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torch-mlir/torchvision-requirements.txt

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build: Update Roll PyTorch version (#3548) This commit also updates the PyTorch and Torchvision nightly links since they are now moved to a different location. PyTorch Nightly: https://download.pytorch.org/whl/nightly/cpu/torch/ Torchvision Nightly: https://download.pytorch.org/whl/nightly/cpu/torchvision/ Disables dtype checks for some ops, tracked by https://github.com/llvm/torch-mlir/issues/3552 Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
2024-07-20 00:08:57 +08:00
-f https://download.pytorch.org/whl/nightly/cpu/torchvision/
python: separate build- and test-related pip dependencies (#1874) We want to ensure that pip packages required for building torch-mlir should be included in the dependencies of torch-mlir, but we don't want the pip packages required for _testing_ of torch-mlir to be included among the dependencies. To be able to specify and install one set of dependencies and not the other, this patch separates the pip packages into two files: build-requirements.txt and test-requirements.txt. This patch also updates references to the requirements.txt file so that CI builds that run end-to-end tests install test-related pip dependencies while everything else (including WHL builds) sticks to just the build-related pip dependencies. Despite this change, this patch should not affect a torch-mlir developer's workflow. More precisely, since this patch makes the top-level requirements.txt file refer to both build-requirements.txt and test-requirements.txt files, a torch-mlir developer should be able to continue referring to the requirements.txt file without any impact.
2023-02-14 11:22:09 +08:00
--pre
build: manually update PyTorch version and fix CI failure (#3830) This commit sets the PyTorch and TorchVision version to nightly release 2024-10-29. This commit also fixes the CI failure after this commit https://github.com/llvm/torch-mlir/commit/54d9e2401376e7eb2c6c219e3b3555f45f8b2635 got merged. The issue was that the CI checks in the PR were run before the previous roll pytorch update but the PR was actually merged after the roll pytorch update. Hence, the failure was not caught before merging the PR. While exporting the fx_graph through fx_importer for `rrelu` and `rrelu_with_noise` op for train mode, it decomposes the `aten.rrelu_with_noise` op based on the PyTorch decomposition which is the default behavior. However, the decomposition contains an input mutation specifically here https://github.com/pytorch/pytorch/blob/9bbe4a67ad137032add6a3b0b74bda66f5ef83d2/torch/_decomp/decompositions.py#L325, resulting in the runtime failure. This issue would probably be fixed by https://github.com/pytorch/pytorch/pull/138503. Until then, the failing tests are added to the xfail set. Also, after the roll pytorch update following tests started passing for fx_importer, and fx_importer_stablehlo config. - "ElementwiseRreluTrainModule_basic" - "ElementwiseRreluTrainStaticModule_basic" - "ElementwiseRreluWithNoiseTrainModule_basic" - "ElementwiseRreluWithNoiseTrainStaticModule_basic" This commit also updates the dtype check for the `aten.linear` op since the op now expects both the input tensors to have the same dtype. Signed-Off By: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>
2024-10-30 21:26:01 +08:00
torchvision==0.20.0.dev20241029