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Benjamin Glass 5aa5a5763e [inductor triton] Disable incorrect TF32 usage on CUDA capability < 8 (#145684) 
Triton 2.2 and greater have a bug where allowing TF32 generation for a GPU that does not support TF32 will cause code generation errors. Patch around this problem by:

1. Adding a function to `torch.cuda` that determines whether CUDA hardware is capable of using the TF32 format.
2. Using that function to explicitly disable TF32 generation when calling Triton, where needed.

To demonstrate that this fix works, try running `test/inductor/test_max_autotune.py` on a GPU with CUDA compute capability < 8 (e.g. any NVIDIA consumer GPU) without this fix.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/145684
Approved by: https://github.com/eqy
2025-01-28 22:01:08 +00:00
..
cpp docs: get rid of copyright year (#144562) 2025-01-10 19:57:25 +00:00
source [inductor triton] Disable incorrect TF32 usage on CUDA capability < 8 (#145684) 2025-01-28 22:01:08 +00:00
.gitignore
libtorch.rst Add ROCm documentation to libtorch (C++) reST. (#136378) 2024-09-25 02:30:56 +00:00
make.bat
Makefile [ONNX] Update images and APIs to onnx_dynamo.rst (#144358) 2025-01-08 21:44:43 +00:00
README.md
requirements.txt Revert "Fix deprecated pytorch_sphinx_theme editable installation (#145347)" 2025-01-23 20:06:07 +00:00

README.md

Please see the Writing documentation section of CONTRIBUTING.md for details on both writing and building the docs.