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regro-cf-autotick-both-vetinariweiji14
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flash-attn v2.8.2 + CUDA 12.9 (#38)
* updated v2.8.2 * MNT: Re-rendered with conda-build 25.5.0, conda-smithy 3.51.1, and conda-forge-pinning 2025.07.24.10.11.14 * drop CUDA 11.8 leftovers * Upgrade to CUDA 12.9 CUDA 12.8 added support for architectures `sm_100`, `sm_101` and `sm_120`, while CUDA 12.9 further added `sm_103` and `sm_121`. To build for these, maintainers will need to modify their existing list of specified architectures (e.g. `CMAKE_CUDA_ARCHITECTURES`, `TORCH_CUDA_ARCH_LIST`, etc.) for their package. A good balance between broad support and storage footprint (resp. compilation time) is to add `sm_100` and `sm_120`. Since CUDA 12.8, the conda-forge nvcc package now sets `CUDAARCHS` and `TORCH_CUDA_ARCH_LIST` in its activation script to a string containing all of the supported real architectures plus the virtual architecture of the latest. Recipes for packages who use these variables to control their build but do not want to build for all supported architectures will need to override these variables in their build script. ref: https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html#new-features * MNT: Re-rendered with conda-build 25.4.2, conda-smithy 3.51.1, and conda-forge-pinning 2025.07.26.20.42.37 * update CUDA arches * Update setup.py for flash-attention v2.8.2 Xref https://github.com/Dao-AILab/flash-attention/blame/v2.8.2/setup.py --------- Co-authored-by: h-vetinari <[email protected]> Co-authored-by: Wei Ji <[email protected]>
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