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Edward Z. Yang
0e3031f7e7
Functionalize and compute joint simultaneously. (#88063)
This also comes with some bug fixes that were uncovered from doing this: - Forward device calls to inner tensor in FunctionalTensorWrapper - Make legacyExtractDispatchKey exclude Functionalize, so that it can get at the real device type key. This is noncontroversial. - Stop stripping dense from key set. The reason for this is FunctionalWrapperTensor may be used in contexts where people query if it is dense or not. If it doesn't report this correctly (from the dispatch key), it will cause errors. This caused some torchbench models to fail when I did one-pass tracing. - Save and restore reapply views TLS correctly Signed-off-by: Edward Z. Yang <ezyang@fb.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/88063 Approved by: https://github.com/bdhirsh |
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conda | Remove incorrect links to zdevito/ATen (#50065) | 3 years ago | |||||||||
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src | Functionalize and compute joint simultaneously. (#88063) | 1 year ago | |||||||||
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tools | Add cuda_atomic_ops_test to run_tests.sh | 2 years ago | |||||||||
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CMakeLists.txt | [MPS] Fix printTensor() for MPS (#86534) | 1 year ago | |||||||||
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Tensors and Dynamic neural networks in Python with strong GPU acceleration
C++ Python Cuda Text C other
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