[Relax][PyTorch] Fix _slice and _expand for dynamic shapes in PyTorch ExportedProgram frontend#18918
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… ExportedProgram frontend Fixes two issues when translating PyTorch models with dynamic shapes: 1. **_slice**: Resolve `fx.Node` references in start/end/step arguments and detect identity slices where the symbolic end equals the tensor dimension (avoids redundant `strided_slice` ops). 2. **_expand**: Fall back to FX node metadata when `shape_of()` returns `None` for tensors with unknown shapes.
Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request enhances the PyTorch ExportedProgram frontend's ability to correctly handle dynamic shapes by improving the translation of Highlights
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Code Review
This pull request addresses issues with dynamic shapes in the PyTorch frontend for _slice and _expand operations. The _slice operator is updated to resolve symbolic arguments and to identify and elide identity slices with dynamic shapes, which avoids creating redundant strided_slice operations. The _expand operator is enhanced with a fallback mechanism to use shape information from FX node metadata when it's not available at the Relax level. The changes are accompanied by new tests that verify the correct handling of symbolic shapes for slicing.
Fixes two issues when translating PyTorch models with dynamic shapes:
_slice: Resolve
fx.Nodereferences in start/end/step arguments and detect identity slices where the symbolic end equals the tensor dimension (avoids redundantstrided_sliceops)._expand: Fall back to FX node metadata when
shape_of()returnsNonefor tensors with unknown shapes.