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Use binary wheels for Torch#252
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| else | ||
| # sm_101 has been renamed to sm_110 in CUDA 13. | ||
| "7.5;8.0;8.6;8.9;9.0;10.0;11.0;12.0"; | ||
| TORCH_CUDA_ARCH_LIST = lib.concatStringsSep ";" torch.cudaCapabilities; |
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much cleaner ! very nice
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Temporarily put into draft, let's wait until Torch 2.9 is out and we can also immediately get 2.9 from wheels. |
We were pulling in cutlass-sycl for CUDA builds because the dependendies were not filtered by backend/framework.
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Very cool! only few very small nits
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| # PyTorch 2.6 and CUDA 12.6 | ||
| export PYTHONPATH="result/torch26-cxx11-cu126-x86_64-linux" | ||
| export PYTHONPATH="result/torch29-cxx11-cu126-x86_64-linux" |
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Small nit : the torch version in the comment
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👍 I'll update the comments in a separate PR
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| "12.4") CUDA_TAG="cu124" ;; \ | ||
| "12.6") CUDA_TAG="cu126" ;; \ | ||
| "12.8") CUDA_TAG="cu128" ;; \ | ||
| "13.0") CUDA_TAG="cu130" ;; \ |
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we also have 12.9 for torch 2.8 I think
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But we are only testing with 2.9.
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| # Ideally we'd test with 11.8, but the GELU kernel is subtly off. | ||
| ARG CUDA_VERSION=12.1.0 | ||
| ARG UBUNTU_VERSION=18.04 | ||
| ARG TORCH_VERSION=2.5.0 | ||
| ARG CUDA_VERSION=12.6.0 | ||
| ARG UBI_VERSION=8 | ||
| ARG TORCH_VERSION=2.9.0 |
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nit : the comment needs to be updated too I think
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