feat: support in-place plugins - #4279
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narendasan
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Convert in-place QDP plugins by registering a converter on the auto_functionalized(_v2) higher-order wrapper (gated by a capability_validator to the ops that have a plugin) instead of reversing functionalization in a lowering pass. The graph stays functional and scoping is per-node. - Add _auto_functionalized_converter: wrapper converter that reconstructs the inner op's args, delegates to the inner op's converter, and returns the [*returns, *bases] tuple with a faithful base->return alias map; plus a scoped no-op converter for the aliased write-back copy_. - Add qdp_inplace_metadata pass: metadata-only (no graph reversal) so pre-conversion symbolic-shape extraction handles the direct-return case. - Remove unfunctionalize_qdp_inplace: its global copy_ deletion corrupted mixed graphs (a non-plugin in-place op's write-back was dropped). All in-place tests pass (5/5); full plugin+kernels suite green (57 passed).
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| try: | ||
| from torch._subclasses.fake_tensor import FakeTensorMode | ||
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| with FakeTensorMode(): |
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Do you know if FakeTensorUpdator would work here?
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@narendasan To be honest, FakeTensorUpdater is used to propagate and update the meta values but here we want to find the aliased map, we could use it but we still need to find the aliasing here.
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Description
End-to-end support for in-place QDP plugins in torch-tensorrt
Fixes #4240
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