fix(phi4): stage engine plans and export AIPerf tokenizer

[yizhuoz004]

Background

The existing Phi4 E2E was OOM-killed on Community CI's standard host before writing JUnit. Its builder retained the complete prefill engine while building decode, then both engines while building vision. Each decoder plan is about8.3 GiB. The standard public GPU later reached the FP32 eager reference but failed a 192 MiB allocation with 543 MiB reserved and unused by PyTorch. Configure the family test allocator to reduce fragmentation while retaining caller settings. The same family also needs a standalone tokenizer export for the published AIPerf client, which cannot load the model-only remote configuration and can rebuild a GPT2-class regex differently.

This family-only prerequisite is split from #1761 to respect Dev CI's existing five-family limit. Refs #1672; it does not close Stage 5.

Exit Criteria

• Complete the unchanged full Phi4 family E2E within the standard48 GiB container memory limit.
• Run the same FP32 eager reference with its original operators and quality criteria; verify current public/protected CI before merging.
• Export its existing tokenizer for pip-installed AIPerf without changing vocabulary, token IDs, framing or chat template.

Implementation

Stage prefill, decode and vision plans immediately through the existing file-backed BundleWriter, then release each returned byte buffer before the next network is built. Network builders, parameters, call order, precision, references and numerical gates are unchanged. Output publication stays atomic; named sections and their format are unchanged, while their physical order may differ.

The family pytest configuration defaults to expandable_segments:True only when the caller has not selected an allocator. This changes allocation management, with no change to the reference model, operators, FP32 precision, prompt, generation controls or gates.

Add families/phi4_multimodal/tests/aiperf/prepare_tokenizer.py. In the existing prepared family environment (transformers==4.48.2), run:

python families/phi4_multimodal/tests/aiperf/prepare_tokenizer.py \
  --model-dir /path/to/Phi-4-multimodal-instruct \
  --output-dir /tmp/phi4-tokenizer

Pass the new directory to AIPerf with --tokenizer /tmp/phi4-tokenizer. The utility preserves the backend, vocabulary, special framing and chat template, saves a standard fast tokenizer, reloads it and checks identity. No AIPerf source checkout is required.

Change categories

• Model or runtime behavior
• Public API
• ABI
• Bundle or artifact format
• Dependencies
• Documentation only
• CI or developer tooling

Validation

Commands and Results

• Current-head public CPU/stable, standard GPU E2E/resource cleanup and protected premerge: PASS. Public standard execution: 39069510845; protected result is the sanitized status on the exact head above.
• python -m pytest families/phi4_multimodal/tests/test_plan_lifetime.py families/phi4_multimodal/tests/test_family_contract.py families/phi4_multimodal/tests/test_vision_oracle.py -q: 22 passed on the new head. The new lifecycle regression fails the old code because the prefill blob is retained when decode begins.
• python -m pytest families/phi4_multimodal/tests/test_e2e.py::test_official_checkpoint_e2e --e2e-testcase phi4-multimodal: 1 non-skipped pass, with the unchanged reference and criteria, in an isolated container capped at48 GiB RAM with swap disabled. The same case on unchanged main was OOMKilled/exit137 before JUnit under the same local limit. Both logs and cgroup observations are preserved. These are resource/correctness diagnostics, not a timing comparison.
• Matched GB300 allocator-capacity control, using a 21.8 GiB PyTorch budget: default allocation fails the same 192 MiB request; expandable segments complete the original FP32 eager reference. All 30 token IDs and the full text exactly match the earlier uncapped reference. This is a GB300 resource diagnostic, not an L4 reproduction or a new full E2E pass.
• Loaded the exported tokenizer in the actual PyPI AIPerf0.13.0 environment: all200,029 vocabulary entries and 8 source ID/framing probes match. Its 423-character chat template and 2 rendered-chat/exact-ID probes also match across source and client environments.
• Ruff, model CI, git diff --check, author-owned DCO and a fresh detached self-review pass. The integration's separately recorded Phi4 native/HTTP run passes its unchanged9/10 corpus gate and all55 client requests; that earlier transport evidence is not relabelled as a new run on this head.

Hardware, Environment, and Revisions

Base a9d2ba7fe7905b548b729a440e6ed598c57185f5; current head eed140a43ed1ec49488e08b5a6e30acf572a0b6f. The full 48 GiB build-memory E2E and allocator diagnostic retain source epoch c84512364642e36d652046704d48ed7e1df6b545; rebasing leaves those builder and tokenizer implementations byte-identical. The additional current-head change is the family pytest allocator configuration. Checkpoint microsoft/Phi-4-multimodal-instruct@93f923e1a7727d1c4f446756212d9d3e8fcc5d81. Local resource controls use aarch64 GB300/SM103, TensorRT11.1.0.106, Torch2.12.0+cu130, Python3.12.3 and family Transformers4.48.2. The control host differs from public x86 Community CI; fresh exact-head CI must still pass.

Not Run / Remaining Gaps

Current head eed140a43ed1ec49488e08b5a6e30acf572a0b6f passes Stable Community CI, the standard Dev GPU workflow and TRTMC Internal CI / Automated premerge gate=PASS. Standard Dev CI completed its selected full family E2E and confirmed cloud-resource release and cleanup. No larger runner was needed for this head. The approved larger retry retains its actual older c845123 epoch; it is not substituted for the current standard result. This PR changes no inference equations, precision policy, numerical threshold, checkpoint, dependency declaration, ABI or bundle format. No weights or generated artifacts are committed.

Contributor Self-Review

• I have completed a self-review of this change.

Notes For Future Readers

The core writer already stages sections on disk; use that mechanic instead of retaining large engine byte buffers in the family. No runner capacity or model correctness criterion is changed. The family test allocator default addresses measured fragmentation and preserves explicit caller settings. Preserve the checkpoint backend in tokenizer export, and run it in the declared family environment. Existing Phi4 checkpoint MIT terms continue to apply to user-built bundles; no new external code/package or asset redistribution is introduced.

Risk level

• Low
• Medium
• High

The build now stages sections earlier. A full E2E validates the resulting named-section bundle; the existing writer preserves atomic publication and abort behavior.

[coderabbitai]

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• families/phi4_multimodal/tests/conftest.py

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📝 Summary

Summary

The Phi-4 multimodal build stages the prefill, decode, and vision plans through the existing BundleWriter in that order. It releases each serialized plan buffer before building the next network. It checks for a missing vision engine before staging the vision plan. This reduces the time that multiple plan buffers remain live without changing the network builders or bundle format.

A regression test checks that each plan is released before the next engine build and that bundle creation completes. The family test configuration also enables PyTorch expandable CUDA allocator segments only when PYTORCH_ALLOC_CONF is unset and PYTORCH_CUDA_ALLOC_CONF is not already set.

The new prepare_tokenizer.py utility exports a local Phi-4 multimodal checkpoint tokenizer for AIPerf. It preserves the tokenizer backend and settings, then reloads the export and checks the vocabulary, chat template, and token IDs for eight probes. It writes an audit JSON after these checks pass.

The author reports 22 passes across the plan-lifetime, family-contract, and vision-oracle tests. The author also reports one non-skipped official-checkpoint E2E pass in a 48 GiB, swap-disabled container. These results were not independently verified. A Dev run on an earlier head was reportedly killed by host-memory pressure before JUnit output. A later run reportedly reached the FP32 reference but hit CUDA OOM during reference vision attention, so it produced no parity verdict. Fresh public and protected CI for the updated head remains pending. The author also reports that AIPerf 0.13.0 matched the source tokenizer’s vocabulary and probes.

Architecture impact

• Family-owned files: The build changes, tokenizer utility, plan-lifetime test, and allocator test configuration are within the Phi-4 multimodal family.
• Changed shared surfaces: The family build uses the existing shared BundleWriter API. No shared implementation change is shown. Bundle writing now stages each plan during the build instead of retaining plans until later.
• Dependency direction: The family build depends on BundleWriter. The tokenizer utility depends on transformers when run. The supplied evidence shows no dependency from shared code to the family or from core code to AIPerf.
• Affected consumers: Bundle readers consume the staged plans. AIPerf consumes the exported tokenizer directory. Compatibility evidence is limited to the reported checkpoint and AIPerf 0.13.0.
• Unresolved blast-radius questions: Fresh CI qualification for the updated head and broader tokenizer compatibility remain unverified. The CUDA OOM run does not establish a parity result.
• Review outcome: HUMAN REVIEW REQUIRED. Current review findings were not supplied, so finding counts are unavailable. The outstanding CI and compatibility questions prevent a broader conclusion. This outcome does not assert a confirmed violation.

Adds a command-line script to export and verify a local Phi-4 multimodal tokenizer. The native build writes each engine plan after construction and releases its buffer before building the next engine.

Changes: Tokenizer export

Layer / File(s)	Summary
Export and validate tokenizer families/phi4_multimodal/tests/aiperf/prepare_tokenizer.py	Adds export_tokenizer and a command-line entry point. The script validates the model type, exports the tokenizer, checks the reloaded vocabulary, chat template, and probe token IDs, then writes an audit JSON.

Serialized plan lifetime

Layer / File(s)	Summary
Stage and release plans during build families/phi4_multimodal/model.py, families/phi4_multimodal/tests/test_plan_lifetime.py, families/phi4_multimodal/tests/conftest.py	The native build writes the prefill, decode, and vision plans after construction and deletes each buffer before building the next engine. The regression test checks build order, plan release, and bundle creation. The pytest configuration sets the CUDA allocator variable only when the relevant variables are unset.

Priority: ➖ Normal

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Bug fix

Merge Risk: ⚪ Minimal · up to eed14

The allocator setting is configured before the family tests import PyTorch. No concrete merge-blocking risk is established for the reviewed change.

Pre-merge checks: 8 · 1

Failed checks: 1 warning

Check name	Status	Explanation	Resolution
Docstring Coverage		Docstring coverage is 15.38% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 13 functions across 4 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

Passed checks: 8 passed

Check name	Status	Explanation
Linked Issues check		Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check		Check skipped because no linked issues were found for this pull request.
Family Ownership Boundary		No cross-family dependency is introduced. The authoritative diff contains only four files under families/phi4_multimodal/. In model.py:346-347,360-361,373-374,383-384, the new staging calls use th…
Shared Semantic Neutrality		PASS. The reviewed range changes only families/phi4_multimodal/model.py and family-owned test/tool files. The plan staging and header decisions are in the Phi-4 model module. The allocator hook, lif…
Benchmark Validation Integrity		PASS. The PR changes plan staging and test allocator configuration, not benchmark accounting or comparison semantics. The native build still uses the same prefill, decode, and vision plans; it only wr…
Shared Change Blast Radius		The pull request changes only families/phi4_multimodal: the family builder, family AIPerf export utility, family conftest.py, and a family regression test. The BundleWriter API and shared bundle…
Title check		The title clearly and concisely summarizes both primary changes: staging Phi-4 engine plans and exporting the AIPerf tokenizer.
Description check		The description completes all required template sections. It explains the motivation, exit criteria, implementation, change categories, validation results, environment, remaining gaps, self-review, ri…

Full details: Family Ownership Boundary

Explanation

No cross-family dependency is introduced. The authoritative diff contains only four files under families/phi4_multimodal/. In model.py:346-347,360-361,373-374,383-384, the new staging calls use the caller-provided shared BundleWriter; the builder remains Phi4-owned and its existing local imports at model.py:20-21,203,227,413 stay within families/phi4_multimodal. The new test imports only families.phi4_multimodal at test_plan_lifetime.py:15-16 and shared tensorrt_model_connect.bundle_writer at line 17. The tokenizer utility uses shared transformers at line 11. No other family, central registry, switch, source list, or strategy map is edited or referenced by the changed code.

Full details: Shared Semantic Neutrality

Explanation

PASS. The reviewed range changes only families/phi4_multimodal/model.py and family-owned test/tool files. The plan staging and header decisions are in the Phi-4 model module. The allocator hook, lifecycle regression test, and tokenizer exporter are family test/tool code. No shared code outside the excluded model-owned Python, runtime, test, E2E, or family-tool areas changed.

Full details: Benchmark Validation Integrity

Explanation

PASS. The PR changes plan staging and test allocator configuration, not benchmark accounting or comparison semantics. The native build still uses the same prefill, decode, and vision plans; it only writes each named section earlier and releases the returned bytes. Runtime consumers resolve sections by name, so physical section order does not alter execution. The reference E2E path retains the same eager operators, precision, prompt, generation settings, output checks, and parity threshold. The tokenizer utility adds vocabulary, chat-template, and token-ID identity checks without changing benchmark aggregation or workload units. No changed path adds one-sided synchronization, transfers, reductions, serialization, or validation.

Full details: Shared Change Blast Radius

Explanation

The pull request changes only families/phi4_multimodal: the family builder, family AIPerf export utility, family conftest.py, and a family regression test. The BundleWriter API and shared bundle reader are unchanged; the builder only uses existing set_header and add_bytes calls. The allocator default is scoped to families/phi4_multimodal/tests, and the tokenizer utility is explicitly gated to Phi-4 multimodal checkpoints. This is a family-local change that does not alter a shared surface, so the shared-change blast-radius check is not applicable.

Full details: Description check

Explanation

The description completes all required template sections. It explains the motivation, exit criteria, implementation, change categories, validation results, environment, remaining gaps, self-review, risks, and follow-up notes.

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[coderabbitai]

Actionable comments posted: 1

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🤖 Prompt to fix review comments

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Inline comments:
Review comments at @families/phi4_multimodal/tests/aiperf/prepare_tokenizer.py:
- Around line 30-37: Preserve the source tokenizer’s chat template when
constructing the exported tokenizer in the `PreTrainedTokenizerFast` setup, and
validate after restoration that `restored.chat_template` matches
`tokenizer.chat_template`. Keep the existing vocabulary validation unchanged.

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[yizhuoz004]

Dev CI run 38996735705 reached the existing phi4-multimodal E2E, then Docker reported OOMKilled and pytest was terminated by SIGKILL before writing JUnit. The run selected the standard 64 GiB host profile; the trusted coordinator caps the container at 75% of host memory. This is an uncompleted test, not a passing or failing numerical comparison.

This PR changes only the tokenizer export utility; the model build/runtime/E2E code is unchanged from main. Local family E2E and the separate image-chat qualification pass, including 55 complete native/HTTP matches and the unchanged 9/10 corpus gate. The protected internal premerge gate passed exact head 121134a9d4de28f7c9bedd2ae8d3eafda52583aa. Larger-host Dev qualification is pending; no check or correctness criterion has been disabled or relaxed.

[yizhuoz004]

Update at current head eed140a43ed1ec49488e08b5a6e30acf572a0b6f: rebased onto current main and added a family pytest allocator default that respects caller settings. A matched GB300 diagnostic with a 21.8 GiB PyTorch budget fails the original FP32 eager reference under the default allocator, then completes under expandable segments with all 30 token IDs and full text exactly matching the earlier uncapped reference. This is a controlled allocator-capacity diagnostic, not an L4 reproduction. No reference operators, precision, prompts, generation controls or numerical gates changed. Current-head 22 family CPU tests pass; fresh standard public and protected CI are required.

The previously approved larger-runner retry belongs to old head c84512364642e36d652046704d48ed7e1df6b545 and retains its normal cleanup. Its result cannot qualify the new head. The earlier public failure evidence follows.

The current head c84512364642e36d652046704d48ed7e1df6b545 fixes the previous host-memory failure: the fresh standard Dev run finishes native build/inference and reaches the unchanged FP32 reference. It then fails in the reference vision attention with CUDA OOM: 22.04 GiB total GPU memory, 192 MiB requested, 149 MiB free. This run has no parity verdict; it is a GPU-capacity failure in the reference, rather than the earlier host OOM.

The same unchanged full E2E passes locally under a 48 GiB/no-swap host-memory limit on a capable GPU. A retry using the existing large Dev profile (one L40S GPU, 128 GiB host RAM) is prepared and awaits the owner's explicit retry authorization. Reference weights, FP32 precision, selected input, and correctness gates remain unchanged. No retry or test deferral has been used to bypass this failure.