chore: import upstream snapshot with attribution
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@@ -0,0 +1,28 @@
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#!/bin/bash
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set -eux
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python_executable=python$1
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cuda_home=/usr/local/cuda-$2
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# Update paths
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PATH=${cuda_home}/bin:$PATH
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LD_LIBRARY_PATH=${cuda_home}/lib64:$LD_LIBRARY_PATH
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# Install requirements
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if [ "$(echo "$2" | cut -d. -f1)" = "12" ]; then
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sed -i 's/^nvidia-cutlass-dsl\[cu13\]>=/nvidia-cutlass-dsl>=/' requirements/cuda.txt
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fi
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$python_executable -m pip install -r requirements/build/cuda.txt -r requirements/cuda.txt
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# Limit the number of parallel jobs to avoid OOM
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export MAX_JOBS=1
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# Make sure release wheels are built for the following architectures
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# Do not add +PTX here: vLLM filters torch's top-level PTX flag when it
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# converts global gencode flags into per-kernel arch lists. If a specific
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# kernel needs PTX, add +PTX to that kernel's CMake arch list instead.
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export TORCH_CUDA_ARCH_LIST="7.5 8.0 8.6 8.9 9.0 10.0 12.0"
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bash tools/check_repo.sh
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# Build
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$python_executable setup.py bdist_wheel --dist-dir=dist
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