[AutoBump] Merge with 4d7cdba4 (May 22) (44) #277
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This commit fixes the onnx.MaxPool op lowering which was lacking the indices result support. Signed-Off By: Vivek Khandelwal <[email protected]>
ensures stability of results between different set ups
…tend (llvm#3376) Discord Thread: https://discord.com/channels/636084430946959380/1238330633328005243 ## Context: [This](https://github.com/llvm/torch-mlir/blob/main/python/torch_mlir/fx.py#L61) was updated to support e2e tests for the TorchDynamo frontend in Torch-MLIR, where we run FX decompositions and import the FX IR to generate Torch dialect, followed by `torch-function-to-torch-backend-pipeline`, skipping only the shape/type refinement for now. However, we should be able to skip many of the torch simplification passes, as depicted in the [frontend roadmap](https://github.com/llvm/torch-mlir/blob/main/docs/images/roadmap_frontend.png). Based on IREE's TorchDynamo [pipeline](https://github.com/iree-org/iree/blob/main/compiler/plugins/input/Torch/InputConversion/Passes.cpp#L29), the only two passes we seem to require are: `ReduceOpVariantsPass` and `DecomposeComplexOpsPass`. This is inline with our findings as well based on initial exploration. This PR creates a dedicated frontend simplification pipeline for TorchDynamo / FX Importer which calls only `ReduceOpVariantsPass` and `DecomposeComplexOpsPass`. We rely on the e2e fx_importer tests to ensure we're not regressing by removing many of the passes that were historically needed for TorchScript. One notable change here is that we do not call the `LowerToBackendContractPass` anymore, which used to call `TorchSimplificationPipeline` iteratively until VerifyBackendContract was clean. Some of this was required for the shape/type refinement to converge, which seems a non-issue for Dynamo frontend. Do we anticipate this (the iterative invocation of TorchSimplificationPipeline followed by VerifyBackendContract) to be worth retaining in the Dynamo frontend pipeline? If so, I can make those changes, PLMK.
This commit fixes the bugs for the `onnx.OneHot` operator by: 1) Converting negative indices to non-negative indices 2) Handling both `int` and `float` types for `off` and `on` values 3) Using the correct result type It also includes a new unit test.
…uOp (llvm#3330) I am trying to eliminate 'getWithLeastStaticInformation' in DecomposeAtenTriuOp. Could you provide me with some suggestions? @qingyunqu @zjgarvey See issue llvm#3312
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