[Relax][PyTorch] Add support for decomposed operators and fix IR of ops tests(6)#18420
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Summary of ChangesHello @tlopex, 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 introduces support for decomposed operators within the PyTorch frontend for TVM Relax, specifically addressing and correcting the Intermediate Representation (IR) generated for several key operations. The changes ensure that Highlights
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Code Review
This pull request improves the PyTorch frontend by adding support for decomposed operators and fixing the IR for several ops tests. The changes in _squeeze and _slice handlers make the translation more robust, especially when run_ep_decomposition is enabled. The test suite is updated accordingly, ensuring the correctness of the new decomposed IR for operators like roll, slice, and squeeze. Overall, this is a solid improvement. I have one minor suggestion to improve code style.
| return self.block_builder.emit(relax.op.take(x, index, dim)) | ||
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| def _slice(self, node: fx.Node) -> relax.Var: | ||
| import sys |
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@tvm-bot rerun |
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cc @mshr-h |
This pr fixes ops like
roll,select_slice, andsqueeze.