newText": "from transformers.models.plbart.modular_plbart import PLBartForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PLBartForSequenceClassification", "kind": 7, "label": "PLBartForSequenceClassification (import transformers.models.plbart.modular_plbart)", "sortText": "349"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "PT_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "350"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_SPEECH_FRAME_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_SPEECH_FRAME_CLASS_SAMPLE", "kind": 21, "label": "PT_SPEECH_FRAME_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "351"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_SPEECH_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_SPEECH_SEQ_CLASS_SAMPLE", "kind": 21, "label": "PT_SPEECH_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "352"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "PT_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "353"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "540"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "541"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "542"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": 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{"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationParameters", "kind": 6, "label": "TextClassificationParameters (import huggingface_hub)", "sortText": "552"}, {"additionalTextEdits": [{"newText": ", TextClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextClassificationPipeline", "kind": 6, "label": "TextClassificationPipeline (import transformers)", "sortText": "553"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import TextClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationPipeline", "kind": 7, "label": "TextClassificationPipeline (import transformers.pipelines.text_classification)", "sortText": "554"}, {"additionalTextEdits": [{"newText": ", TextNetForImageClassification", "range": {"end": {"character": 33, "line": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": 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33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers)", "sortText": "578"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech_sat.modular_unispeech_sat import UniSpeechSatForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "579"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import VIDEO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VIDEO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "VIDEO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "580"}, {"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTHybridForImageClassification", "kind": 7, "label": "ViTHybridForImageClassification (import transformers)", "sortText": "584"}, {"additionalTextEdits": [{"newText": ", ViTMSNForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTMSNForImageClassification", "kind": 7, "label": "ViTMSNForImageClassification (import transformers)", "sortText": "585"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationInput", "kind": 6, "label": "VideoClassificationInput (import huggingface_hub)", "sortText": "586"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForImagesAndTextClassification", "kind": 7, "label": "ViltForImagesAndTextClassification (import transformers)", "sortText": "593"}, {"additionalTextEdits": [{"newText": ", ViltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForTokenClassification", "kind": 7, "label": "ViltForTokenClassification (import transformers)", "sortText": "594"}, {"additionalTextEdits": [{"newText": ", VivitForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VivitForVideoClassification", "kind": 7, "label": "VivitForVideoClassification (import transformers)", "sortText": "595"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "601"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers)", "sortText": "602"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "603"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": 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"sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} -{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 5, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BitForImageClassification", "kind": 7, "label": "BitForImageClassification (import transformers)", "sortText": " 62"}, {"additionalTextEdits": [{"newText": ", BloomForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForSequenceClassification", "kind": 7, "label": "BloomForSequenceClassification (import transformers)", "sortText": " 63"}, {"additionalTextEdits": [{"newText": ", BloomForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForTokenClassification", "kind": 7, "label": "BloomForTokenClassification (import transformers)", "sortText": " 64"}, {"additionalTextEdits": [{"newText": ", BrosForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosForTokenClassification", "kind": 7, "label": "BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, 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"ErnieForSequenceClassification", "kind": 7, "label": "ErnieForSequenceClassification (import transformers)", "sortText": "125"}, {"additionalTextEdits": [{"newText": ", ErnieForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForTokenClassification", "kind": 7, "label": "ErnieForTokenClassification (import transformers)", "sortText": "126"}, {"additionalTextEdits": [{"newText": ", ErnieMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForSequenceClassification", "kind": 7, "label": "ErnieMForSequenceClassification (import transformers)", "sortText": "127"}, {"additionalTextEdits": [{"newText": ", ErnieMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForTokenClassification", "kind": 7, "label": "ErnieMForTokenClassification (import 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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"kind": 21, "label": "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "137"}, {"additionalTextEdits": [{"newText": ", FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "138"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "139"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "140"}, {"additionalTextEdits": [{"newText": ", FNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForSequenceClassification", "kind": 7, "label": "FNetForSequenceClassification (import transformers)", "sortText": "141"}, {"additionalTextEdits": [{"newText": ", FNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForTokenClassification", "kind": 7, "label": "FNetForTokenClassification (import transformers)", "sortText": "142"}, {"additionalTextEdits": [{"newText": ", FalconForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForSequenceClassification", "kind": 7, "label": "FalconForSequenceClassification (import transformers)", "sortText": "143"}, {"additionalTextEdits": [{"newText": ", FalconForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForTokenClassification", "kind": 7, "label": "FalconForTokenClassification (import transformers)", "sortText": "144"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import FixMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FixMetaclass", "kind": 7, "label": "FixMetaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "145"}, {"additionalTextEdits": [{"newText": ", FlaubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForSequenceClassification", "kind": 7, "label": "FlaubertForSequenceClassification (import transformers)", 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"GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 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0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"sortText": "434"}, {"additionalTextEdits": [{"newText": "from transformers.models.starcoder2.modular_starcoder2 import Starcoder2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Starcoder2ForSequenceClassification", "kind": 7, "label": "Starcoder2ForSequenceClassification (import transformers.models.starcoder2.modular_starcoder2)", "sortText": "435"}, {"additionalTextEdits": [{"newText": ", Starcoder2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Starcoder2ForTokenClassification", "kind": 7, "label": "Starcoder2ForTokenClassification (import transformers)", "sortText": "436"}, {"additionalTextEdits": [{"newText": "from transformers.models.starcoder2.modular_starcoder2 import Starcoder2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "540"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "541"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "542"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKENIZER_CLASSES", "kind": 21, "label": "TOKENIZER_CLASSES (import transformers.convert_slow_tokenizers_checkpoints_to_fast)", "sortText": "546"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "547"}, {"additionalTextEdits": [{"newText": ", TapasForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TapasForSequenceClassification", "kind": 7, "label": "TapasForSequenceClassification (import transformers)", "sortText": "548"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": 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{"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": 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{"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 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"insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "601"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers)", "sortText": "602"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "603"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} +{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import 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"AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BitForImageClassification", "kind": 7, "label": "BitForImageClassification (import transformers)", "sortText": " 62"}, {"additionalTextEdits": [{"newText": ", BloomForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForSequenceClassification", "kind": 7, "label": "BloomForSequenceClassification (import transformers)", "sortText": " 63"}, {"additionalTextEdits": [{"newText": ", BloomForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForTokenClassification", "kind": 7, "label": "BloomForTokenClassification (import transformers)", "sortText": " 64"}, {"additionalTextEdits": [{"newText": ", BrosForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosForTokenClassification", "kind": 7, "label": "BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", 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{"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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"kind": 21, "label": "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "137"}, {"additionalTextEdits": [{"newText": ", FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "138"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "139"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "140"}, {"additionalTextEdits": [{"newText": ", FNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForSequenceClassification", "kind": 7, "label": "FNetForSequenceClassification (import transformers)", "sortText": "141"}, {"additionalTextEdits": [{"newText": ", FNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForTokenClassification", "kind": 7, "label": "FNetForTokenClassification (import transformers)", "sortText": "142"}, {"additionalTextEdits": [{"newText": ", FalconForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForSequenceClassification", "kind": 7, "label": "FalconForSequenceClassification (import transformers)", "sortText": "143"}, {"additionalTextEdits": [{"newText": ", FalconForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForTokenClassification", "kind": 7, "label": "FalconForTokenClassification (import transformers)", "sortText": "144"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import FixMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FixMetaclass", "kind": 7, "label": "FixMetaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "145"}, {"additionalTextEdits": [{"newText": ", FlaubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForSequenceClassification", "kind": 7, "label": "FlaubertForSequenceClassification (import transformers)", 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FlaxAutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForImageClassification", "kind": 7, "label": "FlaxAutoModelForImageClassification (import transformers)", "sortText": "150"}, {"additionalTextEdits": [{"newText": ", FlaxAutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForSequenceClassification", "kind": 7, "label": "FlaxAutoModelForSequenceClassification (import transformers)", "sortText": "151"}, {"additionalTextEdits": [{"newText": ", FlaxAutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForTokenClassification", "kind": 7, "label": "FlaxAutoModelForTokenClassification (import transformers)", "sortText": "152"}, {"additionalTextEdits": [{"newText": ", FlaxBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBartForSequenceClassification", "kind": 7, "label": "FlaxBartForSequenceClassification (import transformers)", "sortText": "153"}, {"additionalTextEdits": [{"newText": ", FlaxBeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBeitForImageClassification", "kind": 7, "label": "FlaxBeitForImageClassification (import transformers)", "sortText": "154"}, {"additionalTextEdits": [{"newText": ", FlaxBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBertForSequenceClassification", "kind": 7, "label": "FlaxBertForSequenceClassification (import transformers)", "sortText": "155"}, {"additionalTextEdits": [{"newText": ", FlaxBertForTokenClassification", "range": {"end": {"character": 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1}}}], "insertText": "FlaxDinov2ForImageClassification", "kind": 7, "label": "FlaxDinov2ForImageClassification (import transformers)", "sortText": "159"}, {"additionalTextEdits": [{"newText": ", FlaxDistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxDistilBertForSequenceClassification", "kind": 7, "label": "FlaxDistilBertForSequenceClassification (import transformers)", "sortText": "160"}, {"additionalTextEdits": [{"newText": ", FlaxDistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxDistilBertForTokenClassification", "kind": 7, "label": "FlaxDistilBertForTokenClassification (import transformers)", "sortText": "161"}, {"additionalTextEdits": [{"newText": ", FlaxElectraForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxElectraForSequenceClassification", "kind": 7, "label": "FlaxElectraForSequenceClassification (import transformers)", "sortText": "162"}, {"additionalTextEdits": [{"newText": ", FlaxElectraForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxElectraForTokenClassification", "kind": 7, "label": "FlaxElectraForTokenClassification (import transformers)", "sortText": "163"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flax_outputs import FlaxImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FlaxImageClassifierOutputWithNoAttention", "kind": 7, "label": "FlaxImageClassifierOutputWithNoAttention (import transformers.modeling_flax_outputs)", "sortText": "164"}, {"additionalTextEdits": [{"newText": ", FlaxMBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxMBartForSequenceClassification", "kind": 7, "label": "FlaxMBartForSequenceClassification (import transformers)", "sortText": "165"}, {"additionalTextEdits": [{"newText": ", FlaxRegNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRegNetForImageClassification", "kind": 7, "label": "FlaxRegNetForImageClassification (import transformers)", "sortText": "166"}, {"additionalTextEdits": [{"newText": ", FlaxResNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxResNetForImageClassification", "kind": 7, "label": "FlaxResNetForImageClassification (import transformers)", "sortText": "167"}, {"additionalTextEdits": [{"newText": ", FlaxRoFormerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRoFormerForSequenceClassification", "kind": 7, "label": "FlaxRoFormerForSequenceClassification (import transformers)", "sortText": "168"}, {"additionalTextEdits": [{"newText": ", FlaxRoFormerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRoFormerForTokenClassification", "kind": 7, "label": "FlaxRoFormerForTokenClassification (import transformers)", "sortText": "169"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaForSequenceClassification", "kind": 7, "label": "FlaxRobertaForSequenceClassification (import transformers)", "sortText": "170"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaForTokenClassification", "kind": 7, "label": "FlaxRobertaForTokenClassification (import transformers)", "sortText": "171"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaPreLayerNormForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaPreLayerNormForSequenceClassification", "kind": 7, "label": "FlaxRobertaPreLayerNormForSequenceClassification (import transformers)", "sortText": "172"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaPreLayerNormForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaPreLayerNormForTokenClassification", "kind": 7, "label": "FlaxRobertaPreLayerNormForTokenClassification (import transformers)", "sortText": "173"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flax_outputs import FlaxSeq2SeqSequenceClassifierOutput\n", "range": {"end": 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"line": 0}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "198"}, {"additionalTextEdits": [{"newText": ", Gemma2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers)", "sortText": "199"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "200"}, {"additionalTextEdits": [{"newText": ", Gemma3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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Gemma3TextForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "204"}, {"additionalTextEdits": [{"newText": ", GemmaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers)", "sortText": "205"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers.models.gemma.modular_gemma)", "sortText": "206"}, {"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import 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"GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForTokenClassification", "kind": 7, "label": "MegatronBertForTokenClassification (import transformers)", "sortText": "301"}, {"additionalTextEdits": [{"newText": "from transformers.models.metaclip_2 import MetaClip2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MetaClip2ForImageClassification", "kind": 7, "label": "MetaClip2ForImageClassification (import transformers.models.metaclip_2)", "sortText": "302"}, {"additionalTextEdits": [{"newText": "from transformers.models.metaclip_2.modular_metaclip_2 import MetaClip2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MetaClip2ForImageClassification", "kind": 7, "label": "MetaClip2ForImageClassification (import transformers.models.metaclip_2.modular_metaclip_2)", "sortText": "303"}, {"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers.models.ministral.modular_ministral)", "sortText": "309"}, {"additionalTextEdits": [{"newText": ", MinistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers)", "sortText": "310"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers.models.ministral.modular_ministral)", "sortText": "311"}, {"additionalTextEdits": [{"newText": ", MistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MistralForSequenceClassification", "kind": 7, "label": "MistralForSequenceClassification (import transformers)", "sortText": "312"}, {"additionalTextEdits": [{"newText": "from transformers.models.mistral.modular_mistral import MistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForSequenceClassification", "kind": 7, "label": "MistralForSequenceClassification (import transformers.models.mistral.modular_mistral)", "sortText": "313"}, {"additionalTextEdits": [{"newText": ", MistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers)", "sortText": "314"}, {"additionalTextEdits": [{"newText": "from transformers.models.mistral.modular_mistral import MistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers.models.mistral.modular_mistral)", "sortText": "315"}, {"additionalTextEdits": [{"newText": ", MixtralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers)", "sortText": "316"}, {"additionalTextEdits": [{"newText": "from transformers.models.mixtral.modular_mixtral import MixtralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers.models.mixtral.modular_mixtral)", "sortText": 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKENIZER_CLASSES", "kind": 21, "label": "TOKENIZER_CLASSES (import transformers.convert_slow_tokenizers_checkpoints_to_fast)", "sortText": "546"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "547"}, {"additionalTextEdits": [{"newText": ", TapasForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TapasForSequenceClassification", "kind": 7, "label": "TapasForSequenceClassification (import transformers)", "sortText": "548"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationParameters", "kind": 6, "label": "TextClassificationParameters (import huggingface_hub)", "sortText": "552"}, {"additionalTextEdits": [{"newText": ", TextClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextClassificationPipeline", "kind": 6, "label": "TextClassificationPipeline (import transformers)", "sortText": "553"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import TextClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationPipeline", "kind": 7, "label": "TextClassificationPipeline (import transformers.pipelines.text_classification)", "sortText": "554"}, {"additionalTextEdits": [{"newText": ", TextNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextNetForImageClassification", "kind": 7, "label": "TextNetForImageClassification (import transformers)", "sortText": "555"}, {"additionalTextEdits": [{"newText": ", TimesformerForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TimesformerForVideoClassification", "kind": 7, "label": "TimesformerForVideoClassification (import transformers)", "sortText": "556"}, {"additionalTextEdits": [{"newText": ", TimmWrapperForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TimmWrapperForImageClassification", "kind": 7, "label": "TimmWrapperForImageClassification (import transformers)", "sortText": "557"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationAggregationStrategy\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TvltForAudioVisualClassification", "kind": 7, "label": "TvltForAudioVisualClassification (import transformers)", "sortText": "567"}, {"additionalTextEdits": [{"newText": ", UMT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForSequenceClassification", "kind": 7, "label": "UMT5ForSequenceClassification (import transformers)", "sortText": "568"}, {"additionalTextEdits": [{"newText": ", UMT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForTokenClassification", "kind": 7, "label": "UMT5ForTokenClassification (import transformers)", "sortText": "569"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import UNROLL_KWARGS_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": 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{"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 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"insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import 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transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import 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transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} +{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 2, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, 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"BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge)", "sortText": "116"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge.modular_doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge.modular_doge)", "sortText": "117"}, {"additionalTextEdits": [{"newText": ", DonutSwinForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DonutSwinForImageClassification", "kind": 7, "label": "DonutSwinForImageClassification (import transformers)", "sortText": "118"}, {"additionalTextEdits": [{"newText": "from types import DynamicClassAttribute\n", "range": {"end": 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"insertText": "GPTBigCodeForTokenClassification", "kind": 7, "label": "GPTBigCodeForTokenClassification (import transformers)", "sortText": "189"}, {"additionalTextEdits": [{"newText": ", GPTJForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GPTJForSequenceClassification", "kind": 7, "label": "GPTJForSequenceClassification (import transformers)", "sortText": "190"}, {"additionalTextEdits": [{"newText": ", GPTNeoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GPTNeoForSequenceClassification", "kind": 7, "label": "GPTNeoForSequenceClassification (import transformers)", "sortText": "191"}, {"additionalTextEdits": [{"newText": ", GPTNeoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GPTNeoForTokenClassification", "kind": 7, "label": 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"kind": 7, "label": "GPTNeoXForTokenClassification (import transformers)", "sortText": "195"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_neox.modular_gpt_neox import GPTNeoXForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GPTNeoXForTokenClassification", "kind": 7, "label": "GPTNeoXForTokenClassification (import transformers.models.gpt_neox.modular_gpt_neox)", "sortText": "196"}, {"additionalTextEdits": [{"newText": ", Gemma2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers)", "sortText": "197"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "198"}, {"additionalTextEdits": [{"newText": ", Gemma2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers)", "sortText": "199"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "200"}, {"additionalTextEdits": [{"newText": ", Gemma3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma3ForSequenceClassification", "kind": 7, "label": "Gemma3ForSequenceClassification (import transformers)", "sortText": "201"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma3.modular_gemma3 import Gemma3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3ForSequenceClassification", "kind": 7, "label": "Gemma3ForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "202"}, {"additionalTextEdits": [{"newText": ", Gemma3TextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers)", "sortText": "203"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma3.modular_gemma3 import Gemma3TextForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "204"}, {"additionalTextEdits": [{"newText": ", GemmaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers)", "sortText": "205"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers.models.gemma.modular_gemma)", "sortText": "206"}, {"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import transformers.modeling_layers)", "sortText": "209"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForTokenClassification", "kind": 7, "label": "GenericForTokenClassification (import transformers.modeling_layers)", "sortText": "210"}, {"additionalTextEdits": [{"newText": ", Glm4ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Glm4ForSequenceClassification", "kind": 7, "label": "Glm4ForSequenceClassification (import transformers)", "sortText": "211"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm4.modular_glm4 import Glm4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Glm4ForSequenceClassification", "kind": 7, "label": "Glm4ForSequenceClassification (import transformers.models.glm4.modular_glm4)", "sortText": "212"}, {"additionalTextEdits": [{"newText": ", Glm4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers)", "sortText": "213"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm4.modular_glm4 import Glm4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers.models.glm4.modular_glm4)", "sortText": "214"}, {"additionalTextEdits": [{"newText": ", GlmForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", 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MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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{"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": 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"insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": 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{"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TvltForAudioVisualClassification", "kind": 7, "label": "TvltForAudioVisualClassification (import transformers)", "sortText": "567"}, {"additionalTextEdits": [{"newText": ", UMT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForSequenceClassification", "kind": 7, "label": "UMT5ForSequenceClassification (import transformers)", "sortText": "568"}, {"additionalTextEdits": [{"newText": ", UMT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForTokenClassification", "kind": 7, "label": "UMT5ForTokenClassification (import transformers)", "sortText": "569"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import UNROLL_KWARGS_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers.models.unispeech.modular_unispeech)", "sortText": "575"}, {"additionalTextEdits": [{"newText": ", UniSpeechSatForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechSatForAudioFrameClassification", "kind": 7, "label": "UniSpeechSatForAudioFrameClassification (import transformers)", "sortText": "576"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech_sat.modular_unispeech_sat import UniSpeechSatForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechSatForAudioFrameClassification", "kind": 7, "label": "UniSpeechSatForAudioFrameClassification (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "577"}, {"additionalTextEdits": [{"newText": ", UniSpeechSatForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers)", "sortText": "578"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech_sat.modular_unispeech_sat import UniSpeechSatForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "579"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import VIDEO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VIDEO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "VIDEO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "580"}, {"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTHybridForImageClassification", "kind": 7, "label": "ViTHybridForImageClassification (import transformers)", "sortText": "584"}, {"additionalTextEdits": [{"newText": ", ViTMSNForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTMSNForImageClassification", "kind": 7, "label": "ViTMSNForImageClassification (import transformers)", "sortText": "585"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationInput", "kind": 6, "label": "VideoClassificationInput (import huggingface_hub)", "sortText": "586"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForImagesAndTextClassification", "kind": 7, "label": "ViltForImagesAndTextClassification (import transformers)", "sortText": "593"}, {"additionalTextEdits": [{"newText": ", ViltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForTokenClassification", "kind": 7, "label": "ViltForTokenClassification (import transformers)", "sortText": "594"}, {"additionalTextEdits": [{"newText": ", VivitForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VivitForVideoClassification", "kind": 7, "label": "VivitForVideoClassification (import transformers)", "sortText": "595"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 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[{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} +{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 3, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, 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{"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": 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1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge)", "sortText": "116"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge.modular_doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DogeForSequenceClassification", "kind": 7, "label": "DogeForSequenceClassification (import transformers.models.doge.modular_doge)", "sortText": "117"}, {"additionalTextEdits": [{"newText": ", DonutSwinForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DonutSwinForImageClassification", "kind": 7, "label": "DonutSwinForImageClassification (import transformers)", "sortText": "118"}, {"additionalTextEdits": [{"newText": "from types import DynamicClassAttribute\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DynamicClassAttribute", "kind": 7, "label": "DynamicClassAttribute (import types)", "sortText": "119"}, {"additionalTextEdits": [{"newText": ", EfficientFormerForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientFormerForImageClassification", "kind": 7, "label": "EfficientFormerForImageClassification (import transformers)", "sortText": "120"}, {"additionalTextEdits": [{"newText": ", EfficientFormerForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientFormerForImageClassificationWithTeacher", "kind": 7, "label": "EfficientFormerForImageClassificationWithTeacher (import transformers)", "sortText": "121"}, {"additionalTextEdits": [{"newText": ", EfficientNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientNetForImageClassification", "kind": 7, "label": "EfficientNetForImageClassification (import transformers)", "sortText": "122"}, {"additionalTextEdits": [{"newText": ", ElectraForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ElectraForSequenceClassification", "kind": 7, "label": "ElectraForSequenceClassification (import transformers)", "sortText": "123"}, {"additionalTextEdits": [{"newText": ", ElectraForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ElectraForTokenClassification", "kind": 7, "label": "ElectraForTokenClassification (import transformers)", "sortText": "124"}, {"additionalTextEdits": [{"newText": ", ErnieForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForSequenceClassification", "kind": 7, "label": "ErnieForSequenceClassification (import transformers)", "sortText": "125"}, {"additionalTextEdits": [{"newText": ", ErnieForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForTokenClassification", "kind": 7, "label": "ErnieForTokenClassification (import transformers)", "sortText": "126"}, {"additionalTextEdits": [{"newText": ", ErnieMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForSequenceClassification", "kind": 7, "label": "ErnieMForSequenceClassification (import transformers)", "sortText": "127"}, {"additionalTextEdits": [{"newText": ", ErnieMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForTokenClassification", "kind": 7, "label": "ErnieMForTokenClassification (import 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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{"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import 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"Glm4ForSequenceClassification (import transformers.models.glm4.modular_glm4)", "sortText": "212"}, {"additionalTextEdits": [{"newText": ", Glm4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers)", "sortText": "213"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm4.modular_glm4 import Glm4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Glm4ForTokenClassification", "kind": 7, "label": "Glm4ForTokenClassification (import transformers.models.glm4.modular_glm4)", "sortText": "214"}, {"additionalTextEdits": [{"newText": ", GlmForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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{"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers.models.ministral.modular_ministral)", "sortText": "309"}, {"additionalTextEdits": [{"newText": ", MinistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers)", "sortText": "310"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers.models.ministral.modular_ministral)", "sortText": "311"}, {"additionalTextEdits": [{"newText": ", MistralForSequenceClassification", "range": {"end": {"character": 33, 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MistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers.models.mistral.modular_mistral)", "sortText": "315"}, {"additionalTextEdits": [{"newText": ", MixtralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers)", "sortText": "316"}, {"additionalTextEdits": [{"newText": "from transformers.models.mixtral.modular_mixtral import MixtralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers.models.mixtral.modular_mixtral)", "sortText": 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", MobileViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MobileViTForImageClassification", "kind": 7, "label": "MobileViTForImageClassification (import transformers)", "sortText": "324"}, {"additionalTextEdits": [{"newText": ", MobileViTV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MobileViTV2ForImageClassification", "kind": 7, "label": "MobileViTV2ForImageClassification (import transformers)", "sortText": "325"}, {"additionalTextEdits": [{"newText": ", ModernBertDecoderForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ModernBertDecoderForSequenceClassification", "kind": 7, "label": "ModernBertDecoderForSequenceClassification (import transformers)", "sortText": "326"}, {"additionalTextEdits": [{"newText": "from transformers.models.modernbert_decoder.modular_modernbert_decoder import ModernBertDecoderForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ModernBertDecoderForSequenceClassification", "kind": 7, "label": "ModernBertDecoderForSequenceClassification (import transformers.models.modernbert_decoder.modular_modernbert_decoder)", "sortText": "327"}, {"additionalTextEdits": [{"newText": ", ModernBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ModernBertForSequenceClassification", "kind": 7, "label": "ModernBertForSequenceClassification (import transformers)", "sortText": "328"}, {"additionalTextEdits": [{"newText": "from transformers.models.modernbert.modular_modernbert import ModernBertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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[{"newText": ", NemotronForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NemotronForSequenceClassification", "kind": 7, "label": "NemotronForSequenceClassification (import transformers)", "sortText": "339"}, {"additionalTextEdits": [{"newText": ", NemotronForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NemotronForTokenClassification", "kind": 7, "label": "NemotronForTokenClassification (import transformers)", "sortText": "340"}, {"additionalTextEdits": [{"newText": ", NezhaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NezhaForSequenceClassification", "kind": 7, "label": "NezhaForSequenceClassification (import transformers)", "sortText": "341"}, {"additionalTextEdits": [{"newText": ", NezhaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NezhaForTokenClassification", "kind": 7, "label": "NezhaForTokenClassification (import transformers)", "sortText": "342"}, {"additionalTextEdits": [{"newText": ", NystromformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NystromformerForSequenceClassification", "kind": 7, "label": "NystromformerForSequenceClassification (import transformers)", "sortText": "343"}, {"additionalTextEdits": [{"newText": ", NystromformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "NystromformerForTokenClassification", "kind": 7, "label": "NystromformerForTokenClassification (import transformers)", "sortText": "344"}, {"additionalTextEdits": [{"newText": ", OPTForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "OPTForSequenceClassification", "kind": 7, "label": "OPTForSequenceClassification (import transformers)", "sortText": "345"}, {"additionalTextEdits": [{"newText": ", OpenAIGPTForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "OpenAIGPTForSequenceClassification", "kind": 7, "label": "OpenAIGPTForSequenceClassification (import transformers)", "sortText": "346"}, {"additionalTextEdits": [{"newText": ", OpenLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "OpenLlamaForSequenceClassification", "kind": 7, "label": "OpenLlamaForSequenceClassification (import transformers)", "sortText": "347"}, {"additionalTextEdits": [{"newText": ", PLBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PLBartForSequenceClassification", "kind": 7, "label": "PLBartForSequenceClassification (import transformers)", "sortText": "348"}, {"additionalTextEdits": [{"newText": "from transformers.models.plbart.modular_plbart import PLBartForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PLBartForSequenceClassification", "kind": 7, "label": "PLBartForSequenceClassification (import transformers.models.plbart.modular_plbart)", "sortText": "349"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "PT_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "350"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_SPEECH_FRAME_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_SPEECH_FRAME_CLASS_SAMPLE", "kind": 21, "label": "PT_SPEECH_FRAME_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "351"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_SPEECH_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_SPEECH_SEQ_CLASS_SAMPLE", "kind": 21, "label": "PT_SPEECH_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "352"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import PT_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "PT_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "PT_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "353"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "540"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "541"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "542"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": 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{"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationParameters", "kind": 6, "label": "TextClassificationParameters (import huggingface_hub)", "sortText": "552"}, {"additionalTextEdits": [{"newText": ", TextClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextClassificationPipeline", "kind": 6, "label": "TextClassificationPipeline (import transformers)", "sortText": "553"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import TextClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationPipeline", "kind": 7, "label": "TextClassificationPipeline (import transformers.pipelines.text_classification)", "sortText": "554"}, {"additionalTextEdits": [{"newText": ", TextNetForImageClassification", "range": {"end": {"character": 33, "line": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": 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33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers)", "sortText": "578"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech_sat.modular_unispeech_sat import UniSpeechSatForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechSatForSequenceClassification", "kind": 7, "label": "UniSpeechSatForSequenceClassification (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "579"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import VIDEO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VIDEO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "VIDEO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "580"}, {"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTHybridForImageClassification", "kind": 7, "label": "ViTHybridForImageClassification (import transformers)", "sortText": "584"}, {"additionalTextEdits": [{"newText": ", ViTMSNForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTMSNForImageClassification", "kind": 7, "label": "ViTMSNForImageClassification (import transformers)", "sortText": "585"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationInput", "kind": 6, "label": "VideoClassificationInput (import huggingface_hub)", "sortText": "586"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForImagesAndTextClassification", "kind": 7, "label": "ViltForImagesAndTextClassification (import transformers)", "sortText": "593"}, {"additionalTextEdits": [{"newText": ", ViltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViltForTokenClassification", "kind": 7, "label": "ViltForTokenClassification (import transformers)", "sortText": "594"}, {"additionalTextEdits": [{"newText": ", VivitForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VivitForVideoClassification", "kind": 7, "label": "VivitForVideoClassification (import transformers)", "sortText": "595"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "601"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers)", "sortText": "602"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "603"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": 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"sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} +{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 4, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 34"}, {"additionalTextEdits": [{"newText": ", ArceeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers)", "sortText": " 35"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForTokenClassification", "kind": 7, "label": "ArceeForTokenClassification (import transformers.models.arcee.modular_arcee)", "sortText": " 36"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationInput", "kind": 6, "label": "AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BitForImageClassification", "kind": 7, "label": "BitForImageClassification (import transformers)", "sortText": " 62"}, {"additionalTextEdits": [{"newText": ", BloomForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForSequenceClassification", "kind": 7, "label": "BloomForSequenceClassification (import transformers)", "sortText": " 63"}, {"additionalTextEdits": [{"newText": ", BloomForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForTokenClassification", "kind": 7, "label": "BloomForTokenClassification (import transformers)", "sortText": " 64"}, {"additionalTextEdits": [{"newText": ", BrosForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosForTokenClassification", "kind": 7, "label": "BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers)", "sortText": " 99"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForTokenClassification", "kind": 7, "label": "DeepseekV3ForTokenClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": "100"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassification", "kind": 7, "label": "DeiTForImageClassification (import transformers)", "sortText": "101"}, {"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, 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"ErnieForSequenceClassification", "kind": 7, "label": "ErnieForSequenceClassification (import transformers)", "sortText": "125"}, {"additionalTextEdits": [{"newText": ", ErnieForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieForTokenClassification", "kind": 7, "label": "ErnieForTokenClassification (import transformers)", "sortText": "126"}, {"additionalTextEdits": [{"newText": ", ErnieMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForSequenceClassification", "kind": 7, "label": "ErnieMForSequenceClassification (import transformers)", "sortText": "127"}, {"additionalTextEdits": [{"newText": ", ErnieMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ErnieMForTokenClassification", "kind": 7, "label": "ErnieMForTokenClassification (import 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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"kind": 21, "label": "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "137"}, {"additionalTextEdits": [{"newText": ", FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "138"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "139"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "140"}, {"additionalTextEdits": [{"newText": ", FNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForSequenceClassification", "kind": 7, "label": "FNetForSequenceClassification (import transformers)", "sortText": "141"}, {"additionalTextEdits": [{"newText": ", FNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForTokenClassification", "kind": 7, "label": "FNetForTokenClassification (import transformers)", "sortText": "142"}, {"additionalTextEdits": [{"newText": ", FalconForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForSequenceClassification", "kind": 7, "label": "FalconForSequenceClassification (import transformers)", "sortText": "143"}, {"additionalTextEdits": [{"newText": ", FalconForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForTokenClassification", "kind": 7, "label": "FalconForTokenClassification (import transformers)", "sortText": "144"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import FixMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FixMetaclass", "kind": 7, "label": "FixMetaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "145"}, {"additionalTextEdits": [{"newText": ", FlaubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForSequenceClassification", "kind": 7, "label": "FlaubertForSequenceClassification (import transformers)", 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"GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 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0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"sortText": "434"}, {"additionalTextEdits": [{"newText": "from transformers.models.starcoder2.modular_starcoder2 import Starcoder2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Starcoder2ForSequenceClassification", "kind": 7, "label": "Starcoder2ForSequenceClassification (import transformers.models.starcoder2.modular_starcoder2)", "sortText": "435"}, {"additionalTextEdits": [{"newText": ", Starcoder2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Starcoder2ForTokenClassification", "kind": 7, "label": "Starcoder2ForTokenClassification (import transformers)", "sortText": "436"}, {"additionalTextEdits": [{"newText": "from transformers.models.starcoder2.modular_starcoder2 import Starcoder2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": 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"sortText": "537"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "538"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "539"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "540"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "541"}, {"additionalTextEdits": [{"newText": ", TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "542"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKENIZER_CLASSES", "kind": 21, "label": "TOKENIZER_CLASSES (import transformers.convert_slow_tokenizers_checkpoints_to_fast)", "sortText": "546"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "547"}, {"additionalTextEdits": [{"newText": ", TapasForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TapasForSequenceClassification", "kind": 7, "label": "TapasForSequenceClassification (import transformers)", "sortText": "548"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": 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"line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": 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{"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": 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{"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 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"insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "599"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers)", "sortText": "600"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ConformerForAudioFrameClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "601"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ConformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers)", "sortText": "602"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer import Wav2Vec2ConformerForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2ConformerForSequenceClassification", "kind": 7, "label": "Wav2Vec2ConformerForSequenceClassification (import transformers.models.wav2vec2_conformer.modular_wav2vec2_conformer)", "sortText": "603"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2ForAudioFrameClassification (import transformers)", "sortText": "604"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2ForSequenceClassification", "kind": 7, "label": "Wav2Vec2ForSequenceClassification (import transformers)", "sortText": "605"}, {"additionalTextEdits": [{"newText": ", WavLMForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers)", "sortText": "606"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities)", "sortText": "737"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities (import transformers.models.deprecated.transfo_xl.modeling_transfo_xl_utilities)", "sortText": "738"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.tvlt.image_processing_tvlt\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.tvlt.image_processing_tvlt", "kind": 9, "label": "transformers.models.deprecated.tvlt.image_processing_tvlt (import transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} +{"suite": "transformers", "label": "classifier pipeline completion", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 15, "character": 19, "iteration": 5, "result": {"isIncomplete": true, "items": [{"detail": "Unknown", "documentation": {"kind": "plaintext", "value": "`Unknown` is a dynamic type inferred due to missing type information or an inference error.\n\nty infers `Unknown` for unannotated values with insufficient type information. It also uses it as a\nfallback after certain type errors. This contrasts with `Any`, which represents an *explicitly*\nannotated dynamic type. Like `Any`, however, it is a dynamic type, so ty allows any operation on it.\n"}, "label": "classifier", "sortText": " 0"}, {"additionalTextEdits": [{"newText": "import dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclasses", "kind": 9, "label": "dataclasses (import dataclasses)", "sortText": " 1"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": " 2"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": " 3"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import CLASS_MEMBER_MODIFIER\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CLASS_MEMBER_MODIFIER", "kind": 21, "label": "CLASS_MEMBER_MODIFIER (import python_lsp_compare.tsp_semantic_tokens)", "sortText": " 4"}, {"additionalTextEdits": [{"newText": "from typing import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing)", "sortText": " 5"}, {"additionalTextEdits": [{"newText": "from typing import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing)", "sortText": " 6"}, {"additionalTextEdits": [{"newText": "from msilib.schema import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 6, "label": "Class (import msilib.schema)", "sortText": " 7"}, {"additionalTextEdits": [{"newText": "from pyclbr import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import pyclbr)", "sortText": " 8"}, {"additionalTextEdits": [{"newText": "from symtable import Class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Class", "kind": 7, "label": "Class (import symtable)", "sortText": " 9"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassAttrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassAttrs", "kind": 7, "label": "ClassAttrs (import transformers.utils.auto_docstring)", "sortText": " 10"}, {"additionalTextEdits": [{"newText": "from ast import ClassDef\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDef", "kind": 7, "label": "ClassDef (import ast)", "sortText": " 11"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import ClassDocstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassDocstring", "kind": 7, "label": "ClassDocstring (import transformers.utils.auto_docstring)", "sortText": " 12"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import ClassFinder\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFinder", "kind": 7, "label": "ClassFinder (import transformers.commands.add_new_model_like)", "sortText": " 13"}, {"additionalTextEdits": [{"newText": "from inspect import ClassFoundException\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassFoundException", "kind": 7, "label": "ClassFoundException (import inspect)", "sortText": " 14"}, {"additionalTextEdits": [{"newText": "from transformers.activations import ClassInstantier\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassInstantier", "kind": 7, "label": "ClassInstantier (import transformers.activations)", "sortText": " 15"}, {"additionalTextEdits": [{"newText": "from types import ClassMethodDescriptorType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassMethodDescriptorType", "kind": 7, "label": "ClassMethodDescriptorType (import types)", "sortText": " 16"}, {"additionalTextEdits": [{"newText": "from typing_extensions import ClassVar\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassVar", "kind": 6, "label": "ClassVar (import typing_extensions)", "sortText": " 17"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.image_classification)", "sortText": " 18"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import ClassificationFunction\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassificationFunction", "kind": 7, "label": "ClassificationFunction (import transformers.pipelines.text_classification)", "sortText": " 19"}, {"additionalTextEdits": [{"newText": ", ClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": " 20"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": " 21"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import ClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "ClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": " 22"}, {"additionalTextEdits": [{"newText": "from inspect import classify_class_attrs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "classify_class_attrs", "kind": 3, "label": "classify_class_attrs (import inspect)", "sortText": " 23"}, {"additionalTextEdits": [{"newText": "from subprocess import ABOVE_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ABOVE_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "ABOVE_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 24"}, {"additionalTextEdits": [{"newText": ", ASTForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ASTForAudioClassification", "kind": 7, "label": "ASTForAudioClassification (import transformers)", "sortText": " 25"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 26"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import AUDIO_FRAME_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUDIO_FRAME_CLASSIFICATION_SAMPLE", "kind": 21, "label": "AUDIO_FRAME_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": " 27"}, {"additionalTextEdits": [{"newText": "from transformers.processing_utils import AUTO_TO_BASE_CLASS_MAPPING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AUTO_TO_BASE_CLASS_MAPPING", "kind": 21, "label": "AUTO_TO_BASE_CLASS_MAPPING (import transformers.processing_utils)", "sortText": " 28"}, {"additionalTextEdits": [{"newText": ", AlbertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForSequenceClassification", "kind": 7, "label": "AlbertForSequenceClassification (import transformers)", "sortText": " 29"}, {"additionalTextEdits": [{"newText": ", AlbertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AlbertForTokenClassification", "kind": 7, "label": "AlbertForTokenClassification (import transformers)", "sortText": " 30"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus)", "sortText": " 31"}, {"additionalTextEdits": [{"newText": "from transformers.models.apertus.modular_apertus import ApertusForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ApertusForTokenClassification", "kind": 7, "label": "ApertusForTokenClassification (import transformers.models.apertus.modular_apertus)", "sortText": " 32"}, {"additionalTextEdits": [{"newText": ", ArceeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import transformers)", "sortText": " 33"}, {"additionalTextEdits": [{"newText": "from transformers.models.arcee.modular_arcee import ArceeForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ArceeForSequenceClassification", "kind": 7, "label": "ArceeForSequenceClassification (import 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"AudioClassificationInput (import huggingface_hub)", "sortText": " 37"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputElement", "kind": 6, "label": "AudioClassificationOutputElement (import huggingface_hub)", "sortText": " 38"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationOutputTransform", "kind": 6, "label": "AudioClassificationOutputTransform (import huggingface_hub)", "sortText": " 39"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import AudioClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationParameters", "kind": 6, "label": "AudioClassificationParameters (import huggingface_hub)", "sortText": " 40"}, {"additionalTextEdits": [{"newText": ", AudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AudioClassificationPipeline", "kind": 6, "label": "AudioClassificationPipeline (import transformers)", "sortText": " 41"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.audio_classification import AudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "AudioClassificationPipeline", "kind": 7, "label": "AudioClassificationPipeline (import transformers.pipelines.audio_classification)", "sortText": " 42"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioClassification", "kind": 7, "label": "AutoModelForAudioClassification (import transformers)", "sortText": " 43"}, {"additionalTextEdits": [{"newText": ", AutoModelForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForAudioFrameClassification", "kind": 7, "label": "AutoModelForAudioFrameClassification (import transformers)", "sortText": " 44"}, {"additionalTextEdits": [{"newText": ", AutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForImageClassification", "kind": 7, "label": "AutoModelForImageClassification (import transformers)", "sortText": " 45"}, {"additionalTextEdits": [{"newText": ", AutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForSequenceClassification", "kind": 7, "label": "AutoModelForSequenceClassification (import transformers)", "sortText": " 46"}, {"additionalTextEdits": [{"newText": ", AutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForTokenClassification", "kind": 7, "label": "AutoModelForTokenClassification (import transformers)", "sortText": " 47"}, {"additionalTextEdits": [{"newText": ", AutoModelForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForVideoClassification", "kind": 7, "label": "AutoModelForVideoClassification (import transformers)", "sortText": " 48"}, {"additionalTextEdits": [{"newText": ", AutoModelForZeroShotImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "AutoModelForZeroShotImageClassification", "kind": 7, "label": "AutoModelForZeroShotImageClassification (import transformers)", "sortText": " 49"}, {"additionalTextEdits": [{"newText": "from subprocess import BELOW_NORMAL_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BELOW_NORMAL_PRIORITY_CLASS", "kind": 21, "label": "BELOW_NORMAL_PRIORITY_CLASS (import subprocess)", "sortText": " 50"}, {"additionalTextEdits": [{"newText": ", BartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BartForSequenceClassification", "kind": 7, "label": "BartForSequenceClassification (import transformers)", "sortText": " 51"}, {"additionalTextEdits": [{"newText": ", BeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BeitForImageClassification", "kind": 7, "label": "BeitForImageClassification (import transformers)", "sortText": " 52"}, {"additionalTextEdits": [{"newText": ", BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForSequenceClassification", "kind": 7, "label": "BertForSequenceClassification (import transformers)", "sortText": " 53"}, {"additionalTextEdits": [{"newText": ", BertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BertForTokenClassification", "kind": 7, "label": "BertForTokenClassification (import transformers)", "sortText": " 54"}, {"additionalTextEdits": [{"newText": ", BigBirdForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForSequenceClassification", "kind": 7, "label": "BigBirdForSequenceClassification (import transformers)", "sortText": " 55"}, {"additionalTextEdits": [{"newText": ", BigBirdForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdForTokenClassification", "kind": 7, "label": "BigBirdForTokenClassification (import transformers)", "sortText": " 56"}, {"additionalTextEdits": [{"newText": ", BigBirdPegasusForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BigBirdPegasusForSequenceClassification", "kind": 7, "label": "BigBirdPegasusForSequenceClassification (import transformers)", "sortText": " 57"}, {"additionalTextEdits": [{"newText": ", BioGptForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers)", "sortText": " 58"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForSequenceClassification", "kind": 7, "label": "BioGptForSequenceClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 59"}, {"additionalTextEdits": [{"newText": ", BioGptForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers)", "sortText": " 60"}, {"additionalTextEdits": [{"newText": "from transformers.models.biogpt.modular_biogpt import BioGptForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "BioGptForTokenClassification", "kind": 7, "label": "BioGptForTokenClassification (import transformers.models.biogpt.modular_biogpt)", "sortText": " 61"}, {"additionalTextEdits": [{"newText": ", BitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BitForImageClassification", "kind": 7, "label": "BitForImageClassification (import transformers)", "sortText": " 62"}, {"additionalTextEdits": [{"newText": ", BloomForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForSequenceClassification", "kind": 7, "label": "BloomForSequenceClassification (import transformers)", "sortText": " 63"}, {"additionalTextEdits": [{"newText": ", BloomForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BloomForTokenClassification", "kind": 7, "label": "BloomForTokenClassification (import transformers)", "sortText": " 64"}, {"additionalTextEdits": [{"newText": ", BrosForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosForTokenClassification", "kind": 7, "label": "BrosForTokenClassification (import transformers)", "sortText": " 65"}, {"additionalTextEdits": [{"newText": ", BrosSpadeEEForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeEEForTokenClassification", "kind": 7, "label": "BrosSpadeEEForTokenClassification (import transformers)", "sortText": " 66"}, {"additionalTextEdits": [{"newText": ", BrosSpadeELForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "BrosSpadeELForTokenClassification", "kind": 7, "label": "BrosSpadeELForTokenClassification (import transformers)", "sortText": " 67"}, {"additionalTextEdits": [{"newText": ", CLIPForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPForImageClassification", "kind": 7, "label": "CLIPForImageClassification (import transformers)", "sortText": " 68"}, {"additionalTextEdits": [{"newText": ", CTRLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CTRLForSequenceClassification", "kind": 7, "label": "CTRLForSequenceClassification (import transformers)", "sortText": " 69"}, {"additionalTextEdits": [{"newText": ", CamembertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForSequenceClassification", "kind": 7, "label": "CamembertForSequenceClassification (import transformers)", "sortText": " 70"}, {"additionalTextEdits": [{"newText": ", CamembertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CamembertForTokenClassification", "kind": 7, "label": "CamembertForTokenClassification (import transformers)", "sortText": " 71"}, {"additionalTextEdits": [{"newText": ", CanineForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForSequenceClassification", "kind": 7, "label": "CanineForSequenceClassification (import transformers)", "sortText": " 72"}, {"additionalTextEdits": [{"newText": ", CanineForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CanineForTokenClassification", "kind": 7, "label": "CanineForTokenClassification (import transformers)", "sortText": " 73"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputToolChoiceClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputToolChoiceClass", "kind": 6, "label": "ChatCompletionInputToolChoiceClass (import huggingface_hub)", "sortText": " 74"}, {"additionalTextEdits": [{"newText": ", ConvBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForSequenceClassification", "kind": 7, "label": "ConvBertForSequenceClassification (import transformers)", "sortText": " 75"}, {"additionalTextEdits": [{"newText": ", ConvBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvBertForTokenClassification", "kind": 7, "label": "ConvBertForTokenClassification (import transformers)", "sortText": " 76"}, {"additionalTextEdits": [{"newText": ", ConvNextForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextForImageClassification", "kind": 7, "label": "ConvNextForImageClassification (import transformers)", "sortText": " 77"}, {"additionalTextEdits": [{"newText": ", ConvNextV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConvNextV2ForImageClassification", "kind": 7, "label": "ConvNextV2ForImageClassification (import transformers)", "sortText": " 78"}, {"additionalTextEdits": [{"newText": ", CvtForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CvtForImageClassification", "kind": 7, "label": "CvtForImageClassification (import transformers)", "sortText": " 79"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForAudioFrameClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers)", "sortText": " 80"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForAudioFrameClassification", "kind": 7, "label": "Data2VecAudioForAudioFrameClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 81"}, {"additionalTextEdits": [{"newText": ", Data2VecAudioForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers)", "sortText": " 82"}, {"additionalTextEdits": [{"newText": "from transformers.models.data2vec.modular_data2vec_audio import Data2VecAudioForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Data2VecAudioForSequenceClassification", "kind": 7, "label": "Data2VecAudioForSequenceClassification (import transformers.models.data2vec.modular_data2vec_audio)", "sortText": " 83"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForSequenceClassification", "kind": 7, "label": "Data2VecTextForSequenceClassification (import transformers)", "sortText": " 84"}, {"additionalTextEdits": [{"newText": ", Data2VecTextForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecTextForTokenClassification", "kind": 7, "label": "Data2VecTextForTokenClassification (import transformers)", "sortText": " 85"}, {"additionalTextEdits": [{"newText": ", Data2VecVisionForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Data2VecVisionForImageClassification", "kind": 7, "label": "Data2VecVisionForImageClassification (import transformers)", "sortText": " 86"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClass", "kind": 6, "label": "DataClass (import transformers.hf_argparser)", "sortText": " 87"}, {"additionalTextEdits": [{"newText": "from transformers.hf_argparser import DataClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataClassType", "kind": 6, "label": "DataClassType (import transformers.hf_argparser)", "sortText": " 88"}, {"additionalTextEdits": [{"newText": ", DataCollatorForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForTokenClassification", "kind": 7, "label": "DataCollatorForTokenClassification (import transformers)", "sortText": " 89"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import huggingface_hub.hub_mixin)", "sortText": " 90"}, {"additionalTextEdits": [{"newText": ", DebertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForSequenceClassification", "kind": 7, "label": "DebertaForSequenceClassification (import transformers)", "sortText": " 91"}, {"additionalTextEdits": [{"newText": ", DebertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaForTokenClassification", "kind": 7, "label": "DebertaForTokenClassification (import transformers)", "sortText": " 92"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForSequenceClassification", "kind": 7, "label": "DebertaV2ForSequenceClassification (import transformers)", "sortText": " 93"}, {"additionalTextEdits": [{"newText": ", DebertaV2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DebertaV2ForTokenClassification", "kind": 7, "label": "DebertaV2ForTokenClassification (import transformers)", "sortText": " 94"}, {"additionalTextEdits": [{"newText": ", DeepseekV2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers)", "sortText": " 95"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v2.modular_deepseek_v2 import DeepseekV2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV2ForSequenceClassification", "kind": 7, "label": "DeepseekV2ForSequenceClassification (import transformers.models.deepseek_v2.modular_deepseek_v2)", "sortText": " 96"}, {"additionalTextEdits": [{"newText": ", DeepseekV3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers)", "sortText": " 97"}, {"additionalTextEdits": [{"newText": "from transformers.models.deepseek_v3.modular_deepseek_v3 import DeepseekV3ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DeepseekV3ForSequenceClassification", "kind": 7, "label": "DeepseekV3ForSequenceClassification (import transformers.models.deepseek_v3.modular_deepseek_v3)", "sortText": " 98"}, {"additionalTextEdits": [{"newText": ", 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{"additionalTextEdits": [{"newText": ", DeiTForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DeiTForImageClassificationWithTeacher", "kind": 7, "label": "DeiTForImageClassificationWithTeacher (import transformers)", "sortText": "102"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import DiaClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiaClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "DiaClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "103"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers)", "sortText": "104"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForSequenceClassification", "kind": 7, "label": "DiffLlamaForSequenceClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "105"}, {"additionalTextEdits": [{"newText": ", DiffLlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers)", "sortText": "106"}, {"additionalTextEdits": [{"newText": "from transformers.models.diffllama.modular_diffllama import DiffLlamaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DiffLlamaForTokenClassification", "kind": 7, "label": "DiffLlamaForTokenClassification (import transformers.models.diffllama.modular_diffllama)", "sortText": "107"}, {"additionalTextEdits": [{"newText": ", DinatForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DinatForImageClassification", "kind": 7, "label": "DinatForImageClassification (import transformers)", "sortText": "108"}, {"additionalTextEdits": [{"newText": ", Dinov2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2ForImageClassification", "kind": 7, "label": "Dinov2ForImageClassification (import transformers)", "sortText": "109"}, {"additionalTextEdits": [{"newText": ", Dinov2WithRegistersForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers)", "sortText": "110"}, {"additionalTextEdits": [{"newText": "from transformers.models.dinov2_with_registers.modular_dinov2_with_registers import Dinov2WithRegistersForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Dinov2WithRegistersForImageClassification", "kind": 7, "label": "Dinov2WithRegistersForImageClassification (import transformers.models.dinov2_with_registers.modular_dinov2_with_registers)", "sortText": "111"}, {"additionalTextEdits": [{"newText": ", DistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForSequenceClassification", "kind": 7, "label": "DistilBertForSequenceClassification (import transformers)", "sortText": "112"}, {"additionalTextEdits": [{"newText": ", DistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DistilBertForTokenClassification", "kind": 7, "label": "DistilBertForTokenClassification (import transformers)", "sortText": "113"}, {"additionalTextEdits": [{"newText": "from distutils.errors import DistutilsClassError\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DistutilsClassError", "kind": 7, "label": "DistutilsClassError (import distutils.errors)", "sortText": "114"}, {"additionalTextEdits": [{"newText": "from ctypes import DllGetClassObject\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DllGetClassObject", "kind": 3, "label": "DllGetClassObject (import ctypes)", "sortText": "115"}, {"additionalTextEdits": [{"newText": "from transformers.models.doge import DogeForSequenceClassification\n", "range": {"end": {"character": 0, 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transformers.models.exaone4.modular_exaone4 import Exaone4ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForSequenceClassification", "kind": 7, "label": "Exaone4ForSequenceClassification (import transformers.models.exaone4.modular_exaone4)", "sortText": "132"}, {"additionalTextEdits": [{"newText": ", Exaone4ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import transformers)", "sortText": "133"}, {"additionalTextEdits": [{"newText": "from transformers.models.exaone4.modular_exaone4 import Exaone4ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Exaone4ForTokenClassification", "kind": 7, "label": "Exaone4ForTokenClassification (import 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"kind": 21, "label": "FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "137"}, {"additionalTextEdits": [{"newText": ", FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "FLAX_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "138"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_SEQUENCE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "139"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import FLAX_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLAX_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "FLAX_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "140"}, {"additionalTextEdits": [{"newText": ", FNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForSequenceClassification", "kind": 7, "label": "FNetForSequenceClassification (import transformers)", "sortText": "141"}, {"additionalTextEdits": [{"newText": ", FNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FNetForTokenClassification", "kind": 7, "label": "FNetForTokenClassification (import transformers)", "sortText": "142"}, {"additionalTextEdits": [{"newText": ", FalconForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForSequenceClassification", "kind": 7, "label": "FalconForSequenceClassification (import transformers)", "sortText": "143"}, {"additionalTextEdits": [{"newText": ", FalconForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FalconForTokenClassification", "kind": 7, "label": "FalconForTokenClassification (import transformers)", "sortText": "144"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import FixMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FixMetaclass", "kind": 7, "label": "FixMetaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "145"}, {"additionalTextEdits": [{"newText": ", FlaubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaubertForSequenceClassification", "kind": 7, "label": "FlaubertForSequenceClassification (import transformers)", 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FlaxAutoModelForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForImageClassification", "kind": 7, "label": "FlaxAutoModelForImageClassification (import transformers)", "sortText": "150"}, {"additionalTextEdits": [{"newText": ", FlaxAutoModelForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForSequenceClassification", "kind": 7, "label": "FlaxAutoModelForSequenceClassification (import transformers)", "sortText": "151"}, {"additionalTextEdits": [{"newText": ", FlaxAutoModelForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxAutoModelForTokenClassification", "kind": 7, "label": "FlaxAutoModelForTokenClassification (import transformers)", "sortText": "152"}, {"additionalTextEdits": [{"newText": ", FlaxBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBartForSequenceClassification", "kind": 7, "label": "FlaxBartForSequenceClassification (import transformers)", "sortText": "153"}, {"additionalTextEdits": [{"newText": ", FlaxBeitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBeitForImageClassification", "kind": 7, "label": "FlaxBeitForImageClassification (import transformers)", "sortText": "154"}, {"additionalTextEdits": [{"newText": ", FlaxBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxBertForSequenceClassification", "kind": 7, "label": "FlaxBertForSequenceClassification (import transformers)", "sortText": "155"}, {"additionalTextEdits": [{"newText": ", FlaxBertForTokenClassification", "range": {"end": {"character": 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1}}}], "insertText": "FlaxDinov2ForImageClassification", "kind": 7, "label": "FlaxDinov2ForImageClassification (import transformers)", "sortText": "159"}, {"additionalTextEdits": [{"newText": ", FlaxDistilBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxDistilBertForSequenceClassification", "kind": 7, "label": "FlaxDistilBertForSequenceClassification (import transformers)", "sortText": "160"}, {"additionalTextEdits": [{"newText": ", FlaxDistilBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxDistilBertForTokenClassification", "kind": 7, "label": "FlaxDistilBertForTokenClassification (import transformers)", "sortText": "161"}, {"additionalTextEdits": [{"newText": ", FlaxElectraForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxElectraForSequenceClassification", "kind": 7, "label": "FlaxElectraForSequenceClassification (import transformers)", "sortText": "162"}, {"additionalTextEdits": [{"newText": ", FlaxElectraForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxElectraForTokenClassification", "kind": 7, "label": "FlaxElectraForTokenClassification (import transformers)", "sortText": "163"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flax_outputs import FlaxImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FlaxImageClassifierOutputWithNoAttention", "kind": 7, "label": "FlaxImageClassifierOutputWithNoAttention (import transformers.modeling_flax_outputs)", "sortText": "164"}, {"additionalTextEdits": [{"newText": ", FlaxMBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxMBartForSequenceClassification", "kind": 7, "label": "FlaxMBartForSequenceClassification (import transformers)", "sortText": "165"}, {"additionalTextEdits": [{"newText": ", FlaxRegNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRegNetForImageClassification", "kind": 7, "label": "FlaxRegNetForImageClassification (import transformers)", "sortText": "166"}, {"additionalTextEdits": [{"newText": ", FlaxResNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxResNetForImageClassification", "kind": 7, "label": "FlaxResNetForImageClassification (import transformers)", "sortText": "167"}, {"additionalTextEdits": [{"newText": ", FlaxRoFormerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRoFormerForSequenceClassification", "kind": 7, "label": "FlaxRoFormerForSequenceClassification (import transformers)", "sortText": "168"}, {"additionalTextEdits": [{"newText": ", FlaxRoFormerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRoFormerForTokenClassification", "kind": 7, "label": "FlaxRoFormerForTokenClassification (import transformers)", "sortText": "169"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaForSequenceClassification", "kind": 7, "label": "FlaxRobertaForSequenceClassification (import transformers)", "sortText": "170"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaForTokenClassification", "kind": 7, "label": "FlaxRobertaForTokenClassification (import transformers)", "sortText": "171"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaPreLayerNormForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaPreLayerNormForSequenceClassification", "kind": 7, "label": "FlaxRobertaPreLayerNormForSequenceClassification (import transformers)", "sortText": "172"}, {"additionalTextEdits": [{"newText": ", FlaxRobertaPreLayerNormForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "FlaxRobertaPreLayerNormForTokenClassification", "kind": 7, "label": "FlaxRobertaPreLayerNormForTokenClassification (import transformers)", "sortText": "173"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flax_outputs import FlaxSeq2SeqSequenceClassifierOutput\n", "range": {"end": 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"line": 0}}}], "insertText": "Gemma2ForSequenceClassification", "kind": 7, "label": "Gemma2ForSequenceClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "198"}, {"additionalTextEdits": [{"newText": ", Gemma2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers)", "sortText": "199"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma2.modular_gemma2 import Gemma2ForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma2ForTokenClassification", "kind": 7, "label": "Gemma2ForTokenClassification (import transformers.models.gemma2.modular_gemma2)", "sortText": "200"}, {"additionalTextEdits": [{"newText": ", Gemma3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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Gemma3TextForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Gemma3TextForSequenceClassification", "kind": 7, "label": "Gemma3TextForSequenceClassification (import transformers.models.gemma3.modular_gemma3)", "sortText": "204"}, {"additionalTextEdits": [{"newText": ", GemmaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers)", "sortText": "205"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForSequenceClassification", "kind": 7, "label": "GemmaForSequenceClassification (import transformers.models.gemma.modular_gemma)", "sortText": "206"}, {"additionalTextEdits": [{"newText": ", GemmaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers)", "sortText": "207"}, {"additionalTextEdits": [{"newText": "from transformers.models.gemma.modular_gemma import GemmaForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GemmaForTokenClassification", "kind": 7, "label": "GemmaForTokenClassification (import transformers.models.gemma.modular_gemma)", "sortText": "208"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_layers import GenericForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GenericForSequenceClassification", "kind": 7, "label": "GenericForSequenceClassification (import 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"GlmForSequenceClassification (import transformers)", "sortText": "215"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForSequenceClassification", "kind": 7, "label": "GlmForSequenceClassification (import transformers.models.glm.modular_glm)", "sortText": "216"}, {"additionalTextEdits": [{"newText": ", GlmForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers)", "sortText": "217"}, {"additionalTextEdits": [{"newText": "from transformers.models.glm.modular_glm import GlmForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GlmForTokenClassification", "kind": 7, "label": "GlmForTokenClassification (import transformers.models.glm.modular_glm)", "sortText": "218"}, {"additionalTextEdits": [{"newText": ", GptOssForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers)", "sortText": "219"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForSequenceClassification", "kind": 7, "label": "GptOssForSequenceClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "220"}, {"additionalTextEdits": [{"newText": ", GptOssForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers)", "sortText": "221"}, {"additionalTextEdits": [{"newText": "from transformers.models.gpt_oss.modular_gpt_oss import GptOssForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "GptOssForTokenClassification", "kind": 7, "label": "GptOssForTokenClassification (import transformers.models.gpt_oss.modular_gpt_oss)", "sortText": "222"}, {"additionalTextEdits": [{"newText": ", GraphormerForGraphClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "GraphormerForGraphClassification", "kind": 7, "label": "GraphormerForGraphClassification (import transformers)", "sortText": "223"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import HFProxyableClassMeta\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HFProxyableClassMeta", "kind": 7, "label": "HFProxyableClassMeta (import transformers.utils.fx)", "sortText": "224"}, {"additionalTextEdits": [{"newText": ", HGNetV2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers)", "sortText": "225"}, {"additionalTextEdits": [{"newText": "from transformers.models.hgnet_v2.modular_hgnet_v2 import HGNetV2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HGNetV2ForImageClassification", "kind": 7, "label": "HGNetV2ForImageClassification (import transformers.models.hgnet_v2.modular_hgnet_v2)", "sortText": "226"}, {"additionalTextEdits": [{"newText": "from subprocess import HIGH_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HIGH_PRIORITY_CLASS", "kind": 21, "label": "HIGH_PRIORITY_CLASS (import subprocess)", "sortText": "227"}, {"additionalTextEdits": [{"newText": "from winreg import HKEY_CLASSES_ROOT\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HKEY_CLASSES_ROOT", "kind": 21, "label": "HKEY_CLASSES_ROOT (import winreg)", "sortText": "228"}, {"additionalTextEdits": [{"newText": ", HeliumForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers)", "sortText": "229"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForSequenceClassification", "kind": 7, "label": "HeliumForSequenceClassification (import transformers.models.helium.modular_helium)", "sortText": "230"}, {"additionalTextEdits": [{"newText": ", HeliumForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers)", "sortText": "231"}, {"additionalTextEdits": [{"newText": "from transformers.models.helium.modular_helium import HeliumForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HeliumForTokenClassification", "kind": 7, "label": "HeliumForTokenClassification (import transformers.models.helium.modular_helium)", "sortText": "232"}, {"additionalTextEdits": [{"newText": ", HieraForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HieraForImageClassification", "kind": 7, "label": "HieraForImageClassification (import transformers)", "sortText": "233"}, {"additionalTextEdits": [{"newText": ", HubertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers)", "sortText": "234"}, {"additionalTextEdits": [{"newText": "from transformers.models.hubert.modular_hubert import HubertForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HubertForSequenceClassification", "kind": 7, "label": "HubertForSequenceClassification (import transformers.models.hubert.modular_hubert)", "sortText": "235"}, {"additionalTextEdits": [{"newText": ", HunYuanDenseV1ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers)", "sortText": "236"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense import HunYuanDenseV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanDenseV1ForSequenceClassification", "kind": 7, "label": "HunYuanDenseV1ForSequenceClassification (import transformers.models.hunyuan_v1_dense.modular_hunyuan_v1_dense)", "sortText": "237"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modeling_hunyuan_v1_moe)", "sortText": "238"}, {"additionalTextEdits": [{"newText": "from transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe import HunYuanMoEV1ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HunYuanMoEV1ForSequenceClassification", "kind": 7, "label": "HunYuanMoEV1ForSequenceClassification (import transformers.models.hunyuan_v1_moe.modular_hunyuan_v1_moe)", "sortText": "239"}, {"additionalTextEdits": [{"newText": ", IBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForSequenceClassification", "kind": 7, "label": "IBertForSequenceClassification (import transformers)", "sortText": "240"}, {"additionalTextEdits": [{"newText": ", IBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IBertForTokenClassification", "kind": 7, "label": "IBertForTokenClassification (import transformers)", "sortText": "241"}, {"additionalTextEdits": [{"newText": "from subprocess import IDLE_PRIORITY_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IDLE_PRIORITY_CLASS", "kind": 21, "label": "IDLE_PRIORITY_CLASS (import subprocess)", "sortText": "242"}, {"additionalTextEdits": [{"newText": ", IJepaForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers)", "sortText": "243"}, {"additionalTextEdits": [{"newText": "from transformers.models.ijepa.modular_ijepa import IJepaForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IJepaForImageClassification", "kind": 7, "label": "IJepaForImageClassification (import transformers.models.ijepa.modular_ijepa)", "sortText": "244"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "245"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_RECVTCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_RECVTCLASS", "kind": 6, "label": "IPV6_RECVTCLASS (import socket)", "sortText": "246"}, {"additionalTextEdits": [{"newText": "from socket import IPV6_TCLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "IPV6_TCLASS", "kind": 6, "label": "IPV6_TCLASS (import socket)", "sortText": "247"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationInput", "kind": 6, "label": "ImageClassificationInput (import huggingface_hub)", "sortText": "248"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputElement", "kind": 6, "label": "ImageClassificationOutputElement (import huggingface_hub)", "sortText": "249"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationOutputTransform", "kind": 6, "label": "ImageClassificationOutputTransform (import huggingface_hub)", "sortText": "250"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationParameters", "kind": 6, "label": "ImageClassificationParameters (import huggingface_hub)", "sortText": "251"}, {"additionalTextEdits": [{"newText": ", ImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageClassificationPipeline", "kind": 6, "label": "ImageClassificationPipeline (import transformers)", "sortText": "252"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.image_classification import ImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassificationPipeline", "kind": 7, "label": "ImageClassificationPipeline (import transformers.pipelines.image_classification)", "sortText": "253"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutput", "kind": 7, "label": "ImageClassifierOutput (import transformers.modeling_outputs)", "sortText": "254"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import ImageClassifierOutputWithNoAttention\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ImageClassifierOutputWithNoAttention", "kind": 7, "label": "ImageClassifierOutputWithNoAttention (import transformers.modeling_outputs)", "sortText": "255"}, {"additionalTextEdits": [{"newText": ", ImageGPTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ImageGPTForImageClassification", "kind": 7, "label": "ImageGPTForImageClassification (import transformers)", "sortText": "256"}, {"additionalTextEdits": [{"newText": "from transformers.data.data_collator import InputDataClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "InputDataClass", "kind": 6, "label": "InputDataClass (import transformers.data.data_collator)", "sortText": "257"}, {"additionalTextEdits": [{"newText": ", JambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JambaForSequenceClassification", "kind": 7, "label": "JambaForSequenceClassification (import transformers)", "sortText": "258"}, {"additionalTextEdits": [{"newText": ", JetMoeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "JetMoeForSequenceClassification", "kind": 7, "label": "JetMoeForSequenceClassification (import transformers)", "sortText": "259"}, {"additionalTextEdits": [{"newText": ", LEDForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LEDForSequenceClassification", "kind": 7, "label": "LEDForSequenceClassification (import transformers)", "sortText": "260"}, {"additionalTextEdits": [{"newText": ", LayoutLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForSequenceClassification", "kind": 7, "label": "LayoutLMForSequenceClassification (import transformers)", "sortText": "261"}, {"additionalTextEdits": [{"newText": ", LayoutLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMForTokenClassification", "kind": 7, "label": "LayoutLMForTokenClassification (import transformers)", "sortText": "262"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForSequenceClassification", "kind": 7, "label": "LayoutLMv2ForSequenceClassification (import transformers)", "sortText": "263"}, {"additionalTextEdits": [{"newText": ", LayoutLMv2ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv2ForTokenClassification", "kind": 7, "label": "LayoutLMv2ForTokenClassification (import transformers)", "sortText": "264"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForSequenceClassification", "kind": 7, "label": "LayoutLMv3ForSequenceClassification (import transformers)", "sortText": "265"}, {"additionalTextEdits": [{"newText": ", LayoutLMv3ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LayoutLMv3ForTokenClassification", "kind": 7, "label": "LayoutLMv3ForTokenClassification (import transformers)", "sortText": "266"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassification", "kind": 7, "label": "LevitForImageClassification (import transformers)", "sortText": "267"}, {"additionalTextEdits": [{"newText": ", LevitForImageClassificationWithTeacher", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LevitForImageClassificationWithTeacher", "kind": 7, "label": "LevitForImageClassificationWithTeacher (import transformers)", "sortText": "268"}, {"additionalTextEdits": [{"newText": ", LiltForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForSequenceClassification", "kind": 7, "label": "LiltForSequenceClassification (import transformers)", "sortText": "269"}, {"additionalTextEdits": [{"newText": ", LiltForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LiltForTokenClassification", "kind": 7, "label": "LiltForTokenClassification (import transformers)", "sortText": "270"}, {"additionalTextEdits": [{"newText": ", LlamaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForSequenceClassification", "kind": 7, "label": "LlamaForSequenceClassification (import transformers)", "sortText": "271"}, {"additionalTextEdits": [{"newText": ", LlamaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LlamaForTokenClassification", "kind": 7, "label": "LlamaForTokenClassification (import transformers)", "sortText": "272"}, {"additionalTextEdits": [{"newText": ", LongformerForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForSequenceClassification", "kind": 7, "label": "LongformerForSequenceClassification (import transformers)", "sortText": "273"}, {"additionalTextEdits": [{"newText": ", LongformerForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongformerForTokenClassification", "kind": 7, "label": "LongformerForTokenClassification (import transformers)", "sortText": "274"}, {"additionalTextEdits": [{"newText": ", LukeForEntityClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityClassification", "kind": 7, "label": "LukeForEntityClassification (import transformers)", "sortText": "275"}, {"additionalTextEdits": [{"newText": ", LukeForEntityPairClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntityPairClassification", "kind": 7, "label": "LukeForEntityPairClassification (import transformers)", "sortText": "276"}, {"additionalTextEdits": [{"newText": ", LukeForEntitySpanClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForEntitySpanClassification", "kind": 7, "label": "LukeForEntitySpanClassification (import transformers)", "sortText": "277"}, {"additionalTextEdits": [{"newText": ", LukeForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForSequenceClassification", "kind": 7, "label": "LukeForSequenceClassification (import transformers)", "sortText": "278"}, {"additionalTextEdits": [{"newText": ", LukeForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LukeForTokenClassification", "kind": 7, "label": "LukeForTokenClassification (import transformers)", "sortText": "279"}, {"additionalTextEdits": [{"newText": ", MBartForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MBartForSequenceClassification", "kind": 7, "label": "MBartForSequenceClassification (import transformers)", "sortText": "280"}, {"additionalTextEdits": [{"newText": ", MMBTForClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MMBTForClassification", "kind": 7, "label": "MMBTForClassification (import transformers)", "sortText": "281"}, {"additionalTextEdits": [{"newText": "from transformers.data.datasets.squad import MODEL_CONFIG_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MODEL_CONFIG_CLASSES", "kind": 21, "label": "MODEL_CONFIG_CLASSES (import transformers.data.datasets.squad)", "sortText": "282"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "283"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING (import transformers)", "sortText": "284"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "285"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "286"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TIME_SERIES_CLASSIFICATION_MAPPING (import transformers)", "sortText": "287"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING (import transformers)", "sortText": "288"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING (import transformers)", "sortText": "289"}, {"additionalTextEdits": [{"newText": ", MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING", "kind": 21, "label": "MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING (import transformers)", "sortText": "290"}, {"additionalTextEdits": [{"newText": ", MPNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForSequenceClassification", "kind": 7, "label": "MPNetForSequenceClassification (import transformers)", "sortText": "291"}, {"additionalTextEdits": [{"newText": ", MPNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MPNetForTokenClassification", "kind": 7, "label": "MPNetForTokenClassification (import transformers)", "sortText": "292"}, {"additionalTextEdits": [{"newText": ", MT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForSequenceClassification", "kind": 7, "label": "MT5ForSequenceClassification (import transformers)", "sortText": "293"}, {"additionalTextEdits": [{"newText": ", MT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MT5ForTokenClassification", "kind": 7, "label": "MT5ForTokenClassification (import transformers)", "sortText": "294"}, {"additionalTextEdits": [{"newText": ", MarkupLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForSequenceClassification", "kind": 7, "label": "MarkupLMForSequenceClassification (import transformers)", "sortText": "295"}, {"additionalTextEdits": [{"newText": ", MarkupLMForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MarkupLMForTokenClassification", "kind": 7, "label": "MarkupLMForTokenClassification (import transformers)", "sortText": "296"}, {"additionalTextEdits": [{"newText": "from ast import MatchClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MatchClass", "kind": 7, "label": "MatchClass (import ast)", "sortText": "297"}, {"additionalTextEdits": [{"newText": ", MegaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForSequenceClassification", "kind": 7, "label": "MegaForSequenceClassification (import transformers)", "sortText": "298"}, {"additionalTextEdits": [{"newText": ", MegaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegaForTokenClassification", "kind": 7, "label": "MegaForTokenClassification (import transformers)", "sortText": "299"}, {"additionalTextEdits": [{"newText": ", MegatronBertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForSequenceClassification", "kind": 7, "label": "MegatronBertForSequenceClassification (import transformers)", "sortText": "300"}, {"additionalTextEdits": [{"newText": ", MegatronBertForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MegatronBertForTokenClassification", "kind": 7, "label": "MegatronBertForTokenClassification (import transformers)", "sortText": "301"}, {"additionalTextEdits": [{"newText": "from transformers.models.metaclip_2 import MetaClip2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MetaClip2ForImageClassification", "kind": 7, "label": "MetaClip2ForImageClassification (import transformers.models.metaclip_2)", "sortText": "302"}, {"additionalTextEdits": [{"newText": "from transformers.models.metaclip_2.modular_metaclip_2 import MetaClip2ForImageClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MetaClip2ForImageClassification", "kind": 7, "label": "MetaClip2ForImageClassification (import transformers.models.metaclip_2.modular_metaclip_2)", "sortText": "303"}, {"additionalTextEdits": [{"newText": ", MiniMaxForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers)", "sortText": "304"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForSequenceClassification", "kind": 7, "label": "MiniMaxForSequenceClassification (import transformers.models.minimax.modular_minimax)", "sortText": "305"}, {"additionalTextEdits": [{"newText": ", MiniMaxForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers)", "sortText": "306"}, {"additionalTextEdits": [{"newText": "from transformers.models.minimax.modular_minimax import MiniMaxForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MiniMaxForTokenClassification", "kind": 7, "label": "MiniMaxForTokenClassification (import transformers.models.minimax.modular_minimax)", "sortText": "307"}, {"additionalTextEdits": [{"newText": ", MinistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers)", "sortText": "308"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForSequenceClassification", "kind": 7, "label": "MinistralForSequenceClassification (import transformers.models.ministral.modular_ministral)", "sortText": "309"}, {"additionalTextEdits": [{"newText": ", MinistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers)", "sortText": "310"}, {"additionalTextEdits": [{"newText": "from transformers.models.ministral.modular_ministral import MinistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MinistralForTokenClassification", "kind": 7, "label": "MinistralForTokenClassification (import transformers.models.ministral.modular_ministral)", "sortText": "311"}, {"additionalTextEdits": [{"newText": ", MistralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MistralForSequenceClassification", "kind": 7, "label": "MistralForSequenceClassification (import transformers)", "sortText": "312"}, {"additionalTextEdits": [{"newText": "from transformers.models.mistral.modular_mistral import MistralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForSequenceClassification", "kind": 7, "label": "MistralForSequenceClassification (import transformers.models.mistral.modular_mistral)", "sortText": "313"}, {"additionalTextEdits": [{"newText": ", MistralForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers)", "sortText": "314"}, {"additionalTextEdits": [{"newText": "from transformers.models.mistral.modular_mistral import MistralForTokenClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MistralForTokenClassification", "kind": 7, "label": "MistralForTokenClassification (import transformers.models.mistral.modular_mistral)", "sortText": "315"}, {"additionalTextEdits": [{"newText": ", MixtralForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers)", "sortText": "316"}, {"additionalTextEdits": [{"newText": "from transformers.models.mixtral.modular_mixtral import MixtralForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "MixtralForSequenceClassification", "kind": 7, "label": "MixtralForSequenceClassification (import transformers.models.mixtral.modular_mixtral)", "sortText": 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"Seq2SeqSequenceClassifierOutput", "kind": 7, "label": "Seq2SeqSequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "417"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutput", "kind": 7, "label": "SequenceClassifierOutput (import transformers.modeling_outputs)", "sortText": "418"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import SequenceClassifierOutputWithPast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "SequenceClassifierOutputWithPast", "kind": 7, "label": "SequenceClassifierOutputWithPast (import transformers.modeling_outputs)", "sortText": "419"}, {"additionalTextEdits": [{"newText": ", ShieldGemma2ForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": 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"insertText": "TF_SEQUENCE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_SEQUENCE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "543"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TF_TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "544"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TF_VISION_SEQ_CLASS_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TF_VISION_SEQ_CLASS_SAMPLE", "kind": 21, "label": "TF_VISION_SEQ_CLASS_SAMPLE (import transformers.utils.doc)", "sortText": "545"}, {"additionalTextEdits": [{"newText": "from transformers.convert_slow_tokenizers_checkpoints_to_fast import TOKENIZER_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKENIZER_CLASSES", "kind": 21, "label": "TOKENIZER_CLASSES (import transformers.convert_slow_tokenizers_checkpoints_to_fast)", "sortText": "546"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import TOKEN_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TOKEN_CLASSIFICATION_SAMPLE", "kind": 21, "label": "TOKEN_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "547"}, {"additionalTextEdits": [{"newText": ", TapasForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TapasForSequenceClassification", "kind": 7, "label": "TapasForSequenceClassification (import transformers)", "sortText": "548"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationInput", "kind": 6, "label": "TextClassificationInput (import huggingface_hub)", "sortText": "549"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputElement", "kind": 6, "label": "TextClassificationOutputElement (import huggingface_hub)", "sortText": "550"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationOutputTransform", "kind": 6, "label": "TextClassificationOutputTransform (import huggingface_hub)", "sortText": "551"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TextClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationParameters", "kind": 6, "label": "TextClassificationParameters (import huggingface_hub)", "sortText": "552"}, {"additionalTextEdits": [{"newText": ", TextClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextClassificationPipeline", "kind": 6, "label": "TextClassificationPipeline (import transformers)", "sortText": "553"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.text_classification import TextClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TextClassificationPipeline", "kind": 7, "label": "TextClassificationPipeline (import transformers.pipelines.text_classification)", "sortText": "554"}, {"additionalTextEdits": [{"newText": ", TextNetForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TextNetForImageClassification", "kind": 7, "label": "TextNetForImageClassification (import transformers)", "sortText": "555"}, {"additionalTextEdits": [{"newText": ", TimesformerForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TimesformerForVideoClassification", "kind": 7, "label": "TimesformerForVideoClassification (import transformers)", "sortText": "556"}, {"additionalTextEdits": [{"newText": ", TimmWrapperForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TimmWrapperForImageClassification", "kind": 7, "label": "TimmWrapperForImageClassification (import transformers)", "sortText": "557"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationAggregationStrategy\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationAggregationStrategy", "kind": 6, "label": "TokenClassificationAggregationStrategy (import huggingface_hub)", "sortText": "558"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationArgumentHandler", "kind": 7, "label": "TokenClassificationArgumentHandler (import transformers.pipelines.token_classification)", "sortText": "559"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationInput", "kind": 6, "label": "TokenClassificationInput (import huggingface_hub)", "sortText": "560"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationOutputElement", "kind": 6, "label": "TokenClassificationOutputElement (import huggingface_hub)", "sortText": "561"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import TokenClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationParameters", "kind": 6, "label": "TokenClassificationParameters (import huggingface_hub)", "sortText": "562"}, {"additionalTextEdits": [{"newText": ", TokenClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TokenClassificationPipeline", "kind": 6, "label": "TokenClassificationPipeline (import transformers)", "sortText": "563"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.token_classification import TokenClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassificationPipeline", "kind": 7, "label": "TokenClassificationPipeline (import transformers.pipelines.token_classification)", "sortText": "564"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_outputs import TokenClassifierOutput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TokenClassifierOutput", "kind": 7, "label": "TokenClassifierOutput (import transformers.modeling_outputs)", "sortText": "565"}, {"additionalTextEdits": [{"newText": ", TransfoXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TransfoXLForSequenceClassification", "kind": 7, "label": "TransfoXLForSequenceClassification (import transformers)", "sortText": "566"}, {"additionalTextEdits": [{"newText": ", TvltForAudioVisualClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "TvltForAudioVisualClassification", "kind": 7, "label": "TvltForAudioVisualClassification (import transformers)", "sortText": "567"}, {"additionalTextEdits": [{"newText": ", UMT5ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForSequenceClassification", "kind": 7, "label": "UMT5ForSequenceClassification (import transformers)", "sortText": "568"}, {"additionalTextEdits": [{"newText": ", UMT5ForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UMT5ForTokenClassification", "kind": 7, "label": "UMT5ForTokenClassification (import transformers)", "sortText": "569"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import UNROLL_KWARGS_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UNROLL_KWARGS_CLASSES", "kind": 21, "label": "UNROLL_KWARGS_CLASSES (import transformers.utils.auto_docstring)", "sortText": "570"}, {"additionalTextEdits": [{"newText": ", UnbatchedClassifierFreeGuidanceLogitsProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 6, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers)", "sortText": "571"}, {"additionalTextEdits": [{"newText": "from transformers.generation.logits_process import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.generation.logits_process)", "sortText": "572"}, {"additionalTextEdits": [{"newText": "from transformers.utils.dummy_pt_objects import UnbatchedClassifierFreeGuidanceLogitsProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UnbatchedClassifierFreeGuidanceLogitsProcessor", "kind": 7, "label": "UnbatchedClassifierFreeGuidanceLogitsProcessor (import transformers.utils.dummy_pt_objects)", "sortText": "573"}, {"additionalTextEdits": [{"newText": ", UniSpeechForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": "UniSpeechForSequenceClassification (import transformers)", "sortText": "574"}, {"additionalTextEdits": [{"newText": "from transformers.models.unispeech.modular_unispeech import UniSpeechForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "UniSpeechForSequenceClassification", "kind": 7, "label": 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{"additionalTextEdits": [{"newText": ", VJEPA2ForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VJEPA2ForVideoClassification", "kind": 7, "label": "VJEPA2ForVideoClassification (import transformers)", "sortText": "581"}, {"additionalTextEdits": [{"newText": ", VanForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VanForImageClassification", "kind": 7, "label": "VanForImageClassification (import transformers)", "sortText": "582"}, {"additionalTextEdits": [{"newText": ", ViTForImageClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ViTForImageClassification", "kind": 7, "label": "ViTForImageClassification (import transformers)", "sortText": "583"}, {"additionalTextEdits": [{"newText": ", ViTHybridForImageClassification", "range": {"end": {"character": 33, "line": 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"insertText": "VideoClassificationOutputElement", "kind": 6, "label": "VideoClassificationOutputElement (import huggingface_hub)", "sortText": "587"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationOutputTransform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationOutputTransform", "kind": 6, "label": "VideoClassificationOutputTransform (import huggingface_hub)", "sortText": "588"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import VideoClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationParameters", "kind": 6, "label": "VideoClassificationParameters (import huggingface_hub)", "sortText": "589"}, {"additionalTextEdits": [{"newText": ", VideoClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoClassificationPipeline", "kind": 6, "label": "VideoClassificationPipeline (import transformers)", "sortText": "590"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.video_classification import VideoClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "VideoClassificationPipeline", "kind": 7, "label": "VideoClassificationPipeline (import transformers.pipelines.video_classification)", "sortText": "591"}, {"additionalTextEdits": [{"newText": ", VideoMAEForVideoClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "VideoMAEForVideoClassification", "kind": 7, "label": "VideoMAEForVideoClassification (import transformers)", "sortText": "592"}, {"additionalTextEdits": [{"newText": ", ViltForImagesAndTextClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], 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"Wav2Vec2BertForAudioFrameClassification (import transformers)", "sortText": "596"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import Wav2Vec2BertForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Wav2Vec2BertForAudioFrameClassification", "kind": 7, "label": "Wav2Vec2BertForAudioFrameClassification (import transformers.models.wav2vec2_bert.modular_wav2vec2_bert)", "sortText": "597"}, {"additionalTextEdits": [{"newText": ", Wav2Vec2BertForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Wav2Vec2BertForSequenceClassification", "kind": 7, "label": "Wav2Vec2BertForSequenceClassification (import transformers)", "sortText": "598"}, {"additionalTextEdits": [{"newText": "from transformers.models.wav2vec2_bert.modular_wav2vec2_bert import 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transformers.models.wavlm.modular_wavlm import WavLMForAudioFrameClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForAudioFrameClassification", "kind": 7, "label": "WavLMForAudioFrameClassification (import transformers.models.wavlm.modular_wavlm)", "sortText": "607"}, {"additionalTextEdits": [{"newText": ", WavLMForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import transformers)", "sortText": "608"}, {"additionalTextEdits": [{"newText": "from transformers.models.wavlm.modular_wavlm import WavLMForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "WavLMForSequenceClassification", "kind": 7, "label": "WavLMForSequenceClassification (import 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XLMRobertaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForSequenceClassification", "kind": 7, "label": "XLMRobertaForSequenceClassification (import transformers)", "sortText": "613"}, {"additionalTextEdits": [{"newText": ", XLMRobertaForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaForTokenClassification", "kind": 7, "label": "XLMRobertaForTokenClassification (import transformers)", "sortText": "614"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForSequenceClassification", "kind": 7, "label": "XLMRobertaXLForSequenceClassification (import transformers)", "sortText": "615"}, {"additionalTextEdits": [{"newText": ", XLMRobertaXLForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLMRobertaXLForTokenClassification", "kind": 7, "label": "XLMRobertaXLForTokenClassification (import transformers)", "sortText": "616"}, {"additionalTextEdits": [{"newText": ", XLNetForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForSequenceClassification", "kind": 7, "label": "XLNetForSequenceClassification (import transformers)", "sortText": "617"}, {"additionalTextEdits": [{"newText": ", XLNetForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XLNetForTokenClassification", "kind": 7, "label": "XLNetForTokenClassification (import transformers)", "sortText": "618"}, {"additionalTextEdits": [{"newText": ", XmodForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForSequenceClassification", "kind": 7, "label": "XmodForSequenceClassification (import transformers)", "sortText": "619"}, {"additionalTextEdits": [{"newText": ", XmodForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "XmodForTokenClassification", "kind": 7, "label": "XmodForTokenClassification (import transformers)", "sortText": "620"}, {"additionalTextEdits": [{"newText": "from yaml import YAMLObjectMetaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "YAMLObjectMetaclass", "kind": 7, "label": "YAMLObjectMetaclass (import yaml)", "sortText": "621"}, {"additionalTextEdits": [{"newText": ", YosoForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForSequenceClassification", "kind": 7, "label": "YosoForSequenceClassification (import transformers)", "sortText": "622"}, {"additionalTextEdits": [{"newText": ", YosoForTokenClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "YosoForTokenClassification", "kind": 7, "label": "YosoForTokenClassification (import transformers)", "sortText": "623"}, {"additionalTextEdits": [{"newText": "from transformers.utils.doc import ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE", "kind": 21, "label": "ZERO_SHOT_IMAGE_CLASSIFICATION_SAMPLE (import transformers.utils.doc)", "sortText": "624"}, {"additionalTextEdits": [{"newText": ", Zamba2ForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers)", "sortText": "625"}, {"additionalTextEdits": [{"newText": "from transformers.models.zamba2.modular_zamba2 import Zamba2ForSequenceClassification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "Zamba2ForSequenceClassification", "kind": 7, "label": "Zamba2ForSequenceClassification (import transformers.models.zamba2.modular_zamba2)", "sortText": "626"}, {"additionalTextEdits": [{"newText": ", ZambaForSequenceClassification", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZambaForSequenceClassification", "kind": 7, "label": "ZambaForSequenceClassification (import transformers)", "sortText": "627"}, {"additionalTextEdits": [{"newText": ", ZeroShotAudioClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 6, "label": "ZeroShotAudioClassificationPipeline (import transformers)", "sortText": "628"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_audio_classification import ZeroShotAudioClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotAudioClassificationPipeline", "kind": 7, "label": "ZeroShotAudioClassificationPipeline (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "629"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationArgumentHandler\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationArgumentHandler", "kind": 7, "label": "ZeroShotClassificationArgumentHandler (import transformers.pipelines.zero_shot_classification)", "sortText": "630"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationInput", "kind": 6, "label": "ZeroShotClassificationInput (import huggingface_hub)", "sortText": "631"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationOutputElement", "kind": 6, "label": "ZeroShotClassificationOutputElement (import huggingface_hub)", "sortText": "632"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationParameters", "kind": 6, "label": "ZeroShotClassificationParameters (import huggingface_hub)", "sortText": "633"}, {"additionalTextEdits": [{"newText": ", ZeroShotClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 6, "label": "ZeroShotClassificationPipeline (import transformers)", "sortText": "634"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_classification import ZeroShotClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotClassificationPipeline", "kind": 7, "label": "ZeroShotClassificationPipeline (import transformers.pipelines.zero_shot_classification)", "sortText": "635"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationInput\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationInput", "kind": 6, "label": "ZeroShotImageClassificationInput (import huggingface_hub)", "sortText": "636"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationOutputElement\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationOutputElement", "kind": 6, "label": "ZeroShotImageClassificationOutputElement (import huggingface_hub)", "sortText": "637"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ZeroShotImageClassificationParameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationParameters", "kind": 6, "label": "ZeroShotImageClassificationParameters (import huggingface_hub)", "sortText": "638"}, {"additionalTextEdits": [{"newText": ", ZeroShotImageClassificationPipeline", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 6, "label": "ZeroShotImageClassificationPipeline (import transformers)", "sortText": "639"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines.zero_shot_image_classification import ZeroShotImageClassificationPipeline\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ZeroShotImageClassificationPipeline", "kind": 7, "label": "ZeroShotImageClassificationPipeline (import transformers.pipelines.zero_shot_image_classification)", "sortText": "640"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import auto_class_docstring\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "auto_class_docstring", "kind": 3, "label": "auto_class_docstring (import transformers.utils.auto_docstring)", "sortText": "641"}, {"additionalTextEdits": [{"newText": "from idna.idnadata import codepoint_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "codepoint_classes", "kind": 6, "label": "codepoint_classes (import idna.idnadata)", "sortText": "642"}, {"additionalTextEdits": [{"newText": "from dataclasses import dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass", "kind": 3, "label": "dataclass (import dataclasses)", "sortText": "643"}, {"additionalTextEdits": [{"newText": "from typing_extensions import dataclass_transform\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dataclass_transform", "kind": 3, "label": "dataclass_transform (import typing_extensions)", "sortText": "644"}, {"additionalTextEdits": [{"newText": "from logging.config import dictConfigClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "dictConfigClass", "kind": 6, "label": "dictConfigClass (import logging.config)", "sortText": "645"}, {"additionalTextEdits": [{"newText": "from transformers.commands.add_new_model_like import find_all_classes_from_file\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "find_all_classes_from_file", "kind": 3, "label": "find_all_classes_from_file (import transformers.commands.add_new_model_like)", "sortText": "646"}, {"additionalTextEdits": [{"newText": "from logging import getLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getLoggerClass", "kind": 3, "label": "getLoggerClass (import logging)", "sortText": "647"}, {"additionalTextEdits": [{"newText": "from transformers.utils.auto_docstring import get_checkpoint_from_config_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_checkpoint_from_config_class", "kind": 3, "label": "get_checkpoint_from_config_class (import transformers.utils.auto_docstring)", "sortText": "648"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_from_dynamic_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_from_dynamic_module", "kind": 3, "label": "get_class_from_dynamic_module (import transformers.dynamic_module_utils)", "sortText": "649"}, {"additionalTextEdits": [{"newText": "from transformers.dynamic_module_utils import get_class_in_module\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_class_in_module", "kind": 3, "label": "get_class_in_module (import transformers.dynamic_module_utils)", "sortText": "650"}, {"additionalTextEdits": [{"newText": "from fsspec import get_filesystem_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_filesystem_class", "kind": 3, "label": "get_filesystem_class (import fsspec)", "sortText": "651"}, {"additionalTextEdits": [{"newText": "from transformers.trainer_pt_utils import get_module_class_from_name\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "get_module_class_from_name", "kind": 3, "label": "get_module_class_from_name (import transformers.trainer_pt_utils)", "sortText": "652"}, {"additionalTextEdits": [{"newText": "from inspect import getclasstree\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "getclasstree", "kind": 3, "label": "getclasstree (import inspect)", "sortText": "653"}, {"additionalTextEdits": [{"newText": "from lib2to3.fixes.fix_metaclass import has_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "has_metaclass", "kind": 3, "label": "has_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "654"}, {"additionalTextEdits": [{"newText": "import huggingface_hub.dataclasses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "huggingface_hub.dataclasses", "kind": 9, "label": "huggingface_hub.dataclasses (import huggingface_hub.dataclasses)", "sortText": "655"}, {"additionalTextEdits": [{"newText": "from dataclasses import is_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "is_dataclass", "kind": 3, "label": "is_dataclass (import dataclasses)", "sortText": "656"}, {"additionalTextEdits": [{"newText": "from inspect import isclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "isclass", "kind": 3, "label": "isclass (import inspect)", "sortText": "657"}, {"additionalTextEdits": [{"newText": "import lib2to3.fixes.fix_metaclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "lib2to3.fixes.fix_metaclass", "kind": 9, "label": "lib2to3.fixes.fix_metaclass (import lib2to3.fixes.fix_metaclass)", "sortText": "658"}, {"additionalTextEdits": [{"newText": "from dataclasses import make_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "make_dataclass", "kind": 3, "label": "make_dataclass (import dataclasses)", "sortText": "659"}, {"additionalTextEdits": [{"newText": "from types import new_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "new_class", "kind": 3, "label": "new_class (import types)", "sortText": "660"}, {"additionalTextEdits": [{"newText": "from types import prepare_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "prepare_class", "kind": 3, "label": "prepare_class (import types)", "sortText": "661"}, {"additionalTextEdits": [{"newText": "from logging import setLoggerClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "setLoggerClass", "kind": 3, "label": "setLoggerClass (import logging)", "sortText": "662"}, {"additionalTextEdits": [{"newText": "from unittest.util import strclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "strclass", "kind": 3, "label": "strclass (import unittest.util)", "sortText": "663"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.audio_classification", "kind": 9, "label": "transformers.pipelines.audio_classification (import transformers.pipelines.audio_classification)", "sortText": "664"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.image_classification", "kind": 9, "label": "transformers.pipelines.image_classification (import transformers.pipelines.image_classification)", "sortText": "665"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.text_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.text_classification", "kind": 9, "label": "transformers.pipelines.text_classification (import transformers.pipelines.text_classification)", "sortText": "666"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.token_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.token_classification", "kind": 9, "label": "transformers.pipelines.token_classification (import transformers.pipelines.token_classification)", "sortText": "667"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.video_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.video_classification", "kind": 9, "label": "transformers.pipelines.video_classification (import transformers.pipelines.video_classification)", "sortText": "668"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_audio_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_audio_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_audio_classification (import transformers.pipelines.zero_shot_audio_classification)", "sortText": "669"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_classification (import transformers.pipelines.zero_shot_classification)", "sortText": "670"}, {"additionalTextEdits": [{"newText": "import transformers.pipelines.zero_shot_image_classification\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.pipelines.zero_shot_image_classification", "kind": 9, "label": "transformers.pipelines.zero_shot_image_classification (import transformers.pipelines.zero_shot_image_classification)", "sortText": "671"}, {"additionalTextEdits": [{"newText": "from socket import CAN_ISOTP_DEFAULT_EXT_ADDRESS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "CAN_ISOTP_DEFAULT_EXT_ADDRESS", "kind": 21, "label": "CAN_ISOTP_DEFAULT_EXT_ADDRESS (import socket)", "sortText": "672"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessor", "kind": 7, "label": "CLIPImageProcessor (import transformers)", "sortText": "673"}, {"additionalTextEdits": [{"newText": ", CLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "CLIPImageProcessorFast", "kind": 7, "label": "CLIPImageProcessorFast (import transformers)", "sortText": "674"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessor", "kind": 7, "label": "ChameleonImageProcessor (import transformers)", "sortText": "675"}, {"additionalTextEdits": [{"newText": ", ChameleonImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChameleonImageProcessorFast", "kind": 7, "label": "ChameleonImageProcessorFast (import transformers)", "sortText": "676"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import ChatCompletionInputResponseFormatJSONSchema\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ChatCompletionInputResponseFormatJSONSchema", "kind": 6, "label": "ChatCompletionInputResponseFormatJSONSchema (import huggingface_hub)", "sortText": "677"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessor", "kind": 7, "label": "ChineseCLIPImageProcessor (import transformers)", "sortText": "678"}, {"additionalTextEdits": [{"newText": ", ChineseCLIPImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ChineseCLIPImageProcessorFast", "kind": 7, "label": "ChineseCLIPImageProcessorFast (import transformers)", "sortText": "679"}, {"additionalTextEdits": [{"newText": ", ClapProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ClapProcessor", "kind": 7, "label": "ClapProcessor (import transformers)", "sortText": "680"}, {"additionalTextEdits": [{"newText": ", ColPaliProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers)", "sortText": "681"}, {"additionalTextEdits": [{"newText": "from transformers.models.colpali.modular_colpali import ColPaliProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColPaliProcessor", "kind": 7, "label": "ColPaliProcessor (import transformers.models.colpali.modular_colpali)", "sortText": "682"}, {"additionalTextEdits": [{"newText": "from transformers.data.processors.glue import ColaProcessor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ColaProcessor", "kind": 7, "label": "ColaProcessor (import transformers.data.processors.glue)", "sortText": "683"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessor", "kind": 7, "label": "ConditionalDetrImageProcessor (import transformers)", "sortText": "684"}, {"additionalTextEdits": [{"newText": ", ConditionalDetrImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers)", "sortText": "685"}, {"additionalTextEdits": [{"newText": "from transformers.models.conditional_detr.modular_conditional_detr import ConditionalDetrImageProcessorFast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ConditionalDetrImageProcessorFast", "kind": 7, "label": "ConditionalDetrImageProcessorFast (import transformers.models.conditional_detr.modular_conditional_detr)", "sortText": "686"}, {"additionalTextEdits": [{"newText": ", DataCollatorForSeq2Seq", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "DataCollatorForSeq2Seq", "kind": 7, "label": "DataCollatorForSeq2Seq (import transformers)", "sortText": "687"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_mistral_common import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_mistral_common)", "sortText": "688"}, {"additionalTextEdits": [{"newText": "from transformers.tokenization_utils_base import ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING", "kind": 21, "label": "ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING (import transformers.tokenization_utils_base)", "sortText": "689"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessor", "kind": 7, "label": "EfficientLoFTRImageProcessor (import transformers)", "sortText": "690"}, {"additionalTextEdits": [{"newText": ", EfficientLoFTRImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "EfficientLoFTRImageProcessorFast", "kind": 7, "label": "EfficientLoFTRImageProcessorFast (import transformers)", "sortText": "691"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_READ\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_READ", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_READ (import asyncio.constants)", "sortText": "692"}, {"additionalTextEdits": [{"newText": "from asyncio.constants import FLOW_CONTROL_HIGH_WATER_SSL_WRITE\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE", "kind": 21, "label": "FLOW_CONTROL_HIGH_WATER_SSL_WRITE (import asyncio.constants)", "sortText": "693"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.constants import HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD", "kind": 21, "label": "HF_HUB_LOCAL_DIR_AUTO_SYMLINK_THRESHOLD (import huggingface_hub.constants)", "sortText": "694"}, {"additionalTextEdits": [{"newText": "from socket import HVSOCKET_ADDRESS_FLAG_PASSTHRU\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "HVSOCKET_ADDRESS_FLAG_PASSTHRU", "kind": 21, "label": "HVSOCKET_ADDRESS_FLAG_PASSTHRU (import socket)", "sortText": "695"}, {"additionalTextEdits": [{"newText": ", InstructBlipVideoImageProcessor", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "InstructBlipVideoImageProcessor", "kind": 7, "label": "InstructBlipVideoImageProcessor (import transformers)", "sortText": "696"}, {"additionalTextEdits": [{"newText": ", LongcatFlashForCausalLM", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers)", "sortText": "697"}, {"additionalTextEdits": [{"newText": "from transformers.models.longcat_flash.modular_longcat_flash import LongcatFlashForCausalLM\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "LongcatFlashForCausalLM", "kind": 7, "label": "LongcatFlashForCausalLM (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "698"}, {"additionalTextEdits": [{"newText": ", PerceptionLMImageProcessorFast", "range": {"end": {"character": 33, "line": 1}, "start": {"character": 33, "line": 1}}}], "insertText": "PerceptionLMImageProcessorFast", "kind": 7, "label": "PerceptionLMImageProcessorFast (import transformers)", "sortText": "699"}, {"additionalTextEdits": [{"newText": "from winreg import REG_NOTIFY_CHANGE_LAST_SET\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "REG_NOTIFY_CHANGE_LAST_SET", "kind": 21, "label": "REG_NOTIFY_CHANGE_LAST_SET (import winreg)", "sortText": "700"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_tf_utils import TFCausalLanguageModelingLoss\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TFCausalLanguageModelingLoss", "kind": 7, "label": "TFCausalLanguageModelingLoss (import transformers.modeling_tf_utils)", "sortText": "701"}, {"additionalTextEdits": [{"newText": "from transformers.commands.serving import TransformersCompletionCreateParamsStreaming\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "TransformersCompletionCreateParamsStreaming", "kind": 7, "label": "TransformersCompletionCreateParamsStreaming (import transformers.commands.serving)", "sortText": "702"}, {"additionalTextEdits": [{"newText": "from codecs import backslashreplace_errors\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "backslashreplace_errors", "kind": 3, "label": "backslashreplace_errors (import codecs)", "sortText": "703"}, {"additionalTextEdits": [{"newText": "from huggingface_hub import cancel_access_request\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "cancel_access_request", "kind": 6, "label": "cancel_access_request (import huggingface_hub)", "sortText": "704"}, {"additionalTextEdits": [{"newText": "from transformers.utils.import_utils import check_torch_load_is_safe\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "check_torch_load_is_safe", "kind": 3, "label": "check_torch_load_is_safe (import transformers.utils.import_utils)", "sortText": "705"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angle_atoms_for_res\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angle_atoms_for_res", "kind": 6, "label": "chi_angle_atoms_for_res (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "706"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_list\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_list", "kind": 6, "label": "chi_angles_atom_indices_list (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "707"}, {"additionalTextEdits": [{"newText": "from transformers.models.esm.openfold_utils.residue_constants import chi_angles_atom_indices_ours\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "chi_angles_atom_indices_ours", "kind": 6, "label": "chi_angles_atom_indices_ours (import transformers.models.esm.openfold_utils.residue_constants)", "sortText": "708"}, {"additionalTextEdits": [{"newText": "from transformers.pipelines import clean_custom_task\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clean_custom_task", "kind": 3, "label": "clean_custom_task (import transformers.pipelines)", "sortText": "709"}, {"additionalTextEdits": [{"newText": "from turtle import clearstamps\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "clearstamps", "kind": 3, "label": "clearstamps (import turtle)", "sortText": "710"}, {"additionalTextEdits": [{"newText": "from ipaddress import collapse_addresses\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "collapse_addresses", "kind": 3, "label": "collapse_addresses (import ipaddress)", "sortText": "711"}, {"additionalTextEdits": [{"newText": "from transformers.onnx.utils import compute_serialized_parameters_size\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "compute_serialized_parameters_size", "kind": 3, "label": "compute_serialized_parameters_size (import transformers.onnx.utils)", "sortText": "712"}, {"additionalTextEdits": [{"newText": "from transformers.integrations.tensor_parallel import convert_local_tensor_to_dtensor\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "convert_local_tensor_to_dtensor", "kind": 3, "label": "convert_local_tensor_to_dtensor (import transformers.integrations.tensor_parallel)", "sortText": "713"}, {"additionalTextEdits": [{"newText": "from packaging.tags import create_compatible_tags_selector\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_compatible_tags_selector", "kind": 3, "label": "create_compatible_tags_selector (import packaging.tags)", "sortText": "714"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import create_sliding_window_causal_mask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "create_sliding_window_causal_mask", "kind": 3, "label": "create_sliding_window_causal_mask (import transformers.masking_utils)", "sortText": "715"}, {"additionalTextEdits": [{"newText": "import encodings.aliases\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "encodings.aliases", "kind": 9, "label": "encodings.aliases (import encodings.aliases)", "sortText": "716"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.asyn_wrapper\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.asyn_wrapper", "kind": 9, "label": "fsspec.implementations.asyn_wrapper (import fsspec.implementations.asyn_wrapper)", "sortText": "717"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dask\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dask", "kind": 9, "label": "fsspec.implementations.dask (import fsspec.implementations.dask)", "sortText": "718"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dbfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dbfs", "kind": 9, "label": "fsspec.implementations.dbfs (import fsspec.implementations.dbfs)", "sortText": "719"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.dirfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.dirfs", "kind": 9, "label": "fsspec.implementations.dirfs (import fsspec.implementations.dirfs)", "sortText": "720"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.gist\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.gist", "kind": 9, "label": "fsspec.implementations.gist (import fsspec.implementations.gist)", "sortText": "721"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.http_sync\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.http_sync", "kind": 9, "label": "fsspec.implementations.http_sync (import fsspec.implementations.http_sync)", "sortText": "722"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.sftp\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.sftp", "kind": 9, "label": "fsspec.implementations.sftp (import fsspec.implementations.sftp)", "sortText": "723"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.smb\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.smb", "kind": 9, "label": "fsspec.implementations.smb (import fsspec.implementations.smb)", "sortText": "724"}, {"additionalTextEdits": [{"newText": "import fsspec.implementations.webhdfs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "fsspec.implementations.webhdfs", "kind": 9, "label": "fsspec.implementations.webhdfs (import fsspec.implementations.webhdfs)", "sortText": "725"}, {"additionalTextEdits": [{"newText": "import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer", "kind": 9, "label": "transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer (import transformers.models.audio_spectrogram_transformer.modeling_audio_spectrogram_transformer)", "sortText": "726"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon (import transformers.models.chameleon.image_processing_chameleon)", "sortText": "727"}, {"additionalTextEdits": [{"newText": "import transformers.models.chameleon.image_processing_chameleon_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chameleon.image_processing_chameleon_fast", "kind": 9, "label": "transformers.models.chameleon.image_processing_chameleon_fast (import transformers.models.chameleon.image_processing_chameleon_fast)", "sortText": "728"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip (import transformers.models.chinese_clip.image_processing_chinese_clip)", "sortText": "729"}, {"additionalTextEdits": [{"newText": "import transformers.models.chinese_clip.image_processing_chinese_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.chinese_clip.image_processing_chinese_clip_fast", "kind": 9, "label": "transformers.models.chinese_clip.image_processing_chinese_clip_fast (import transformers.models.chinese_clip.image_processing_chinese_clip_fast)", "sortText": "730"}, {"additionalTextEdits": [{"newText": "import transformers.models.clap.processing_clap\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clap.processing_clap", "kind": 9, "label": "transformers.models.clap.processing_clap (import transformers.models.clap.processing_clap)", "sortText": "731"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip", "kind": 9, "label": "transformers.models.clip.image_processing_clip (import transformers.models.clip.image_processing_clip)", "sortText": "732"}, {"additionalTextEdits": [{"newText": "import transformers.models.clip.image_processing_clip_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.clip.image_processing_clip_fast", "kind": 9, "label": "transformers.models.clip.image_processing_clip_fast (import transformers.models.clip.image_processing_clip_fast)", "sortText": "733"}, {"additionalTextEdits": [{"newText": "import transformers.models.colpali.processing_colpali\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.colpali.processing_colpali", "kind": 9, "label": "transformers.models.colpali.processing_colpali (import transformers.models.colpali.processing_colpali)", "sortText": "734"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr (import transformers.models.conditional_detr.image_processing_conditional_detr)", "sortText": "735"}, {"additionalTextEdits": [{"newText": "import transformers.models.conditional_detr.image_processing_conditional_detr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.conditional_detr.image_processing_conditional_detr_fast", "kind": 9, "label": "transformers.models.conditional_detr.image_processing_conditional_detr_fast (import transformers.models.conditional_detr.image_processing_conditional_detr_fast)", "sortText": "736"}, {"additionalTextEdits": [{"newText": "import transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities", "kind": 9, "label": "transformers.models.deprecated.transfo_xl.modeling_tf_transfo_xl_utilities (import 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transformers.models.deprecated.tvlt.image_processing_tvlt)", "sortText": "739"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr (import transformers.models.efficientloftr.image_processing_efficientloftr)", "sortText": "740"}, {"additionalTextEdits": [{"newText": "import transformers.models.efficientloftr.image_processing_efficientloftr_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.efficientloftr.image_processing_efficientloftr_fast", "kind": 9, "label": "transformers.models.efficientloftr.image_processing_efficientloftr_fast (import transformers.models.efficientloftr.image_processing_efficientloftr_fast)", "sortText": "741"}, {"additionalTextEdits": [{"newText": "import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer", "kind": 9, "label": "transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer (import transformers.models.fastspeech2_conformer.modeling_fastspeech2_conformer)", "sortText": "742"}, {"additionalTextEdits": [{"newText": "import transformers.models.instructblipvideo.image_processing_instructblipvideo\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.instructblipvideo.image_processing_instructblipvideo", "kind": 9, "label": "transformers.models.instructblipvideo.image_processing_instructblipvideo (import transformers.models.instructblipvideo.image_processing_instructblipvideo)", "sortText": "743"}, {"additionalTextEdits": [{"newText": "import transformers.models.llava_onevision.image_processing_llava_onevision_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.llava_onevision.image_processing_llava_onevision_fast", "kind": 9, "label": "transformers.models.llava_onevision.image_processing_llava_onevision_fast (import transformers.models.llava_onevision.image_processing_llava_onevision_fast)", "sortText": "744"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.configuration_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.configuration_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.configuration_longcat_flash (import transformers.models.longcat_flash.configuration_longcat_flash)", "sortText": "745"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modeling_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modeling_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modeling_longcat_flash (import transformers.models.longcat_flash.modeling_longcat_flash)", "sortText": "746"}, {"additionalTextEdits": [{"newText": "import transformers.models.longcat_flash.modular_longcat_flash\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.longcat_flash.modular_longcat_flash", "kind": 9, "label": "transformers.models.longcat_flash.modular_longcat_flash (import transformers.models.longcat_flash.modular_longcat_flash)", "sortText": "747"}, {"additionalTextEdits": [{"newText": "import transformers.models.perception_lm.image_processing_perception_lm_fast\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.perception_lm.image_processing_perception_lm_fast", "kind": 9, "label": "transformers.models.perception_lm.image_processing_perception_lm_fast (import transformers.models.perception_lm.image_processing_perception_lm_fast)", "sortText": "748"}, {"additionalTextEdits": [{"newText": "import transformers.models.switch_transformers.modeling_switch_transformers\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.switch_transformers.modeling_switch_transformers", "kind": 9, "label": "transformers.models.switch_transformers.modeling_switch_transformers (import transformers.models.switch_transformers.modeling_switch_transformers)", "sortText": "749"}, {"additionalTextEdits": [{"newText": "import transformers.models.unispeech_sat.modular_unispeech_sat\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "transformers.models.unispeech_sat.modular_unispeech_sat", "kind": 9, "label": "transformers.models.unispeech_sat.modular_unispeech_sat (import transformers.models.unispeech_sat.modular_unispeech_sat)", "sortText": "750"}, {"additionalTextEdits": [{"newText": "from abc import abstractclassmethod\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "abstractclassmethod", "kind": 7, "label": "abstractclassmethod (import abc)", "sortText": "751"}, {"additionalTextEdits": [{"newText": "from _typeshed import DataclassInstance\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "DataclassInstance", "kind": 7, "label": "DataclassInstance (import _typeshed)", "sortText": "752"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "753"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "754"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "755"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "756"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.tsp_semantic_tokens import _classify_type_result\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_classify_type_result", "kind": 3, "label": "_classify_type_result (import python_lsp_compare.tsp_semantic_tokens)", "sortText": "757"}, {"additionalTextEdits": [{"newText": "from python_lsp_compare.runner import _effective_validation_thresholds\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_effective_validation_thresholds", "kind": 3, "label": "_effective_validation_thresholds (import python_lsp_compare.runner)", "sortText": "758"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _AnyParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_AnyParamWindowAggregateClass", "kind": 7, "label": "_AnyParamWindowAggregateClass (import sqlite3)", "sortText": "759"}, {"additionalTextEdits": [{"newText": "from urllib3.connectionpool import _DEFAULT_QUEUE_CLASS\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_DEFAULT_QUEUE_CLASS", "kind": 21, "label": "_DEFAULT_QUEUE_CLASS (import urllib3.connectionpool)", "sortText": "760"}, {"additionalTextEdits": [{"newText": "from charset_normalizer.constant import _KNOWN_MB_CLASSES\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_KNOWN_MB_CLASSES", "kind": 21, "label": "_KNOWN_MB_CLASSES (import charset_normalizer.constant)", "sortText": "761"}, {"additionalTextEdits": [{"newText": "from unittest.runner import _ResultClassType\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ResultClassType", "kind": 6, "label": "_ResultClassType (import unittest.runner)", "sortText": "762"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _SingleParamWindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SingleParamWindowAggregateClass", "kind": 7, "label": "_SingleParamWindowAggregateClass (import sqlite3)", "sortText": "763"}, {"additionalTextEdits": [{"newText": "from unittest.loader import _SuiteClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_SuiteClass", "kind": 6, "label": "_SuiteClass (import unittest.loader)", "sortText": "764"}, {"additionalTextEdits": [{"newText": "from sqlite3 import _WindowAggregateClass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_WindowAggregateClass", "kind": 7, "label": "_WindowAggregateClass (import sqlite3)", "sortText": "765"}, {"additionalTextEdits": [{"newText": "from idna.core import _combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_combining_class", "kind": 3, "label": "_combining_class (import idna.core)", "sortText": "766"}, {"additionalTextEdits": [{"newText": "from transformers.utils.fx import _generate_supported_model_class_names\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_generate_supported_model_class_names", "kind": 3, "label": "_generate_supported_model_class_names (import transformers.utils.fx)", "sortText": "767"}, {"additionalTextEdits": [{"newText": "from huggingface_hub.hub_mixin import _load_dataclass\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_load_dataclass", "kind": 3, "label": "_load_dataclass (import huggingface_hub.hub_mixin)", "sortText": "768"}, {"additionalTextEdits": [{"newText": "from fsspec.spec import _registered_classes\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_registered_classes", "kind": 6, "label": "_registered_classes (import fsspec.spec)", "sortText": "769"}, {"additionalTextEdits": [{"newText": "from idna.core import _virama_combining_class\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_virama_combining_class", "kind": 6, "label": "_virama_combining_class (import idna.core)", "sortText": "770"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_rope_utils import _compute_linear_scaling_rope_parameters\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_compute_linear_scaling_rope_parameters", "kind": 3, "label": "_compute_linear_scaling_rope_parameters (import transformers.modeling_rope_utils)", "sortText": "771"}, {"additionalTextEdits": [{"newText": "from transformers.masking_utils import _ignore_causal_mask_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_ignore_causal_mask_sdpa", "kind": 3, "label": "_ignore_causal_mask_sdpa (import transformers.masking_utils)", "sortText": "772"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_attn_mask_utils import _prepare_4d_causal_attention_mask_for_sdpa\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_prepare_4d_causal_attention_mask_for_sdpa", "kind": 3, "label": "_prepare_4d_causal_attention_mask_for_sdpa (import transformers.modeling_attn_mask_utils)", "sortText": "773"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_attention_kwargs\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_attention_kwargs", "kind": 3, "label": "_process_flash_attention_kwargs (import transformers.modeling_flash_attention_utils)", "sortText": "774"}, {"additionalTextEdits": [{"newText": "from transformers.modeling_flash_attention_utils import _process_flash_kwargs_fn\n", "range": {"end": {"character": 0, "line": 0}, "start": {"character": 0, "line": 0}}}], "insertText": "_process_flash_kwargs_fn", "kind": 6, "label": "_process_flash_kwargs_fn (import transformers.modeling_flash_attention_utils)", "sortText": "775"}]}} {"suite": "transformers", "label": "pipeline hover", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 9, "character": 18, "iteration": 1, "result": {"contents": {"kind": "plaintext", "value": "Unknown"}, "range": {"end": {"character": 18, "line": 9}, "start": {"character": 4, "line": 9}}}} {"suite": "transformers", "label": "pipeline hover", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 9, "character": 18, "iteration": 2, "result": {"contents": {"kind": "plaintext", "value": "Unknown"}, "range": {"end": {"character": 18, "line": 9}, "start": {"character": 4, "line": 9}}}} {"suite": "transformers", "label": "pipeline hover", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/transformers/src/inference.py", "line": 9, "character": 18, "iteration": 3, "result": {"contents": {"kind": "plaintext", "value": "Unknown"}, "range": {"end": {"character": 18, "line": 9}, "start": {"character": 4, "line": 9}}}} @@ -138,13 +138,13 @@ {"suite": "web", "label": "client references", "method": "textDocument/references", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 10, "character": 17, "iteration": 3, "result": [{"range": {"end": {"character": 6, "line": 5}, "start": {"character": 0, "line": 5}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py"}, {"range": {"end": {"character": 21, "line": 10}, "start": {"character": 15, "line": 10}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py"}]} {"suite": "web", "label": "client references", "method": "textDocument/references", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 10, "character": 17, "iteration": 4, "result": [{"range": {"end": {"character": 6, "line": 5}, "start": {"character": 0, "line": 5}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py"}, {"range": {"end": {"character": 21, "line": 10}, "start": {"character": 15, "line": 10}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py"}]} {"suite": "web", "label": "client references", "method": "textDocument/references", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 10, "character": 17, "iteration": 5, "result": [{"range": {"end": {"character": 6, "line": 5}, "start": {"character": 0, "line": 5}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py"}, {"range": {"end": {"character": 21, "line": 10}, "start": {"character": 15, "line": 10}}, "uri": "file:///home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py"}]} -{"suite": "web", "label": "edit response then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 55, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "Literal[False]", "kind": 14, "label": "False", "sortText": " 0"}, {"detail": "None", "kind": 14, "label": "None", "sortText": " 1"}, {"detail": "Literal[True]", "kind": 14, "label": "True", "sortText": " 2"}, {"kind": 14, "label": "and", "sortText": " 3"}, {"kind": 14, "label": "as", "sortText": " 4"}, {"kind": 14, "label": "assert", "sortText": " 5"}, {"kind": 14, "label": "async", "sortText": " 6"}, {"kind": 14, "label": "await", "sortText": " 7"}, {"kind": 14, "label": "break", "sortText": " 8"}, {"kind": 14, "label": "case", "sortText": " 9"}, {"kind": 14, "label": "class", "sortText": " 10"}, {"kind": 14, "label": "continue", "sortText": " 11"}, {"kind": 14, "label": "def", "sortText": " 12"}, {"kind": 14, "label": "del", "sortText": " 13"}, {"kind": 14, "label": "elif", "sortText": " 14"}, {"kind": 14, "label": "else", "sortText": " 15"}, {"kind": 14, "label": "except", "sortText": " 16"}, {"kind": 14, "label": "finally", "sortText": " 17"}, {"kind": 14, "label": "for", "sortText": " 18"}, {"kind": 14, "label": "from", "sortText": " 19"}, {"kind": 14, "label": "global", "sortText": " 20"}, {"kind": 14, "label": "if", "sortText": " 21"}, {"kind": 14, "label": "import", "sortText": " 22"}, {"kind": 14, "label": "in", "sortText": " 23"}, {"kind": 14, "label": "is", "sortText": " 24"}, {"kind": 14, "label": "lambda", "sortText": " 25"}, {"kind": 14, "label": "match", "sortText": " 26"}, {"kind": 14, "label": "nonlocal", "sortText": " 27"}, {"kind": 14, "label": "not", "sortText": " 28"}, {"kind": 14, "label": "or", "sortText": " 29"}, {"kind": 14, "label": "pass", "sortText": " 30"}, {"kind": 14, "label": "raise", "sortText": " 31"}, {"kind": 14, "label": "return", "sortText": " 32"}, {"kind": 14, "label": "try", "sortText": " 33"}, {"kind": 14, "label": "while", "sortText": " 34"}, {"kind": 14, "label": "with", "sortText": " 35"}, {"kind": 14, "label": "yield", "sortText": " 36"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated 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"sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. 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It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated 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"plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated exceptions.\n"}, "kind": 7, "label": "BaseExceptionGroup", "sortText": " 47"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "I/O operation would block.\n"}, "kind": 7, "label": "BlockingIOError", "sortText": " 48"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Broken pipe.\n"}, "kind": 7, "label": "BrokenPipeError", "sortText": " 49"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Buffer error.\n"}, "kind": 7, "label": "BufferError", "sortText": " 50"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about bytes and buffer related problems, mostly\nrelated to conversion from str or comparing to str.\n"}, "kind": 7, "label": "BytesWarning", "sortText": " 51"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Child process error.\n"}, "kind": 7, "label": "ChildProcessError", "sortText": " 52"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection aborted.\n"}, "kind": 7, "label": "ConnectionAbortedError", "sortText": " 53"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection error.\n"}, "kind": 7, "label": "ConnectionError", "sortText": " 54"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection refused.\n"}, "kind": 7, "label": "ConnectionRefusedError", "sortText": " 55"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection reset.\n"}, "kind": 7, "label": "ConnectionResetError", "sortText": " 56"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about deprecated features.\n"}, "kind": 7, "label": "DeprecationWarning", "sortText": " 57"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Read beyond end of file.\n"}, "kind": 7, "label": "EOFError", "sortText": " 58"}, {"detail": "EllipsisType", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 22, "label": "Ellipsis", "sortText": " 59"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about encodings.\n"}, "kind": 7, "label": "EncodingWarning", "sortText": " 60"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "EnvironmentError", "sortText": " 61"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all non-exit exceptions.\n"}, "kind": 7, "label": "Exception", "sortText": " 62"}, {"detail": "", "kind": 7, "label": "ExceptionGroup", "sortText": " 63"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "File already exists.\n"}, "kind": 7, "label": "FileExistsError", "sortText": " 64"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "File not found.\n"}, "kind": 7, "label": "FileNotFoundError", "sortText": " 65"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Floating-point operation failed.\n"}, "kind": 7, "label": "FloatingPointError", "sortText": " 66"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about constructs that will change semantically\nin the future.\n"}, "kind": 7, "label": "FutureWarning", "sortText": " 67"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request that a generator exit.\n"}, "kind": 7, "label": "GeneratorExit", "sortText": " 68"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "IOError", "sortText": " 69"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Import can't find module, or can't find name in module.\n"}, "kind": 7, "label": "ImportError", "sortText": " 70"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about probable mistakes in module imports\n"}, "kind": 7, "label": "ImportWarning", "sortText": " 71"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper indentation.\n"}, "kind": 7, "label": "IndentationError", "sortText": " 72"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Sequence index out of range.\n"}, "kind": 7, "label": "IndexError", "sortText": " 73"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Interrupted by signal.\n"}, "kind": 7, "label": "InterruptedError", "sortText": " 74"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation doesn't work on directories.\n"}, "kind": 7, "label": "IsADirectoryError", "sortText": " 75"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Mapping key not found.\n"}, "kind": 7, "label": "KeyError", "sortText": " 76"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Program interrupted by user.\n"}, "kind": 7, "label": "KeyboardInterrupt", "sortText": " 77"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for lookup errors.\n"}, "kind": 7, "label": "LookupError", "sortText": " 78"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Out of memory.\n"}, "kind": 7, "label": "MemoryError", "sortText": " 79"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Module not found.\n"}, "kind": 7, "label": "ModuleNotFoundError", "sortText": " 80"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Name not found globally.\n"}, "kind": 7, "label": "NameError", "sortText": " 81"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation only works on directories.\n"}, "kind": 7, "label": "NotADirectoryError", "sortText": " 82"}, {"detail": "NotImplementedType", "documentation": {"kind": "plaintext", "value": "The type of the NotImplemented singleton.\n"}, "kind": 22, "label": "NotImplemented", "sortText": " 83"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Method or function hasn't been implemented yet.\n"}, "kind": 7, "label": "NotImplementedError", "sortText": " 84"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "OSError", "sortText": " 85"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Result too large to be represented.\n"}, "kind": 7, "label": "OverflowError", "sortText": " 86"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about features which will be deprecated\nin the future.\n"}, "kind": 7, "label": "PendingDeprecationWarning", "sortText": " 87"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Not enough permissions.\n"}, "kind": 7, "label": "PermissionError", "sortText": " 88"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Process not found.\n"}, "kind": 7, "label": "ProcessLookupError", "sortText": " 89"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Recursion limit exceeded.\n"}, "kind": 7, "label": "RecursionError", "sortText": " 90"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Weak ref proxy used after referent went away.\n"}, "kind": 7, "label": "ReferenceError", "sortText": " 91"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about resource usage.\n"}, "kind": 7, "label": "ResourceWarning", "sortText": " 92"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unspecified run-time error.\n"}, "kind": 7, "label": "RuntimeError", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious runtime behavior.\n"}, "kind": 7, "label": "RuntimeWarning", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__anext__().\n"}, "kind": 7, "label": "StopAsyncIteration", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. 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aborted.\n"}, "kind": 7, "label": "ConnectionAbortedError", "sortText": " 53"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection error.\n"}, "kind": 7, "label": "ConnectionError", "sortText": " 54"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection refused.\n"}, "kind": 7, "label": "ConnectionRefusedError", "sortText": " 55"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection reset.\n"}, "kind": 7, "label": "ConnectionResetError", "sortText": " 56"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about deprecated features.\n"}, "kind": 7, "label": "DeprecationWarning", "sortText": " 57"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Read beyond end of file.\n"}, "kind": 7, "label": "EOFError", "sortText": " 58"}, {"detail": "EllipsisType", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 22, "label": 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"documentation": {"kind": "plaintext", "value": "Improper indentation.\n"}, "kind": 7, "label": "IndentationError", "sortText": " 72"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Sequence index out of range.\n"}, "kind": 7, "label": "IndexError", "sortText": " 73"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Interrupted by signal.\n"}, "kind": 7, "label": "InterruptedError", "sortText": " 74"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation doesn't work on directories.\n"}, "kind": 7, "label": "IsADirectoryError", "sortText": " 75"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Mapping key not found.\n"}, "kind": 7, "label": "KeyError", "sortText": " 76"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Program interrupted by user.\n"}, "kind": 7, "label": "KeyboardInterrupt", "sortText": " 77"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for lookup 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"RecursionError", "sortText": " 90"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Weak ref proxy used after referent went away.\n"}, "kind": 7, "label": "ReferenceError", "sortText": " 91"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about resource usage.\n"}, "kind": 7, "label": "ResourceWarning", "sortText": " 92"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unspecified run-time error.\n"}, "kind": 7, "label": "RuntimeError", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious runtime behavior.\n"}, "kind": 7, "label": "RuntimeWarning", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__anext__().\n"}, "kind": 7, "label": "StopAsyncIteration", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. 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It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated 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"sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: type | UnionType | tuple[Divergent, ...], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__warningregistry__", "sortText": "224"}]}} -{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 1, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: None | float | Sequence[Divergent] | Mapping[str, Divergent] | str = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} -{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 2, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: None | float | Sequence[Divergent] | Mapping[str, Divergent] | str = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} -{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 3, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: None | float | Sequence[Divergent] | Mapping[str, Divergent] | str = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} -{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 4, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: None | float | Sequence[Divergent] | Mapping[str, Divergent] | str = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} -{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 5, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: None | float | Sequence[Divergent] | Mapping[str, Divergent] | str = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} +{"suite": "web", "label": "edit response then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 55, "iteration": 1, "result": {"isIncomplete": true, "items": [{"detail": "Literal[False]", "kind": 14, "label": "False", "sortText": " 0"}, {"detail": "None", "kind": 14, "label": "None", "sortText": " 1"}, {"detail": "Literal[True]", "kind": 14, "label": "True", "sortText": " 2"}, {"kind": 14, "label": "and", "sortText": " 3"}, {"kind": 14, "label": "as", "sortText": " 4"}, {"kind": 14, "label": "assert", "sortText": " 5"}, {"kind": 14, "label": "async", "sortText": " 6"}, {"kind": 14, "label": "await", "sortText": " 7"}, {"kind": 14, "label": "break", "sortText": " 8"}, {"kind": 14, "label": "case", "sortText": " 9"}, {"kind": 14, "label": "class", "sortText": " 10"}, {"kind": 14, "label": "continue", "sortText": " 11"}, {"kind": 14, "label": "def", "sortText": " 12"}, {"kind": 14, "label": "del", "sortText": " 13"}, {"kind": 14, "label": "elif", "sortText": " 14"}, {"kind": 14, "label": "else", "sortText": " 15"}, {"kind": 14, "label": "except", "sortText": " 16"}, {"kind": 14, "label": "finally", "sortText": " 17"}, {"kind": 14, "label": "for", "sortText": " 18"}, {"kind": 14, "label": "from", "sortText": " 19"}, {"kind": 14, "label": "global", "sortText": " 20"}, {"kind": 14, "label": "if", "sortText": " 21"}, {"kind": 14, "label": "import", "sortText": " 22"}, {"kind": 14, "label": "in", "sortText": " 23"}, {"kind": 14, "label": "is", "sortText": " 24"}, {"kind": 14, "label": "lambda", "sortText": " 25"}, {"kind": 14, "label": "match", "sortText": " 26"}, {"kind": 14, "label": "nonlocal", "sortText": " 27"}, {"kind": 14, "label": "not", "sortText": " 28"}, {"kind": 14, "label": "or", "sortText": " 29"}, {"kind": 14, "label": "pass", "sortText": " 30"}, {"kind": 14, "label": "raise", "sortText": " 31"}, {"kind": 14, "label": "return", "sortText": " 32"}, {"kind": 14, "label": "try", "sortText": " 33"}, {"kind": 14, "label": "while", "sortText": " 34"}, {"kind": 14, "label": "with", "sortText": " 35"}, {"kind": 14, "label": "yield", "sortText": " 36"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated exceptions.\n"}, "kind": 7, "label": "BaseExceptionGroup", "sortText": " 47"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "I/O operation would block.\n"}, "kind": 7, "label": "BlockingIOError", "sortText": " 48"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Broken pipe.\n"}, "kind": 7, "label": "BrokenPipeError", "sortText": " 49"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Buffer error.\n"}, "kind": 7, "label": "BufferError", "sortText": " 50"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about bytes and buffer related problems, mostly\nrelated to conversion from str or comparing to str.\n"}, "kind": 7, "label": "BytesWarning", "sortText": " 51"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Child process error.\n"}, "kind": 7, "label": "ChildProcessError", "sortText": " 52"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection aborted.\n"}, "kind": 7, "label": "ConnectionAbortedError", "sortText": " 53"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection error.\n"}, "kind": 7, "label": "ConnectionError", "sortText": " 54"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection refused.\n"}, "kind": 7, "label": "ConnectionRefusedError", "sortText": " 55"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection reset.\n"}, "kind": 7, "label": "ConnectionResetError", "sortText": " 56"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about deprecated features.\n"}, "kind": 7, "label": "DeprecationWarning", "sortText": " 57"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Read beyond end of file.\n"}, "kind": 7, "label": "EOFError", "sortText": " 58"}, {"detail": "EllipsisType", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 22, "label": "Ellipsis", "sortText": " 59"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about encodings.\n"}, "kind": 7, "label": "EncodingWarning", "sortText": " 60"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "EnvironmentError", "sortText": " 61"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all non-exit exceptions.\n"}, "kind": 7, "label": "Exception", "sortText": " 62"}, {"detail": "", "kind": 7, "label": "ExceptionGroup", "sortText": " 63"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "File already exists.\n"}, "kind": 7, "label": "FileExistsError", "sortText": " 64"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "File not found.\n"}, "kind": 7, "label": "FileNotFoundError", "sortText": " 65"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Floating-point operation failed.\n"}, "kind": 7, "label": "FloatingPointError", "sortText": " 66"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about constructs that will change semantically\nin the future.\n"}, "kind": 7, "label": "FutureWarning", "sortText": " 67"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request that a generator exit.\n"}, "kind": 7, "label": "GeneratorExit", "sortText": " 68"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "IOError", "sortText": " 69"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Import can't find module, or can't find name in module.\n"}, "kind": 7, "label": "ImportError", "sortText": " 70"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about probable mistakes in module imports\n"}, "kind": 7, "label": "ImportWarning", "sortText": " 71"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper indentation.\n"}, "kind": 7, "label": "IndentationError", "sortText": " 72"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Sequence index out of range.\n"}, "kind": 7, "label": "IndexError", "sortText": " 73"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Interrupted by signal.\n"}, "kind": 7, "label": "InterruptedError", "sortText": " 74"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation doesn't work on directories.\n"}, "kind": 7, "label": "IsADirectoryError", "sortText": " 75"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Mapping key not found.\n"}, "kind": 7, "label": "KeyError", "sortText": " 76"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Program interrupted by user.\n"}, "kind": 7, "label": "KeyboardInterrupt", "sortText": " 77"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for lookup 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iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. 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It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated 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"plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__warningregistry__", "sortText": "224"}]}} +{"suite": "web", "label": "edit response then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 55, "iteration": 3, "result": {"isIncomplete": true, "items": [{"detail": "Literal[False]", "kind": 14, "label": "False", "sortText": " 0"}, {"detail": "None", "kind": 14, "label": "None", "sortText": " 1"}, {"detail": "Literal[True]", "kind": 14, "label": "True", "sortText": " 2"}, {"kind": 14, "label": "and", "sortText": " 3"}, {"kind": 14, "label": "as", "sortText": " 4"}, {"kind": 14, "label": "assert", "sortText": " 5"}, {"kind": 14, "label": "async", "sortText": " 6"}, {"kind": 14, "label": "await", "sortText": " 7"}, {"kind": 14, "label": "break", "sortText": " 8"}, {"kind": 14, "label": "case", "sortText": " 9"}, {"kind": 14, "label": "class", "sortText": " 10"}, {"kind": 14, "label": "continue", "sortText": " 11"}, {"kind": 14, "label": "def", "sortText": " 12"}, {"kind": 14, "label": "del", "sortText": " 13"}, {"kind": 14, "label": "elif", "sortText": " 14"}, {"kind": 14, "label": "else", "sortText": " 15"}, {"kind": 14, "label": "except", "sortText": " 16"}, {"kind": 14, "label": "finally", "sortText": " 17"}, {"kind": 14, "label": "for", "sortText": " 18"}, {"kind": 14, "label": "from", "sortText": " 19"}, {"kind": 14, "label": "global", "sortText": " 20"}, {"kind": 14, "label": "if", "sortText": " 21"}, {"kind": 14, "label": "import", "sortText": " 22"}, {"kind": 14, "label": "in", "sortText": " 23"}, {"kind": 14, "label": "is", "sortText": " 24"}, {"kind": 14, "label": "lambda", "sortText": " 25"}, {"kind": 14, "label": "match", "sortText": " 26"}, {"kind": 14, "label": "nonlocal", "sortText": " 27"}, {"kind": 14, "label": "not", "sortText": " 28"}, {"kind": 14, "label": "or", "sortText": " 29"}, {"kind": 14, "label": "pass", "sortText": " 30"}, {"kind": 14, "label": "raise", "sortText": " 31"}, {"kind": 14, "label": "return", "sortText": " 32"}, {"kind": 14, "label": "try", "sortText": " 33"}, {"kind": 14, "label": "while", "sortText": " 34"}, {"kind": 14, "label": "with", "sortText": " 35"}, {"kind": 14, "label": "yield", "sortText": " 36"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated exceptions.\n"}, "kind": 7, "label": "BaseExceptionGroup", "sortText": " 47"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "I/O operation would block.\n"}, "kind": 7, "label": "BlockingIOError", "sortText": " 48"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Broken pipe.\n"}, "kind": 7, "label": "BrokenPipeError", "sortText": " 49"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Buffer error.\n"}, "kind": 7, "label": "BufferError", "sortText": " 50"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about bytes and buffer related problems, mostly\nrelated to conversion from str or comparing to str.\n"}, "kind": 7, "label": "BytesWarning", "sortText": " 51"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Child process error.\n"}, "kind": 7, "label": "ChildProcessError", "sortText": " 52"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection aborted.\n"}, "kind": 7, "label": "ConnectionAbortedError", "sortText": " 53"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection error.\n"}, "kind": 7, "label": "ConnectionError", "sortText": " 54"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection refused.\n"}, "kind": 7, "label": "ConnectionRefusedError", "sortText": " 55"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection reset.\n"}, "kind": 7, "label": "ConnectionResetError", "sortText": " 56"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about deprecated features.\n"}, "kind": 7, "label": "DeprecationWarning", "sortText": " 57"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Read beyond end of file.\n"}, "kind": 7, "label": "EOFError", "sortText": " 58"}, {"detail": "EllipsisType", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 22, "label": "Ellipsis", "sortText": " 59"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about encodings.\n"}, "kind": 7, "label": "EncodingWarning", "sortText": " 60"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "EnvironmentError", "sortText": " 61"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all non-exit exceptions.\n"}, "kind": 7, "label": "Exception", "sortText": " 62"}, {"detail": "", "kind": 7, "label": "ExceptionGroup", "sortText": " 63"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "File already exists.\n"}, "kind": 7, "label": "FileExistsError", "sortText": " 64"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "File not found.\n"}, "kind": 7, "label": "FileNotFoundError", "sortText": " 65"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Floating-point operation failed.\n"}, "kind": 7, "label": "FloatingPointError", "sortText": " 66"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about constructs that will change semantically\nin the future.\n"}, "kind": 7, "label": "FutureWarning", "sortText": " 67"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request that a generator exit.\n"}, "kind": 7, "label": "GeneratorExit", "sortText": " 68"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "IOError", "sortText": " 69"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Import can't find module, or can't find name in module.\n"}, "kind": 7, "label": "ImportError", "sortText": " 70"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about probable mistakes in module imports\n"}, "kind": 7, "label": "ImportWarning", "sortText": " 71"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper indentation.\n"}, "kind": 7, "label": "IndentationError", "sortText": " 72"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Sequence index out of range.\n"}, "kind": 7, "label": "IndexError", "sortText": " 73"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Interrupted by signal.\n"}, "kind": 7, "label": "InterruptedError", "sortText": " 74"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation doesn't work on directories.\n"}, "kind": 7, "label": "IsADirectoryError", "sortText": " 75"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Mapping key not found.\n"}, "kind": 7, "label": "KeyError", "sortText": " 76"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Program interrupted by user.\n"}, "kind": 7, "label": "KeyboardInterrupt", "sortText": " 77"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for lookup errors.\n"}, "kind": 7, "label": "LookupError", "sortText": " 78"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Out of memory.\n"}, "kind": 7, "label": "MemoryError", "sortText": " 79"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Module not found.\n"}, "kind": 7, "label": "ModuleNotFoundError", "sortText": " 80"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Name not found globally.\n"}, "kind": 7, "label": "NameError", "sortText": " 81"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation only works on directories.\n"}, "kind": 7, "label": "NotADirectoryError", "sortText": " 82"}, {"detail": "NotImplementedType", "documentation": {"kind": "plaintext", "value": "The type of the NotImplemented singleton.\n"}, "kind": 22, "label": "NotImplemented", "sortText": " 83"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Method or function hasn't been implemented yet.\n"}, "kind": 7, "label": "NotImplementedError", "sortText": " 84"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for I/O related errors.\n"}, "kind": 7, "label": "OSError", "sortText": " 85"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Result too large to be represented.\n"}, "kind": 7, "label": "OverflowError", "sortText": " 86"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about features which will be deprecated\nin the future.\n"}, "kind": 7, "label": "PendingDeprecationWarning", "sortText": " 87"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Not enough permissions.\n"}, "kind": 7, "label": "PermissionError", "sortText": " 88"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Process not found.\n"}, "kind": 7, "label": "ProcessLookupError", "sortText": " 89"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Recursion limit exceeded.\n"}, "kind": 7, "label": "RecursionError", "sortText": " 90"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Weak ref proxy used after referent went away.\n"}, "kind": 7, "label": "ReferenceError", "sortText": " 91"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about resource usage.\n"}, "kind": 7, "label": "ResourceWarning", "sortText": " 92"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unspecified run-time error.\n"}, "kind": 7, "label": "RuntimeError", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious runtime behavior.\n"}, "kind": 7, "label": "RuntimeWarning", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__anext__().\n"}, "kind": 7, "label": "StopAsyncIteration", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__warningregistry__", "sortText": "224"}]}} +{"suite": "web", "label": "edit response then complete (edit+completion)", "method": "textDocument/completion", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 55, "iteration": 4, "result": {"isIncomplete": true, "items": [{"detail": "Literal[False]", "kind": 14, "label": "False", "sortText": " 0"}, {"detail": "None", "kind": 14, "label": "None", "sortText": " 1"}, {"detail": "Literal[True]", "kind": 14, "label": "True", "sortText": " 2"}, {"kind": 14, "label": "and", "sortText": " 3"}, {"kind": 14, "label": "as", "sortText": " 4"}, {"kind": 14, "label": "assert", "sortText": " 5"}, {"kind": 14, "label": "async", "sortText": " 6"}, {"kind": 14, "label": "await", "sortText": " 7"}, {"kind": 14, "label": "break", "sortText": " 8"}, {"kind": 14, "label": "case", "sortText": " 9"}, {"kind": 14, "label": "class", "sortText": " 10"}, {"kind": 14, "label": "continue", "sortText": " 11"}, {"kind": 14, "label": "def", "sortText": " 12"}, {"kind": 14, "label": "del", "sortText": " 13"}, {"kind": 14, "label": "elif", "sortText": " 14"}, {"kind": 14, "label": "else", "sortText": " 15"}, {"kind": 14, "label": "except", "sortText": " 16"}, {"kind": 14, "label": "finally", "sortText": " 17"}, {"kind": 14, "label": "for", "sortText": " 18"}, {"kind": 14, "label": "from", "sortText": " 19"}, {"kind": 14, "label": "global", "sortText": " 20"}, {"kind": 14, "label": "if", "sortText": " 21"}, {"kind": 14, "label": "import", "sortText": " 22"}, {"kind": 14, "label": "in", "sortText": " 23"}, {"kind": 14, "label": "is", "sortText": " 24"}, {"kind": 14, "label": "lambda", "sortText": " 25"}, {"kind": 14, "label": "match", "sortText": " 26"}, {"kind": 14, "label": "nonlocal", "sortText": " 27"}, {"kind": 14, "label": "not", "sortText": " 28"}, {"kind": 14, "label": "or", "sortText": " 29"}, {"kind": 14, "label": "pass", "sortText": " 30"}, {"kind": 14, "label": "raise", "sortText": " 31"}, {"kind": 14, "label": "return", "sortText": " 32"}, {"kind": 14, "label": "try", "sortText": " 33"}, {"kind": 14, "label": "while", "sortText": " 34"}, {"kind": 14, "label": "with", "sortText": " 35"}, {"kind": 14, "label": "yield", "sortText": " 36"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. 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aborted.\n"}, "kind": 7, "label": "ConnectionAbortedError", "sortText": " 53"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection error.\n"}, "kind": 7, "label": "ConnectionError", "sortText": " 54"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection refused.\n"}, "kind": 7, "label": "ConnectionRefusedError", "sortText": " 55"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Connection reset.\n"}, "kind": 7, "label": "ConnectionResetError", "sortText": " 56"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about deprecated features.\n"}, "kind": 7, "label": "DeprecationWarning", "sortText": " 57"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Read beyond end of file.\n"}, "kind": 7, "label": "EOFError", "sortText": " 58"}, {"detail": "EllipsisType", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 22, "label": 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"documentation": {"kind": "plaintext", "value": "Improper indentation.\n"}, "kind": 7, "label": "IndentationError", "sortText": " 72"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Sequence index out of range.\n"}, "kind": 7, "label": "IndexError", "sortText": " 73"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Interrupted by signal.\n"}, "kind": 7, "label": "InterruptedError", "sortText": " 74"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Operation doesn't work on directories.\n"}, "kind": 7, "label": "IsADirectoryError", "sortText": " 75"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Mapping key not found.\n"}, "kind": 7, "label": "KeyError", "sortText": " 76"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Program interrupted by user.\n"}, "kind": 7, "label": "KeyboardInterrupt", "sortText": " 77"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for lookup 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"RecursionError", "sortText": " 90"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Weak ref proxy used after referent went away.\n"}, "kind": 7, "label": "ReferenceError", "sortText": " 91"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about resource usage.\n"}, "kind": 7, "label": "ResourceWarning", "sortText": " 92"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unspecified run-time error.\n"}, "kind": 7, "label": "RuntimeError", "sortText": " 93"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious runtime behavior.\n"}, "kind": 7, "label": "RuntimeWarning", "sortText": " 94"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__anext__().\n"}, "kind": 7, "label": "StopAsyncIteration", "sortText": " 95"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Signal the end from iterator.__next__().\n"}, "kind": 7, "label": "StopIteration", "sortText": " 96"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Invalid syntax.\n"}, "kind": 7, "label": "SyntaxError", "sortText": " 97"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about dubious syntax.\n"}, "kind": 7, "label": "SyntaxWarning", "sortText": " 98"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Internal error in the Python interpreter.\n\nPlease report this to the Python maintainer, along with the traceback,\nthe Python version, and the hardware/OS platform and version.\n"}, "kind": 7, "label": "SystemError", "sortText": " 99"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Request to exit from the interpreter.\n"}, "kind": 7, "label": "SystemExit", "sortText": "100"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Improper mixture of spaces and tabs.\n"}, "kind": 7, "label": "TabError", "sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. 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It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 7, "label": "Flask", "sortText": " 37"}, {"detail": "Flask", "documentation": {"kind": "plaintext", "value": "The flask object implements a WSGI application and acts as the central\nobject. It is passed the name of the module or package of the\napplication. Once it is created it will act as a central registry for\nthe view functions, the URL rules, template configuration and much more.\n\nThe name of the package is used to resolve resources from inside the\npackage or the folder the module is contained in depending on if the\npackage parameter resolves to an actual python package (a folder with\nan :file:`__init__.py` file inside) or a standard module (just a ``.py`` file).\n\nFor more information about resource loading, see :func:`open_resource`.\n\nUsually you create a :class:`Flask` instance in your main module or\nin the :file:`__init__.py` file of your package like this::\n\n from flask import Flask\n app = Flask(__name__)\n\n.. admonition:: About the First Parameter\n\n The idea of the first parameter is to give Flask an idea of what\n belongs to your application. This name is used to find resources\n on the filesystem, can be used by extensions to improve debugging\n information and a lot more.\n\n So it's important what you provide there. If you are using a single\n module, `__name__` is always the correct value. If you however are\n using a package, it's usually recommended to hardcode the name of\n your package there.\n\n For example if your application is defined in :file:`yourapplication/app.py`\n you should create it with one of the two versions below::\n\n app = Flask('yourapplication')\n app = Flask(__name__.split('.')[0])\n\n Why is that? The application will work even with `__name__`, thanks\n to how resources are looked up. However it will make debugging more\n painful. Certain extensions can make assumptions based on the\n import name of your application. For example the Flask-SQLAlchemy\n extension will look for the code in your application that triggered\n an SQL query in debug mode. If the import name is not properly set\n up, that debugging information is lost. (For example it would only\n pick up SQL queries in `yourapplication.app` and not\n `yourapplication.views.frontend`)\n\n.. versionadded:: 0.7\n The `static_url_path`, `static_folder`, and `template_folder`\n parameters were added.\n\n.. versionadded:: 0.8\n The `instance_path` and `instance_relative_config` parameters were\n added.\n\n.. versionadded:: 0.11\n The `root_path` parameter was added.\n\n.. versionadded:: 1.0\n The ``host_matching`` and ``static_host`` parameters were added.\n\n.. versionadded:: 1.0\n The ``subdomain_matching`` parameter was added. Subdomain\n matching needs to be enabled manually now. Setting\n :data:`SERVER_NAME` does not implicitly enable it.\n\n:param import_name: the name of the application package\n:param static_url_path: can be used to specify a different path for the\n static files on the web. Defaults to the name\n of the `static_folder` folder.\n:param static_folder: The folder with static files that is served at\n ``static_url_path``. Relative to the application ``root_path``\n or an absolute path. Defaults to ``'static'``.\n:param static_host: the host to use when adding the static route.\n Defaults to None. Required when using ``host_matching=True``\n with a ``static_folder`` configured.\n:param host_matching: set ``url_map.host_matching`` attribute.\n Defaults to False.\n:param subdomain_matching: consider the subdomain relative to\n :data:`SERVER_NAME` when matching routes. Defaults to False.\n:param template_folder: the folder that contains the templates that should\n be used by the application. Defaults to\n ``'templates'`` folder in the root path of the\n application.\n:param instance_path: An alternative instance path for the application.\n By default the folder ``'instance'`` next to the\n package or module is assumed to be the instance\n path.\n:param instance_relative_config: if set to ``True`` relative filenames\n for loading the config are assumed to\n be relative to the instance path instead\n of the application root.\n:param root_path: The path to the root of the application files.\n This should only be set manually when it can't be detected\n automatically, such as for namespace packages.\n"}, "kind": 22, "label": "app", "sortText": " 38"}, {"detail": "Session", "documentation": {"kind": "plaintext", "value": "A Requests session.\n\nProvides cookie persistence, connection-pooling, and configuration.\n\nBasic Usage::\n\n >>> import requests\n >>> s = requests.Session()\n >>> s.get('https://httpbin.org/get')\n \n\nOr as a context manager::\n\n >>> with requests.Session() as s:\n ... s.get('https://httpbin.org/get')\n \n"}, "kind": 22, "label": "client", "sortText": " 39"}, {"detail": "Request", "documentation": {"kind": "plaintext", "value": "The request object used by default in Flask. Remembers the\nmatched endpoint and view arguments.\n\nIt is what ends up as :class:`~flask.request`. If you want to replace\nthe request object used you can subclass this and set\n:attr:`~flask.Flask.request_class` to your subclass.\n\nThe request object is a :class:`~werkzeug.wrappers.Request` subclass and\nprovides all of the attributes Werkzeug defines plus a few Flask\nspecific ones.\n"}, "kind": 22, "label": "request", "sortText": " 40"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Requests HTTP Library\n~~~~~~~~~~~~~~~~~~~~~\n\nRequests is an HTTP library, written in Python, for human beings.\nBasic GET usage:\n\n >>> import requests\n >>> r = requests.get('https://www.python.org')\n >>> r.status_code\n 200\n >>> b'Python is a programming language' in r.content\n True\n\n... or POST:\n\n >>> payload = dict(key1='value1', key2='value2')\n >>> r = requests.post('https://httpbin.org/post', data=payload)\n >>> print(r.text)\n {\n ...\n \"form\": {\n \"key1\": \"value1\",\n \"key2\": \"value2\"\n },\n ...\n }\n\nThe other HTTP methods are supported - see `requests.api`. Full documentation\nis at .\n\n:copyright: (c) 2017 by Kenneth Reitz.\n:license: Apache 2.0, see LICENSE for more details.\n"}, "kind": 9, "label": "requests", "sortText": " 41"}, {"detail": "def users() -> dict[str, object]", "kind": 3, "label": "users", "sortText": " 42"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for arithmetic errors.\n"}, "kind": 7, "label": "ArithmeticError", "sortText": " 43"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Assertion failed.\n"}, "kind": 7, "label": "AssertionError", "sortText": " 44"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Attribute not found.\n"}, "kind": 7, "label": "AttributeError", "sortText": " 45"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Common base class for all exceptions\n"}, "kind": 7, "label": "BaseException", "sortText": " 46"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "A combination of multiple unrelated 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"sortText": "101"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Timeout expired.\n"}, "kind": 7, "label": "TimeoutError", "sortText": "102"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument type.\n"}, "kind": 7, "label": "TypeError", "sortText": "103"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Local name referenced but not bound to a value.\n"}, "kind": 7, "label": "UnboundLocalError", "sortText": "104"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode decoding error.\n"}, "kind": 7, "label": "UnicodeDecodeError", "sortText": "105"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode encoding error.\n"}, "kind": 7, "label": "UnicodeEncodeError", "sortText": "106"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode related error.\n"}, "kind": 7, "label": "UnicodeError", "sortText": "107"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Unicode translation error.\n"}, "kind": 7, "label": "UnicodeTranslateError", "sortText": "108"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings about Unicode related problems, mostly\nrelated to conversion problems.\n"}, "kind": 7, "label": "UnicodeWarning", "sortText": "109"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warnings generated by user code.\n"}, "kind": 7, "label": "UserWarning", "sortText": "110"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Inappropriate argument value (of correct type).\n"}, "kind": 7, "label": "ValueError", "sortText": "111"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Base class for warning categories.\n"}, "kind": 7, "label": "Warning", "sortText": "112"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Second argument to a division or modulo operation was zero.\n"}, "kind": 7, "label": "ZeroDivisionError", "sortText": "113"}, {"detail": "def abs[_T](x: SupportsAbs[_T], /) -> _T", "documentation": {"kind": "plaintext", "value": "Return the absolute value of the argument.\n"}, "kind": 3, "label": "abs", "sortText": "114"}, {"detail": "def aiter[_SupportsAnextT_co](async_iterable: SupportsAiter[_SupportsAnextT_co], /) -> _SupportsAnextT_co", "documentation": {"kind": "plaintext", "value": "Return an AsyncIterator for an AsyncIterable object.\n"}, "kind": 3, "label": "aiter", "sortText": "115"}, {"detail": "def all(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for all values x in the iterable.\n\nIf the iterable is empty, return True.\n"}, "kind": 3, "label": "all", "sortText": "116"}, {"detail": "Overload[[_AwaitableT](i: _SupportsSynchronousAnext[_AwaitableT], /) -> _AwaitableT, [_T, _VT](i: SupportsAnext[_T], default: _VT, /) -> CoroutineType[Any, Any, _T | _VT]]", "kind": 3, "label": "anext", "sortText": "117"}, {"detail": "def any(iterable: Iterable[object], /) -> bool", "documentation": {"kind": "plaintext", "value": "Return True if bool(x) is True for any x in the iterable.\n\nIf the iterable is empty, return False.\n"}, "kind": 3, "label": "any", "sortText": "118"}, {"detail": "def ascii(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return an ASCII-only representation of an object.\n\nAs repr(), return a string containing a printable representation of an\nobject, but escape the non-ASCII characters in the string returned by\nrepr() using \\\\x, \\\\u or \\\\U escapes. This generates a string similar\nto that returned by repr() in Python 2.\n"}, "kind": 3, "label": "ascii", "sortText": "119"}, {"detail": "def bin(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the binary representation of an integer.\n\n>>> bin(2796202)\n'0b1010101010101010101010'\n"}, "kind": 3, "label": "bin", "sortText": "120"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 7, "label": "bool", "sortText": "121"}, {"detail": "def breakpoint(...) -> None", "documentation": {"kind": "plaintext", "value": "Call sys.breakpointhook(*args, **kws). sys.breakpointhook() must accept\nwhatever arguments are passed.\n\nBy default, this drops you into the pdb debugger.\n"}, "kind": 3, "label": "breakpoint", "sortText": "122"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytearray(iterable_of_ints) -> bytearray\nbytearray(string, encoding[, errors]) -> bytearray\nbytearray(bytes_or_buffer) -> mutable copy of bytes_or_buffer\nbytearray(int) -> bytes array of size given by the parameter initialized with null bytes\nbytearray() -> empty bytes array\n\nConstruct a mutable bytearray object from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - a bytes or a buffer object\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytearray", "sortText": "123"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "bytes(iterable_of_ints) -> bytes\nbytes(string, encoding[, errors]) -> bytes\nbytes(bytes_or_buffer) -> immutable copy of bytes_or_buffer\nbytes(int) -> bytes object of size given by the parameter initialized with null bytes\nbytes() -> empty bytes object\n\nConstruct an immutable array of bytes from:\n - an iterable yielding integers in range(256)\n - a text string encoded using the specified encoding\n - any object implementing the buffer API.\n - an integer\n"}, "kind": 7, "label": "bytes", "sortText": "124"}, {"detail": "def callable(obj: object, /) -> TypeIs[(...) -> object]", "documentation": {"kind": "plaintext", "value": "Return whether the object is callable (i.e., some kind of function).\n\nNote that classes are callable, as are instances of classes with a\n__call__() method.\n"}, "kind": 3, "label": "callable", "sortText": "125"}, {"detail": "def chr(i: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return a Unicode string of one character with ordinal i; 0 <= i <= 0x10ffff.\n"}, "kind": 3, "label": "chr", "sortText": "126"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a class method.\n\nA class method receives the class as implicit first argument,\njust like an instance method receives the instance.\nTo declare a class method, use this idiom:\n\n class C:\n @classmethod\n def f(cls, arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). The instance is ignored except for its class.\nIf a class method is called for a derived class, the derived class\nobject is passed as the implied first argument.\n\nClass methods are different than C++ or Java static methods.\nIf you want those, see the staticmethod builtin.\n"}, "kind": 7, "label": "classmethod", "sortText": "127"}, {"detail": "Overload[(source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[0], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, *, dont_inherit: bool = False, optimize: int = -1, _feature_version: int = -1) -> CodeType, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: Literal[1024], dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> AST, (source: str | Buffer | Module | Expression | Interactive, filename: str | bytes | PathLike[Any], mode: str, flags: int, dont_inherit: bool = False, optimize: int = -1, *, _feature_version: int = -1) -> Any]", "kind": 3, "label": "compile", "sortText": "128"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a complex number from a string or numbers.\n\nIf a string is given, parse it as a complex number.\nIf a single number is given, convert it to a complex number.\nIf the 'real' or 'imag' arguments are given, create a complex number\nwith the specified real and imaginary components.\n"}, "kind": 7, "label": "complex", "sortText": "129"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "copyright", "sortText": "130"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "credits", "sortText": "131"}, {"detail": "def delattr(obj: object, name: str, /) -> None", "documentation": {"kind": "plaintext", "value": "Deletes the named attribute from the given object.\n\ndelattr(x, 'y') is equivalent to ``del x.y``\n"}, "kind": 3, "label": "delattr", "sortText": "132"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 7, "label": "dict", "sortText": "133"}, {"detail": "def dir(o: object = ..., /) -> list[str]", "documentation": {"kind": "plaintext", "value": "dir([object]) -> list of strings\n\nIf called without an argument, return the names in the current scope.\nElse, return an alphabetized list of names comprising (some of) the\nattributes of the given object, and of attributes reachable from it.\nIf the object supplies a method named __dir__, it will be used;\notherwise the default dir() logic is used and returns:\n for a module object: the module's attributes.\n for a class object: its attributes, and recursively the attributes\n of its bases.\n for any other object: its attributes, its class's attributes, and\n recursively the attributes of its class's base classes.\n"}, "kind": 3, "label": "dir", "sortText": "134"}, {"detail": "Overload[[_T_contra, _T_co](x: SupportsDivMod[_T_contra, _T_co], y: _T_contra, /) -> _T_co, [_T_contra, _T_co](x: _T_contra, y: SupportsRDivMod[_T_contra, _T_co], /) -> _T_co]", "kind": 3, "label": "divmod", "sortText": "135"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The type of the Ellipsis singleton.\n"}, "kind": 7, "label": "ellipsis", "sortText": "136"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an enumerate object.\n\n iterable\n an object supporting iteration\n\nThe enumerate object yields pairs containing a count (from start, which\ndefaults to zero) and a value yielded by the iterable argument.\n\nenumerate is useful for obtaining an indexed list:\n (0, seq[0]), (1, seq[1]), (2, seq[2]), ...\n"}, "kind": 7, "label": "enumerate", "sortText": "137"}, {"detail": "def eval(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /) -> Any", "documentation": {"kind": "plaintext", "value": "Evaluate the given source in the context of globals and locals.\n\nThe source may be a string representing a Python expression\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\n"}, "kind": 3, "label": "eval", "sortText": "138"}, {"detail": "def exec(source: str | Buffer | CodeType, globals: dict[str, Any] | None = None, locals: Mapping[str, object] | None = None, /, *, closure: tuple[CellType, ...] | None = None) -> None", "documentation": {"kind": "plaintext", "value": "Execute the given source in the context of globals and locals.\n\nThe source may be a string representing one or more Python statements\nor a code object as returned by compile().\nThe globals must be a dictionary and locals can be any mapping,\ndefaulting to the current globals and locals.\nIf only globals is given, locals defaults to it.\nThe closure must be a tuple of cellvars, and can only be used\nwhen source is a code object requiring exactly that many cellvars.\n"}, "kind": 3, "label": "exec", "sortText": "139"}, {"detail": "Quitter", "kind": 22, "label": "exit", "sortText": "140"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return an iterator yielding those items of iterable for which\nfunction(item) is true. If function is None, return the items that\nare true.\n"}, "kind": 7, "label": "filter", "sortText": "141"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a string or number to a floating-point number, if possible.\n"}, "kind": 7, "label": "float", "sortText": "142"}, {"detail": "def format(value: object, format_spec: str = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Return type(value).__format__(value, format_spec)\n\nMany built-in types implement format_spec according to the\nFormat Specification Mini-language. See help('FORMATTING').\n\nIf type(value) does not supply a method named __format__\nand format_spec is empty, then str(value) is returned.\nSee also help('SPECIALMETHODS').\n"}, "kind": 3, "label": "format", "sortText": "143"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an immutable unordered collection of unique elements.\n"}, "kind": 7, "label": "frozenset", "sortText": "144"}, {"detail": "Overload[(o: object, name: str, /) -> Any, (o: object, name: str, default: None, /) -> Any | None, (o: object, name: str, default: bool, /) -> Any | bool, (o: object, name: str, default: list[Any], /) -> Any | list[Any], (o: object, name: str, default: dict[Any, Any], /) -> Any | dict[Any, Any], [_T](o: object, name: str, default: _T, /) -> Any | _T]", "kind": 3, "label": "getattr", "sortText": "145"}, {"detail": "def globals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return the dictionary containing the current scope's global variables.\n\nNOTE: Updates to this dictionary *will* affect name lookups in the\ncurrent global scope and vice-versa.\n"}, "kind": 3, "label": "globals", "sortText": "146"}, {"detail": "def hasattr(obj: object, name: str, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether the object has an attribute with the given name.\n\nThis is done by calling getattr(obj, name) and catching AttributeError.\n"}, "kind": 3, "label": "hasattr", "sortText": "147"}, {"detail": "def hash(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the integer hash value for the given object.\n\nTwo objects that compare equal must also have the same hash value, but\nthe reverse is not necessarily true. Hash values may differ between\nPython processes. Not all objects are hashable; calling hash() on an\nunhashable object raises TypeError.\n"}, "kind": 3, "label": "hash", "sortText": "148"}, {"detail": "_Helper", "documentation": {"kind": "plaintext", "value": "Define the builtin 'help'.\n\nThis is a wrapper around pydoc.help that provides a helpful message\nwhen 'help' is typed at the Python interactive prompt.\n\nCalling help() at the Python prompt starts an interactive help session.\nCalling help(thing) prints help for the python object 'thing'.\n"}, "kind": 22, "label": "help", "sortText": "149"}, {"detail": "def hex(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the hexadecimal representation of an integer.\n\n>>> hex(12648430)\n'0xc0ffee'\n"}, "kind": 3, "label": "hex", "sortText": "150"}, {"detail": "def id(obj: object, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the identity of an object.\n\nThis is guaranteed to be unique among simultaneously existing objects.\n(CPython uses the object's memory address.)\n"}, "kind": 3, "label": "id", "sortText": "151"}, {"detail": "def input(prompt: object = \"\", /) -> str", "documentation": {"kind": "plaintext", "value": "Read a string from standard input. The trailing newline is stripped.\n\nThe prompt string, if given, is printed to standard output without a\ntrailing newline before reading input.\n\nIf the user hits EOF (*nix: Ctrl-D, Windows: Ctrl-Z+Return), raise\nEOFError.\nOn *nix systems, readline is used if available.\n"}, "kind": 3, "label": "input", "sortText": "152"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "int([x]) -> integer\nint(x, base=10) -> integer\n\nConvert a number or string to an integer, or return 0 if no arguments\nare given. If x is a number, return x.__int__(). For floating-point\nnumbers, this truncates towards zero.\n\nIf x is not a number or if base is given, then x must be a string,\nbytes, or bytearray instance representing an integer literal in the\ngiven base. The literal can be preceded by '+' or '-' and be surrounded\nby whitespace. The base defaults to 10. Valid bases are 0 and 2-36.\nBase 0 means to interpret the base from the string as an integer\niteral.\n>>> int('0b100', base=0)\n4\n"}, "kind": 7, "label": "int", "sortText": "153"}, {"detail": "def isinstance(obj: object, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether an object is an instance of a class or of a subclass thereof.\n\nA tuple, as in ``isinstance(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``isinstance(x, A) or\nisinstance(x, B) or ...`` etc.\n"}, "kind": 3, "label": "isinstance", "sortText": "154"}, {"detail": "def issubclass(cls: type, class_or_tuple: _ClassInfo, /) -> bool", "documentation": {"kind": "plaintext", "value": "Return whether 'cls' is derived from another class or is the same class.\n\nA tuple, as in ``issubclass(x, (A, B, ...))``, may be given as the\ntarget to check against. This is equivalent to ``issubclass(x, A) or\nissubclass(x, B) or ...``.\n"}, "kind": 3, "label": "issubclass", "sortText": "155"}, {"detail": "Overload[[_SupportsNextT_co](object: SupportsIter[_SupportsNextT_co], /) -> _SupportsNextT_co, [_T](object: _GetItemIterable[_T], /) -> Iterator[_T], [_T](object: () -> _T | None, sentinel: None, /) -> Iterator[_T], [_T](object: () -> _T, sentinel: object, /) -> Iterator[_T]]", "kind": 3, "label": "iter", "sortText": "156"}, {"detail": "def len(obj: Sized, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the number of items in a container.\n"}, "kind": 3, "label": "len", "sortText": "157"}, {"detail": "_Printer", "documentation": {"kind": "plaintext", "value": "interactive prompt objects for printing the license text, a list of\ncontributors and the copyright notice.\n"}, "kind": 22, "label": "license", "sortText": "158"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in mutable sequence.\n\nIf no argument is given, the constructor creates a new empty list.\nThe argument must be an iterable if specified.\n"}, "kind": 7, "label": "list", "sortText": "159"}, {"detail": "def locals() -> dict[str, Any]", "documentation": {"kind": "plaintext", "value": "Return a dictionary containing the current scope's local variables.\n\nNOTE: Whether or not updates to this dictionary will affect name\nlookups in the local scope and vice-versa is *implementation\ndependent* and not covered by any backwards compatibility\nguarantees.\n"}, "kind": 3, "label": "locals", "sortText": "160"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Make an iterator that computes the function using arguments from\neach of the iterables. Stops when the shortest iterable is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n"}, "kind": 7, "label": "map", "sortText": "161"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "max", "sortText": "162"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Create a new memoryview object which references the given object.\n"}, "kind": 7, "label": "memoryview", "sortText": "163"}, {"detail": "Overload[[SupportsRichComparisonT](arg1: SupportsRichComparisonT, arg2: SupportsRichComparisonT, /, *_args: SupportsRichComparisonT, key: None = None) -> SupportsRichComparisonT, [_T](arg1: _T, arg2: _T, /, *_args: _T, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None) -> SupportsRichComparisonT, [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any]) -> _T, [SupportsRichComparisonT, _T](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, default: _T) -> SupportsRichComparisonT | _T, [_T1, _T2](iterable: Iterable[_T1], /, *, key: (_T1, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], default: _T2) -> _T1 | _T2]", "kind": 3, "label": "min", "sortText": "164"}, {"detail": "Overload[[_T](i: SupportsNext[_T], /) -> _T, [_T, _VT](i: SupportsNext[_T], default: _VT, /) -> _T | _VT]", "kind": 3, "label": "next", "sortText": "165"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The base class of the class hierarchy.\n\nWhen called, it accepts no arguments and returns a new featureless\ninstance that has no instance attributes and cannot be given any.\n"}, "kind": 7, "label": "object", "sortText": "166"}, {"detail": "def oct(number: SupportsIndex, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the octal representation of an integer.\n\n>>> oct(342391)\n'0o1234567'\n"}, "kind": 3, "label": "oct", "sortText": "167"}, {"detail": "Overload[(file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"r+\", \"+r\", \"rt+\", \"r+t\", \"+rt\", ... omitted 48 literals] = \"r\", buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> TextIOWrapper[_WrappedBuffer], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: Literal[0], encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> FileIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 19 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedRandom, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"wb\", \"bw\", \"ab\", \"ba\", \"xb\", \"bx\"], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedWriter[_BufferedWriterStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb\", \"br\", \"rbU\", \"rUb\", \"Urb\", ... omitted 3 literals], buffering: Literal[-1, 1] = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BufferedReader[_BufferedReaderStream], (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: Literal[\"rb+\", \"r+b\", \"+rb\", \"br+\", \"b+r\", ... omitted 33 literals], buffering: int = -1, encoding: None = None, errors: None = None, newline: None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> BinaryIO, (file: int | str | bytes | PathLike[str] | PathLike[bytes], mode: str, buffering: int = -1, encoding: str | None = None, errors: str | None = None, newline: str | None = None, closefd: bool = True, opener: ((str, int, /) -> int) | None = None) -> IO[Any]]", "kind": 3, "label": "open", "sortText": "168"}, {"detail": "def ord(c: str | bytes | bytearray, /) -> int", "documentation": {"kind": "plaintext", "value": "Return the ordinal value of a character.\n\nIf the argument is a one-character string, return the Unicode code\npoint of that character.\n\nIf the argument is a bytes or bytearray object of length 1, return its\nsingle byte value.\n"}, "kind": 3, "label": "ord", "sortText": "169"}, {"detail": "Overload[(base: int, exp: int, mod: int) -> int, (base: int, exp: Literal[0], mod: None = None) -> Literal[1], (base: int, exp: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], mod: None = None) -> int, (base: int, exp: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], mod: None = None) -> float, (base: int, exp: int, mod: None = None) -> Any, (base: Literal[1, 2, 3, 4, 5, ... omitted 20 literals], exp: float, mod: None = None) -> float, (base: Literal[-1, -2, -3, -4, -5, ... omitted 15 literals], exp: float, mod: None = None) -> complex, (base: float, exp: int, mod: None = None) -> float, (base: float, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> Any, (base: complex, exp: complex | _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], mod: None = None) -> complex, [_E_contra, _T_co](base: _SupportsPow2[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _T_co](base: _SupportsPow3NoneOnly[_E_contra, _T_co], exp: _E_contra, mod: None = None) -> _T_co, [_E_contra, _M_contra, _T_co](base: _SupportsPow3[_E_contra, _M_contra, _T_co], exp: _E_contra, mod: _M_contra) -> _T_co, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: float, mod: None = None) -> Any, (base: _SupportsPow2[Any, Any] | _SupportsPow3[Any, Any, Any], exp: complex, mod: None = None) -> complex]", "kind": 3, "label": "pow", "sortText": "170"}, {"detail": "Overload[(*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: SupportsWrite[str] | None = None, flush: Literal[False] = False) -> None, (*values: object, sep: str | None = \" \", end: str | None = \"\\n\", file: _SupportsWriteAndFlush[str] | None = None, flush: bool) -> None]", "kind": 3, "label": "print", "sortText": "171"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Property attribute.\n\n fget\n function to be used for getting an attribute value\n fset\n function to be used for setting an attribute value\n fdel\n function to be used for del'ing an attribute\n doc\n docstring\n\nTypical use is to define a managed attribute x:\n\nclass C(object):\n def getx(self): return self._x\n def setx(self, value): self._x = value\n def delx(self): del self._x\n x = property(getx, setx, delx, \"I'm the 'x' property.\")\n\nDecorators make defining new properties or modifying existing ones easy:\n\nclass C(object):\n @property\n def x(self):\n \"I am the 'x' property.\"\n return self._x\n @x.setter\n def x(self, value):\n self._x = value\n @x.deleter\n def x(self):\n del self._x\n"}, "kind": 7, "label": "property", "sortText": "172"}, {"detail": "Quitter", "kind": 22, "label": "quit", "sortText": "173"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "range(stop) -> range object\nrange(start, stop[, step]) -> range object\n\nReturn an object that produces a sequence of integers from start (inclusive)\nto stop (exclusive) by step. range(i, j) produces i, i+1, i+2, ..., j-1.\nstart defaults to 0, and stop is omitted! range(4) produces 0, 1, 2, 3.\nThese are exactly the valid indices for a list of 4 elements.\nWhen step is given, it specifies the increment (or decrement).\n"}, "kind": 7, "label": "range", "sortText": "174"}, {"detail": "def repr(obj: object, /) -> str", "documentation": {"kind": "plaintext", "value": "Return the canonical string representation of the object.\n\nFor many object types, including most builtins, eval(repr(obj)) == obj.\n"}, "kind": 3, "label": "repr", "sortText": "175"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Return a reverse iterator over the values of the given sequence.\n"}, "kind": 7, "label": "reversed", "sortText": "176"}, {"detail": "Overload[[_T](number: _SupportsRound1[_T], ndigits: None = None) -> _T, [_T](number: _SupportsRound2[_T], ndigits: SupportsIndex) -> _T]", "kind": 3, "label": "round", "sortText": "177"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Build an unordered collection of unique elements.\n"}, "kind": 7, "label": "set", "sortText": "178"}, {"detail": "def setattr(obj: object, name: str, value: Any, /) -> None", "documentation": {"kind": "plaintext", "value": "Sets the named attribute on the given object to the specified value.\n\nsetattr(x, 'y', v) is equivalent to ``x.y = v``\n"}, "kind": 3, "label": "setattr", "sortText": "179"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "slice(stop)\nslice(start, stop[, step])\n\nCreate a slice object.\n\nThis is used for extended slicing (e.g. a[0:10:2]).\n"}, "kind": 7, "label": "slice", "sortText": "180"}, {"detail": "Overload[[SupportsRichComparisonT](iterable: Iterable[SupportsRichComparisonT], /, *, key: None = None, reverse: bool = False) -> list[SupportsRichComparisonT], [_T](iterable: Iterable[_T], /, *, key: (_T, /) -> SupportsDunderLT[Any] | SupportsDunderGT[Any], reverse: bool = False) -> list[_T]]", "kind": 3, "label": "sorted", "sortText": "181"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Convert a function to be a static method.\n\nA static method does not receive an implicit first argument.\nTo declare a static method, use this idiom:\n\n class C:\n @staticmethod\n def f(arg1, arg2, argN):\n ...\n\nIt can be called either on the class (e.g. C.f()) or on an instance\n(e.g. C().f()). Both the class and the instance are ignored, and\nneither is passed implicitly as the first argument to the method.\n\nStatic methods in Python are similar to those found in Java or C++.\nFor a more advanced concept, see the classmethod builtin.\n"}, "kind": 7, "label": "staticmethod", "sortText": "182"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 7, "label": "str", "sortText": "183"}, {"detail": "Overload[(iterable: Iterable[bool | Literal[1, 2, 3, 4, 5, ... omitted 41 literals]], /, start: int = 0) -> int, [_SupportsSumNoDefaultT](iterable: Iterable[_SupportsSumNoDefaultT], /) -> _SupportsSumNoDefaultT | Literal[0], [_AddableT1, _AddableT2](iterable: Iterable[_AddableT1], /, start: _AddableT2) -> _AddableT1 | _AddableT2]", "kind": 3, "label": "sum", "sortText": "184"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "super() -> same as super(__class__, )\nsuper(type) -> unbound super object\nsuper(type, obj) -> bound super object; requires isinstance(obj, type)\nsuper(type, type2) -> bound super object; requires\n issubclass(type2, type)\nTypical use to call a cooperative superclass method:\nclass C(B):\n def meth(self, arg):\n super().meth(arg)\nThis works for class methods too:\nclass C(B):\n @classmethod\n def cmeth(cls, arg):\n super().cmeth(arg)\n"}, "kind": 7, "label": "super", "sortText": "185"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "Built-in immutable sequence.\n\nIf no argument is given, the constructor returns an empty tuple.\nIf iterable is specified the tuple is initialized from iterable's items.\n\nIf the argument is a tuple, the return value is the same object.\n"}, "kind": 7, "label": "tuple", "sortText": "186"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "type(object) -> the object's type\ntype(name, bases, dict, **kwds) -> a new type\n"}, "kind": 7, "label": "type", "sortText": "187"}, {"detail": "Overload[(object: type, /) -> MappingProxyType[str, Any], (object: Any = ..., /) -> dict[str, Any]]", "kind": 3, "label": "vars", "sortText": "188"}, {"detail": "", "documentation": {"kind": "plaintext", "value": "The zip object yields n-length tuples, where n is the number of\niterables passed as positional arguments to zip(). The i-th element\nin every tuple comes from the i-th iterable argument to zip(). This\ncontinues until the shortest argument is exhausted.\n\nIf strict is true and one of the arguments is exhausted before the\nothers, raise a ValueError.\n\n >>> list(zip('abcdefg', range(3), range(4)))\n [('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]\n"}, "kind": 7, "label": "zip", "sortText": "189"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__annotations__", "sortText": "190"}, {"detail": "def __build_class__(func: () -> CellType | Any, name: str, /, *bases: Any, metaclass: Any = ..., **kwds: Any) -> Any", "documentation": {"kind": "plaintext", "value": "__build_class__(func, name, /, *bases, [metaclass], **kwds) -> class\n\nInternal helper function used by the class statement.\n"}, "kind": 3, "label": "__build_class__", "sortText": "191"}, {"detail": "Any", "documentation": {"kind": "plaintext", "value": "Special type indicating an unconstrained type.\n\n- Any is assignable to every type.\n- Any assumed to have all methods and attributes.\n- All values are assignable to Any.\n\nNote that all the above statements are true from the point of view of\nstatic type checkers. At runtime, Any cannot be used with instance\nchecks.\n"}, "label": "__builtins__", "sortText": "192"}, {"detail": "type[ModuleType]", "documentation": {"kind": "plaintext", "value": "Create a module object.\n\nThe name must be a string; the optional doc argument can have any type.\n"}, "kind": 7, "label": "__class__", "sortText": "193"}, {"detail": "bool", "documentation": {"kind": "plaintext", "value": "Returns True when the argument is true, False otherwise.\nThe builtins True and False are the only two instances of the class bool.\nThe class bool is a subclass of the class int, and cannot be subclassed.\n"}, "kind": 22, "label": "__debug__", "sortText": "194"}, {"detail": "bound method ModuleType.__delattr__(name: str, /) -> None", "kind": 2, "label": "__delattr__", "sortText": "195"}, {"detail": "dict[str, Any]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__dict__", "sortText": "196"}, {"detail": "bound method ModuleType.__dir__() -> Iterable[str]", "kind": 2, "label": "__dir__", "sortText": "197"}, {"detail": "str | None", "kind": 22, "label": "__doc__", "sortText": "198"}, {"detail": "bound method ModuleType.__eq__(value: object, /) -> bool", "kind": 2, "label": "__eq__", "sortText": "199"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__file__", "sortText": "200"}, {"detail": "bound method ModuleType.__format__(format_spec: str, /) -> str", "kind": 2, "label": "__format__", "sortText": "201"}, {"detail": "bound method ModuleType.__getattr__(name: str) -> Any", "kind": 2, "label": "__getattr__", "sortText": "202"}, {"detail": "bound method ModuleType.__getattribute__(name: str, /) -> Any", "kind": 2, "label": "__getattribute__", "sortText": "203"}, {"detail": "bound method ModuleType.__getstate__() -> object", "kind": 2, "label": "__getstate__", "sortText": "204"}, {"detail": "bound method ModuleType.__hash__() -> int", "kind": 2, "label": "__hash__", "sortText": "205"}, {"detail": "def __import__(name: str, globals: Mapping[str, object] | None = None, locals: Mapping[str, object] | None = None, fromlist: Sequence[str] | None = ..., level: int = 0) -> ModuleType", "documentation": {"kind": "plaintext", "value": "Import a module.\n\nBecause this function is meant for use by the Python\ninterpreter and not for general use, it is better to use\nimportlib.import_module() to programmatically import a module.\n\nThe globals argument is only used to determine the context;\nthey are not modified. The locals argument is unused. The fromlist\nshould be a list of names to emulate ``from name import ...``, or an\nempty list to emulate ``import name``.\nWhen importing a module from a package, note that __import__('A.B', ...)\nreturns package A when fromlist is empty, but its submodule B when\nfromlist is not empty. The level argument is used to determine whether\nto perform absolute or relative imports: 0 is absolute, while a positive\nnumber is the number of parent directories to search relative to the\ncurrent module.\n"}, "kind": 3, "label": "__import__", "sortText": "206"}, {"detail": "bound method ModuleType.__init__(name: str, doc: str | None = ...) -> None", "kind": 2, "label": "__init__", "sortText": "207"}, {"detail": "bound method type[ModuleType].__init_subclass__() -> None", "kind": 2, "label": "__init_subclass__", "sortText": "208"}, {"detail": "LoaderProtocol | None", "kind": 8, "label": "__loader__", "sortText": "209"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__module__", "sortText": "210"}, {"detail": "str", "documentation": {"kind": "plaintext", "value": "str(object='') -> str\nstr(bytes_or_buffer[, encoding[, errors]]) -> str\n\nCreate a new string object from the given object. If encoding or\nerrors is specified, then the object must expose a data buffer\nthat will be decoded using the given encoding and error handler.\nOtherwise, returns the result of object.__str__() (if defined)\nor repr(object).\nencoding defaults to 'utf-8'.\nerrors defaults to 'strict'.\n"}, "kind": 22, "label": "__name__", "sortText": "211"}, {"detail": "bound method ModuleType.__ne__(value: object, /) -> bool", "kind": 2, "label": "__ne__", "sortText": "212"}, {"detail": "def __new__[Self](cls) -> Self", "kind": 3, "label": "__new__", "sortText": "213"}, {"detail": "str | None", "kind": 22, "label": "__package__", "sortText": "214"}, {"detail": "MutableSequence[str]", "documentation": {"kind": "plaintext", "value": "All the operations on a read-write sequence.\n\nConcrete subclasses must provide __new__ or __init__,\n__getitem__, __setitem__, __delitem__, __len__, and insert().\n"}, "kind": 22, "label": "__path__", "sortText": "215"}, {"detail": "bound method ModuleType.__reduce__() -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce__", "sortText": "216"}, {"detail": "bound method ModuleType.__reduce_ex__(protocol: SupportsIndex, /) -> str | tuple[Any, ...]", "kind": 2, "label": "__reduce_ex__", "sortText": "217"}, {"detail": "bound method ModuleType.__repr__() -> str", "kind": 2, "label": "__repr__", "sortText": "218"}, {"detail": "bound method ModuleType.__setattr__(name: str, value: Any, /) -> None", "kind": 2, "label": "__setattr__", "sortText": "219"}, {"detail": "bound method ModuleType.__sizeof__() -> int", "kind": 2, "label": "__sizeof__", "sortText": "220"}, {"detail": "ModuleSpec | None", "kind": 22, "label": "__spec__", "sortText": "221"}, {"detail": "bound method ModuleType.__str__() -> str", "kind": 2, "label": "__str__", "sortText": "222"}, {"detail": "bound method type[ModuleType].__subclasshook__(subclass: type, /) -> bool", "kind": 2, "label": "__subclasshook__", "sortText": "223"}, {"detail": "dict[Any, int]", "documentation": {"kind": "plaintext", "value": "dict() -> new empty dictionary\ndict(mapping) -> new dictionary initialized from a mapping object's\n (key, value) pairs\ndict(iterable) -> new dictionary initialized as if via:\n d = {}\n for k, v in iterable:\n d[k] = v\ndict(**kwargs) -> new dictionary initialized with the name=value pairs\n in the keyword argument list. For example: dict(one=1, two=2)\n"}, "kind": 22, "label": "__warningregistry__", "sortText": "224"}]}} +{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 1, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: JsonType = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} +{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 2, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: JsonType = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} +{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 3, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: JsonType = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} +{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 4, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: JsonType = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} +{"suite": "web", "label": "edit response then hover (edit+hover)", "method": "textDocument/hover", "file_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/web/src/app.py", "line": 11, "character": 20, "iteration": 5, "result": {"contents": {"kind": "plaintext", "value": "bound method Session.get(\n url: str | bytes,\n params: SupportsItems[str | bytes | float, Iterable[str | bytes | float] | float | None] | Iterable[tuple[str | bytes | float, Iterable[str | bytes | float] | float | None]] | str | bytes | None = None,\n *,\n allow_redirects: bool = ...,\n auth: tuple[str, str] | ((PreparedRequest, /) -> PreparedRequest) | None = ...,\n cert: str | tuple[str, str] | None = ...,\n cookies: CookieJar | dict[str, str] | None = ...,\n data: Iterable[tuple[Any, Any]] | SupportsItems[Any, Any] | Iterable[bytes | str] | ... omitted 3 union elements = ...,\n files: Mapping[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements] | Iterable[tuple[str, SupportsRead[str | bytes] | str | bytes | ... omitted 3 union elements]] | None = ...,\n headers: Mapping[str, str | bytes] | None = ...,\n hooks: Mapping[str, Iterable[(Response, /) -> Any] | ((Response, /) -> Any)] | None = ...,\n json: JsonType = ...,\n proxies: dict[str, str] | None = ...,\n stream: bool | None = ...,\n timeout: float | tuple[float | None, float | None] | None = ...,\n verify: bool | str | None = ...,\n **kwargs: object\n) -> Response\n---------------------------------------------\nSends a GET request. Returns :class:`Response` object.\n\n:param url: URL for the new :class:`Request` object.\n:param params: (optional) Dictionary, list of tuples or bytes to send\nin the query string for the :class:`Request`.\n:param \\*\\*kwargs: Optional arguments that ``request`` takes.\n:rtype: requests.Response\n"}, "range": {"end": {"character": 21, "line": 11}, "start": {"character": 18, "line": 11}}}} diff --git a/latest-results/ty-20260917T060626Z.json b/latest-results/ty-20260918T060520Z.json similarity index 89% rename from latest-results/ty-20260917T060626Z.json rename to latest-results/ty-20260918T060520Z.json index 8fc2346..4ed4bd6 100644 --- a/latest-results/ty-20260917T060626Z.json +++ b/latest-results/ty-20260918T060520Z.json @@ -1,6 +1,6 @@ { "server_command": [ - "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.81/ty-x86_64-unknown-linux-gnu/ty", + "/home/runner/work/python-lsp-compare/python-lsp-compare/.python-lsp-compare/servers/ty/0.0.82/ty-x86_64-unknown-linux-gnu/ty", "server" ], "requested_scenarios": [], @@ -12,8 +12,8 @@ "transformers", "web" ], - "started_at_unix": 1789625281.1079874, - "finished_at_unix": 1789625286.0830112, + "started_at_unix": 1789711610.4971397, + "finished_at_unix": 1789711615.718869, "scenario_reports": [], "benchmark_reports": [ { @@ -26,7 +26,7 @@ "environment_path": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/.venv", "python_executable": "/home/runner/work/python-lsp-compare/python-lsp-compare/benchmarks/data_science/.venv/bin/python", "success": true, - "total_duration_ms": 396.3682819999974, + "total_duration_ms": 534.8502589999953, "error_message": null, "summary": { "request_count": 32, @@ -34,12 +34,12 @@ "success_count": 32, "failure_count": 0, "bytes_sent": 18656, - "bytes_received": 874720, - "min_ms": 0.20183700002007754, - "max_ms": 202.8018080000038, - "mean_ms": 11.712054156250318, - "median_ms": 1.8636269999916522, - "p95_ms": 40.92316510000695, + "bytes_received": 878182, + "min_ms": 0.19357200000058583, + "max_ms": 307.13992600001916, + "mean_ms": 16.050325718752312, + "median_ms": 1.8331134999982623, + "p95_ms": 48.46599244999362, "result_summary": { "present_count": 31, "empty_count": 1, @@ -69,10 +69,10 @@ }, "size_chars": { "min": 0.0, - "max": 80262.0, - "mean": 28009.03125, + "max": 80899.0, + "mean": 28117.21875, "median": 4546.0, - "p95": 80262.0 + "p95": 80899.0 }, "top_level_count": { "min": 1.0, @@ -95,27 +95,27 @@ "by_method": { "textDocument/completion": { "point_count": 2, - "min_ms": 1.5625199999931283, - "max_ms": 11.495146000015666, - "mean_ms": 6.256558599997675, - "median_ms": 6.137834500009376, - "p95_ms": 11.176538800000912 + "min_ms": 1.5987600000073598, + "max_ms": 14.489749999995638, + "mean_ms": 7.086270400006356, + "median_ms": 6.891649499991104, + "p95_ms": 13.434876199998767 }, "textDocument/hover": { "point_count": 2, - "min_ms": 0.29985000000465334, - "max_ms": 3.9177330000086386, - "mean_ms": 2.04753430000153, - "median_ms": 2.0142600000099264, - "p95_ms": 3.899068349997492 + "min_ms": 0.2844009999876107, + "max_ms": 5.8966590000011365, + "mean_ms": 3.0867873000005375, + "median_ms": 3.082815500007996, + "p95_ms": 5.880775800004301 }, "textDocument/definition": { "point_count": 1, - "min_ms": 0.20183700002007754, - "max_ms": 0.24517600002127438, - "mean_ms": 0.21780660001127217, - "median_ms": 0.2121970000246165, - "p95_ms": 0.24079820001929875 + "min_ms": 0.19357200000058583, + "max_ms": 0.20647599998824262, + "mean_ms": 0.20147460000430328, + "median_ms": 0.20223800001417658, + "p95_ms": 0.2062455999919166 } }, "validation": { @@ -140,12 +140,12 @@ "success_count": 5, "failure_count": 0, "bytes_sent": 1425, - "bytes_received": 306550, - "min_ms": 1.5625199999931283, - "max_ms": 1.9635710000045492, - "mean_ms": 1.7329913999958535, - "median_ms": 1.7244229999846539, - "p95_ms": 1.9259646000023167, + "bytes_received": 306250, + "min_ms": 1.5987600000073598, + "max_ms": 2.0274519999929907, + "mean_ms": 1.702037200010409, + "median_ms": 1.629918000020325, + "p95_ms": 1.9497165999950992, "result_summary": { "present_count": 5, "empty_count": 0, @@ -160,11 +160,11 @@ "p95": 223.0 }, "size_chars": { - "min": 63682.0, - "max": 63682.0, - "mean": 63682.0, - "median": 63682.0, - "p95": 63682.0 + "min": 63622.0, + "max": 63622.0, + "mean": 63622.0, + "median": 63622.0, + "p95": 63622.0 }, "top_level_count": { "min": 2.0, @@ -205,11 +205,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 202.8018080000038, + "duration_ms": 307.13992600001916, "success": true, - "started_at_unix": 1789625281.1256125, + "started_at_unix": 1789711610.5148466, "bytes_sent": 285, - "bytes_received": 61310, + "bytes_received": 61250, "request_id": 2, "error_code": null, "error_message": null, @@ -218,7 +218,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 63682, + "size_chars": 63622, "top_level_count": 2, "completion_item_count": 223 }, @@ -235,11 +235,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 1.9635710000045492, + "duration_ms": 2.0274519999929907, "success": true, - "started_at_unix": 1789625281.3293743, + "started_at_unix": 1789711610.8229473, "bytes_sent": 285, - "bytes_received": 61310, + "bytes_received": 61250, "request_id": 3, "error_code": null, "error_message": null, @@ -248,7 +248,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 63682, + "size_chars": 63622, "top_level_count": 2, "completion_item_count": 223 }, @@ -265,11 +265,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 1.7244229999846539, + "duration_ms": 1.638775000003534, "success": true, - "started_at_unix": 1789625281.3327804, + "started_at_unix": 1789711610.8262768, "bytes_sent": 285, - "bytes_received": 61310, + "bytes_received": 61250, "request_id": 4, "error_code": null, "error_message": null, @@ -278,7 +278,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 63682, + "size_chars": 63622, "top_level_count": 2, "completion_item_count": 223 }, @@ -295,11 +295,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 1.6389040000035493, + "duration_ms": 1.5987600000073598, "success": true, - "started_at_unix": 1789625281.335859, + "started_at_unix": 1789711610.8291905, "bytes_sent": 285, - "bytes_received": 61310, + "bytes_received": 61250, "request_id": 5, "error_code": null, "error_message": null, @@ -308,7 +308,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 63682, + "size_chars": 63622, "top_level_count": 2, "completion_item_count": 223 }, @@ -325,11 +325,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 1.5625199999931283, + "duration_ms": 1.615281000027835, "success": true, - "started_at_unix": 1789625281.3387659, + "started_at_unix": 1789711610.8320513, "bytes_sent": 285, - "bytes_received": 61310, + "bytes_received": 61250, "request_id": 6, "error_code": null, "error_message": null, @@ -338,7 +338,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 63682, + "size_chars": 63622, "top_level_count": 2, "completion_item_count": 223 }, @@ -355,11 +355,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 1.7755389999933868, + "duration_ms": 1.629918000020325, "success": true, - "started_at_unix": 1789625281.3416355, + "started_at_unix": 1789711610.8349352, "bytes_sent": 285, - "bytes_received": 61310, + "bytes_received": 61250, "request_id": 7, "error_code": null, "error_message": null, @@ -368,7 +368,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 63682, + "size_chars": 63622, "top_level_count": 2, "completion_item_count": 223 }, @@ -400,11 +400,11 @@ "failure_count": 0, "bytes_sent": 1269, "bytes_received": 22949, - "min_ms": 0.29985000000465334, - "max_ms": 0.3920430000050601, - "mean_ms": 0.33128119999901173, - "median_ms": 0.31846599998175407, - "p95_ms": 0.3821684000058667, + "min_ms": 0.2844009999876107, + "max_ms": 0.3561759999968217, + "mean_ms": 0.32037719999493675, + "median_ms": 0.3300079999917216, + "p95_ms": 0.3541161999976339, "result_summary": { "present_count": 5, "empty_count": 0, @@ -464,9 +464,9 @@ { "kind": "request", "method": "textDocument/hover", - "duration_ms": 0.45782600000165985, + "duration_ms": 0.5373950000091554, "success": true, - "started_at_unix": 1789625281.344756, + "started_at_unix": 1789711610.8379483, "bytes_sent": 253, "bytes_received": 4589, "request_id": 8, @@ -494,9 +494,9 @@ { "kind": "request", "method": "textDocument/hover", - "duration_ms": 0.3920430000050601, + "duration_ms": 0.3561759999968217, "success": true, - "started_at_unix": 1789625281.3452885, + "started_at_unix": 1789711610.8385596, "bytes_sent": 253, "bytes_received": 4589, "request_id": 9, @@ -524,9 +524,9 @@ { "kind": "request", "method": "textDocument/hover", - "duration_ms": 0.3426700000090932, + "duration_ms": 0.3300079999917216, "success": true, - "started_at_unix": 1789625281.3457735, + "started_at_unix": 1789711610.8390086, "bytes_sent": 254, "bytes_received": 4590, "request_id": 10, @@ -554,9 +554,9 @@ { "kind": "request", "method": "textDocument/hover", - "duration_ms": 0.30337699999449796, + "duration_ms": 0.3458770000008826, "success": true, - "started_at_unix": 1789625281.3462217, + "started_at_unix": 1789711610.8394563, "bytes_sent": 254, "bytes_received": 4590, "request_id": 11, @@ -584,9 +584,9 @@ { "kind": "request", "method": "textDocument/hover", - "duration_ms": 0.31846599998175407, + "duration_ms": 0.2844009999876107, "success": true, - "started_at_unix": 1789625281.346611, + "started_at_unix": 1789711610.8398898, "bytes_sent": 254, "bytes_received": 4590, "request_id": 12, @@ -614,9 +614,9 @@ { "kind": "request", "method": "textDocument/hover", - "duration_ms": 0.29985000000465334, + "duration_ms": 0.2854239999976471, "success": true, - "started_at_unix": 1789625281.347036, + "started_at_unix": 1789711610.8402753, "bytes_sent": 254, "bytes_received": 4590, "request_id": 13, @@ -659,11 +659,11 @@ "failure_count": 0, "bytes_sent": 1300, "bytes_received": 1235, - "min_ms": 0.20183700002007754, - "max_ms": 0.24517600002127438, - "mean_ms": 0.21780660001127217, - "median_ms": 0.2121970000246165, - "p95_ms": 0.24079820001929875, + "min_ms": 0.19357200000058583, + "max_ms": 0.20647599998824262, + "mean_ms": 0.20147460000430328, + "median_ms": 0.20223800001417658, + "p95_ms": 0.2062455999919166, "result_summary": { "present_count": 5, "empty_count": 0, @@ -723,9 +723,9 @@ { "kind": "request", "method": "textDocument/definition", - "duration_ms": 0.24347499999066713, + "duration_ms": 0.23610099998450096, "success": true, - "started_at_unix": 1789625281.3474936, + "started_at_unix": 1789711610.8407116, "bytes_sent": 260, "bytes_received": 247, "request_id": 14, @@ -753,9 +753,9 @@ { "kind": "request", "method": "textDocument/definition", - "duration_ms": 0.2065359999789962, + "duration_ms": 0.20647599998824262, "success": true, - "started_at_unix": 1789625281.3477736, + "started_at_unix": 1789711610.8409877, "bytes_sent": 260, "bytes_received": 247, "request_id": 15, @@ -783,9 +783,9 @@ { "kind": "request", "method": "textDocument/definition", - "duration_ms": 0.22328700001139623, + "duration_ms": 0.20223800001417658, "success": true, - "started_at_unix": 1789625281.3480253, + "started_at_unix": 1789711610.8412426, "bytes_sent": 260, "bytes_received": 247, "request_id": 16, @@ -813,9 +813,9 @@ { "kind": "request", "method": "textDocument/definition", - "duration_ms": 0.24517600002127438, + "duration_ms": 0.19357200000058583, "success": true, - "started_at_unix": 1789625281.3482966, + "started_at_unix": 1789711610.8414912, "bytes_sent": 260, "bytes_received": 247, "request_id": 17, @@ -843,9 +843,9 @@ { "kind": "request", "method": "textDocument/definition", - "duration_ms": 0.2121970000246165, + "duration_ms": 0.20532400000661255, "success": true, - "started_at_unix": 1789625281.3486013, + "started_at_unix": 1789711610.84173, "bytes_sent": 260, "bytes_received": 247, "request_id": 18, @@ -873,9 +873,9 @@ { "kind": "request", "method": "textDocument/definition", - "duration_ms": 0.20183700002007754, + "duration_ms": 0.19976300001189884, "success": true, - "started_at_unix": 1789625281.3488643, + "started_at_unix": 1789711610.8420045, "bytes_sent": 260, "bytes_received": 247, "request_id": 19, @@ -917,12 +917,12 @@ "success_count": 5, "failure_count": 0, "bytes_sent": 1440, - "bytes_received": 394530, - "min_ms": 10.312098000014203, - "max_ms": 11.495146000015666, - "mean_ms": 10.780125799999496, - "median_ms": 10.754765000001498, - "p95_ms": 11.353542800009109, + "bytes_received": 397715, + "min_ms": 11.755846999989217, + "max_ms": 14.489749999995638, + "mean_ms": 12.470503600002303, + "median_ms": 12.117493000005197, + "p95_ms": 14.02091719999703, "result_summary": { "present_count": 5, "empty_count": 0, @@ -937,11 +937,11 @@ "p95": 168.0 }, "size_chars": { - "min": 80262.0, - "max": 80262.0, - "mean": 80262.0, - "median": 80262.0, - "p95": 80262.0 + "min": 80899.0, + "max": 80899.0, + "mean": 80899.0, + "median": 80899.0, + "p95": 80899.0 }, "top_level_count": { "min": 2.0, @@ -982,11 +982,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 76.8907439999964, + "duration_ms": 89.99251099999128, "success": true, - "started_at_unix": 1789625281.349304, + "started_at_unix": 1789711610.8424263, "bytes_sent": 288, - "bytes_received": 78906, + "bytes_received": 79543, "request_id": 20, "error_code": null, "error_message": null, @@ -995,7 +995,7 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 80262, + "size_chars": 80899, "top_level_count": 2, "completion_item_count": 168 }, @@ -1012,11 +1012,11 @@ { "kind": "request", "method": "textDocument/completion", - "duration_ms": 11.495146000015666, + "duration_ms": 14.489749999995638, "success": true, - "started_at_unix": 1789625281.4274156, + "started_at_unix": 1789711610.9338257, "bytes_sent": 288, - 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"bytes_received": 1823, + "bytes_received": 1765, "request_id": 31, "error_code": null, "error_message": null, @@ -17247,9 +17247,9 @@ "present": true, "empty": false, "top_level_kind": "dict", - "size_chars": 1779, + "size_chars": 1721, "top_level_count": 2, - "hover_text_char_count": 1613 + "hover_text_char_count": 1555 }, "context": { "suite": "web", @@ -17264,9 +17264,9 @@ { "kind": "notification", "method": "textDocument/didChange", - "duration_ms": 0.0550739999880534, + "duration_ms": 0.029505000014751204, "success": true, - "started_at_unix": 1789625286.0735066, + "started_at_unix": 1789711615.708978, "bytes_sent": 319, "bytes_received": 0, "request_id": null, @@ -17283,9 +17283,9 @@ { "kind": "notification", "method": "textDocument/didClose", - "duration_ms": 0.023623999993560574, + "duration_ms": 0.0291549999928975, "success": true, - "started_at_unix": 1789625286.0736506, + "started_at_unix": 1789711615.7091115, "bytes_sent": 198, "bytes_received": 0, "request_id": null, @@ -17298,9 +17298,9 @@ { "kind": "request", "method": "shutdown", - 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