mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-06 00:20:18 +01:00
4b8b7c7fb9
As in title
idk how the install_cmake script is used because I see it being called with 3.18 but when I look at the build jobs some say 3.18 and others 3.31
Just make everything install cmake via the requirements-ci.txt. I don't know if the comment at 5d36485b4a/.ci/docker/common/install_conda.sh (L78) still holds, but pretty much every build has CONDA_CMAKE set to true, so I'm just defaulting to installing through pip
Also defaulting to 4.0.0 everywhere except the executorch docker build because executorch reinstalls 3.31.something
Pull Request resolved: https://github.com/pytorch/pytorch/pull/152537
Approved by: https://github.com/cyyever, https://github.com/atalman, https://github.com/malfet
96 lines
3.2 KiB
Bash
Executable File
96 lines
3.2 KiB
Bash
Executable File
#!/bin/bash
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set -ex
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mkdir -p /opt/triton
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if [ -z "${TRITON}" ] && [ -z "${TRITON_CPU}" ]; then
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echo "TRITON and TRITON_CPU are not set. Exiting..."
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exit 0
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fi
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source "$(dirname "${BASH_SOURCE[0]}")/common_utils.sh"
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get_pip_version() {
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conda_run pip list | grep -w $* | head -n 1 | awk '{print $2}'
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}
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if [ -n "${XPU_VERSION}" ]; then
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TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
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TRITON_TEXT_FILE="triton-xpu"
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elif [ -n "${TRITON_CPU}" ]; then
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TRITON_REPO="https://github.com/triton-lang/triton-cpu"
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TRITON_TEXT_FILE="triton-cpu"
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else
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TRITON_REPO="https://github.com/triton-lang/triton"
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TRITON_TEXT_FILE="triton"
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fi
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# The logic here is copied from .ci/pytorch/common_utils.sh
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TRITON_PINNED_COMMIT=$(get_pinned_commit ${TRITON_TEXT_FILE})
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if [ -n "${UBUNTU_VERSION}" ];then
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apt update
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apt-get install -y gpg-agent
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fi
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# Keep the current cmake and numpy version here, so we can reinstall them later
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CMAKE_VERSION=$(get_pip_version cmake)
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NUMPY_VERSION=$(get_pip_version numpy)
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if [ -z "${MAX_JOBS}" ]; then
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export MAX_JOBS=$(nproc)
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fi
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# Git checkout triton
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mkdir /var/lib/jenkins/triton
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chown -R jenkins /var/lib/jenkins/triton
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chgrp -R jenkins /var/lib/jenkins/triton
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pushd /var/lib/jenkins/
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as_jenkins git clone --recursive ${TRITON_REPO} triton
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cd triton
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as_jenkins git checkout ${TRITON_PINNED_COMMIT}
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as_jenkins git submodule update --init --recursive
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cd python
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pip_install pybind11==2.13.6
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# TODO: remove patch setup.py once we have a proper fix for https://github.com/triton-lang/triton/issues/4527
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as_jenkins sed -i -e 's/https:\/\/tritonlang.blob.core.windows.net\/llvm-builds/https:\/\/oaitriton.blob.core.windows.net\/public\/llvm-builds/g' setup.py
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if [ -n "${UBUNTU_VERSION}" ] && [ -n "${GCC_VERSION}" ] && [[ "${GCC_VERSION}" == "7" ]]; then
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# Triton needs at least gcc-9 to build
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apt-get install -y g++-9
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CXX=g++-9 conda_run python setup.py bdist_wheel
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elif [ -n "${UBUNTU_VERSION}" ] && [ -n "${CLANG_VERSION}" ]; then
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# Triton needs <filesystem> which surprisingly is not available with clang-9 toolchain
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add-apt-repository -y ppa:ubuntu-toolchain-r/test
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apt-get install -y g++-9
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CXX=g++-9 conda_run python setup.py bdist_wheel
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else
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conda_run python setup.py bdist_wheel
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fi
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# Copy the wheel to /opt for multi stage docker builds
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cp dist/*.whl /opt/triton
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# Install the wheel for docker builds that don't use multi stage
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pip_install dist/*.whl
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# TODO: This is to make sure that the same cmake and numpy version from install conda
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# script is used. Without this step, the newer cmake version (3.25.2) downloaded by
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# triton build step via pip will fail to detect conda MKL. Once that issue is fixed,
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# this can be removed.
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#
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# The correct numpy version also needs to be set here because conda claims that it
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# causes inconsistent environment. Without this, conda will attempt to install the
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# latest numpy version, which fails ASAN tests with the following import error: Numba
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# needs NumPy 1.20 or less.
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# Note that we install numpy with pip as conda might not have the version we want
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if [ -n "${CMAKE_VERSION}" ]; then
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pip_install "cmake==${CMAKE_VERSION}"
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fi
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if [ -n "${NUMPY_VERSION}" ]; then
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pip_install "numpy==${NUMPY_VERSION}"
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fi
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