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Install patch in the docker (#60)
Summary: Now we have to patch third-party submodules like hstu and xformers, install the patch utility to the CI docker. Pull Request resolved: #60 Test Plan: CI https://github.com/pytorch-labs/tritonbench/actions/runs/11946317137 Reviewed By: FindHao Differential Revision: D66273502 Pulled By: xuzhao9 fbshipit-source-id: 78552c53b7d0de008081c4fc94851308bff4350a
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.ci/tritonbench/test-gpu.sh

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@@ -8,11 +8,4 @@ fi
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. "${SETUP_SCRIPT}"
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# FIXME: patch and install hstu
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sudo apt-get install -y patch
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python install.py --hstu
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# FIXME: install colfax
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python install.py --colfax
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python -m unittest test.test_gpu.main -v

docker/tritonbench-nightly.dockerfile

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# Tritonbench library build and test require libcuda.so.1
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# which is from NVIDIA driver
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RUN sudo apt update && sudo apt-get install -y libnvidia-compute-550 patchelf
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RUN sudo apt update && sudo apt-get install -y libnvidia-compute-550 patchelf patch
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# Install Tritonbench
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RUN cd /workspace/tritonbench && \

tools/cuda_utils.py

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]
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cmd = ["conda", "install", "-y"] + torch_deps
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subprocess.check_call(cmd)
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# conda forge deps
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# ubuntu 22.04 comes with libstdcxx6 12.3.0
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# we need to install the same library version in conda
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conda_deps = ["libstdcxx-ng=12.3.0"]
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cmd = ["conda", "install", "-y", "-c", "conda-forge"] + conda_deps
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subprocess.check_call(cmd)
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def install_torch_build_deps(cuda_version: str):

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