mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
6590f4fb0e
Enable python 3.13 for XPU nightly build, it depends on https://github.com/pytorch/pytorch/pull/133454 land. Also update the xpu nightly wheel test env. Works for https://github.com/pytorch/pytorch/issues/114850 Fixes #130543 Pull Request resolved: https://github.com/pytorch/pytorch/pull/133670 Approved by: https://github.com/atalman, https://github.com/malfet
137 lines
4.8 KiB
Bash
Executable File
137 lines
4.8 KiB
Bash
Executable File
#!/bin/bash
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OUTPUT_SCRIPT=${OUTPUT_SCRIPT:-/home/circleci/project/ci_test_script.sh}
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# only source if file exists
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if [[ -f /home/circleci/project/env ]]; then
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source /home/circleci/project/env
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fi
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cat >"${OUTPUT_SCRIPT}" <<EOL
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# =================== The following code will be executed inside Docker container ===================
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set -eux -o pipefail
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retry () {
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"\$@" || (sleep 1 && "\$@") || (sleep 2 && "\$@")
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}
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# Source binary env file here if exists
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if [[ -e "${BINARY_ENV_FILE:-/nofile}" ]]; then
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source "${BINARY_ENV_FILE:-/nofile}"
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fi
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python_nodot="\$(echo $DESIRED_PYTHON | tr -d m.u)"
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# Set up Python
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if [[ "$PACKAGE_TYPE" == conda ]]; then
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retry conda create -qyn testenv python="$DESIRED_PYTHON"
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source activate testenv >/dev/null
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elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
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python_path="/opt/python/cp\$python_nodot-cp\${python_nodot}"
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# Prior to Python 3.8 paths were suffixed with an 'm'
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if [[ -d "\${python_path}/bin" ]]; then
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export PATH="\${python_path}/bin:\$PATH"
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elif [[ -d "\${python_path}m/bin" ]]; then
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export PATH="\${python_path}m/bin:\$PATH"
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fi
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fi
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EXTRA_CONDA_FLAGS=""
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NUMPY_PIN=""
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PROTOBUF_PACKAGE="defaults::protobuf"
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if [[ "\$python_nodot" = *310* ]]; then
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# There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
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# we set a lower boundary here just to be safe
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NUMPY_PIN=">=1.21.2"
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PROTOBUF_PACKAGE="protobuf>=3.19.0"
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fi
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if [[ "\$python_nodot" = *39* ]]; then
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# There's an issue with conda channel priority where it'll randomly pick 1.19 over 1.20
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# we set a lower boundary here just to be safe
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NUMPY_PIN=">=1.20"
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fi
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# Move debug wheels out of the package dir so they don't get installed
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mkdir -p /tmp/debug_final_pkgs
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mv /final_pkgs/debug-*.zip /tmp/debug_final_pkgs || echo "no debug packages to move"
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# Install the package
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# These network calls should not have 'retry's because they are installing
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# locally and aren't actually network calls
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# TODO there is duplicated and inconsistent test-python-env setup across this
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# file, builder/smoke_test.sh, and builder/run_tests.sh, and also in the
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# conda build scripts themselves. These should really be consolidated
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# Pick only one package of multiple available (which happens as result of workflow re-runs)
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pkg="/final_pkgs/\$(ls -1 /final_pkgs|sort|tail -1)"
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if [[ "\$PYTORCH_BUILD_VERSION" == *dev* ]]; then
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CHANNEL="nightly"
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else
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CHANNEL="test"
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fi
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if [[ "$PACKAGE_TYPE" == conda ]]; then
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(
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# For some reason conda likes to re-activate the conda environment when attempting this install
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# which means that a deactivate is run and some variables might not exist when that happens,
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# namely CONDA_MKL_INTERFACE_LAYER_BACKUP from libblas so let's just ignore unbound variables when
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# it comes to the conda installation commands
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set +u
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retry conda install \${EXTRA_CONDA_FLAGS} -yq \
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"numpy\${NUMPY_PIN}" \
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mkl>=2018 \
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ninja \
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sympy>=1.12 \
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typing-extensions \
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${PROTOBUF_PACKAGE}
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if [[ "$DESIRED_CUDA" == 'cpu' ]]; then
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retry conda install -c pytorch -y cpuonly
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else
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cu_ver="${DESIRED_CUDA:2:2}.${DESIRED_CUDA:4}"
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CUDA_PACKAGE="pytorch-cuda"
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retry conda install \${EXTRA_CONDA_FLAGS} -yq -c nvidia -c "pytorch-\${CHANNEL}" "pytorch-cuda=\${cu_ver}"
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fi
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conda install \${EXTRA_CONDA_FLAGS} -y "\$pkg" --offline
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)
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elif [[ "$PACKAGE_TYPE" != libtorch ]]; then
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if [[ "\$BUILD_ENVIRONMENT" != *s390x* ]]; then
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if [[ "$USE_SPLIT_BUILD" == "true" ]]; then
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pkg_no_python="$(ls -1 /final_pkgs/torch_no_python* | sort |tail -1)"
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pkg_torch="$(ls -1 /final_pkgs/torch-* | sort |tail -1)"
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# todo: after folder is populated use the pypi_pkg channel instead
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pip install "\$pkg_no_python" "\$pkg_torch" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}_pypi_pkg"
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retry pip install -q numpy protobuf typing-extensions
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else
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pip install "\$pkg" --index-url "https://download.pytorch.org/whl/\${CHANNEL}/${DESIRED_CUDA}"
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retry pip install -q numpy protobuf typing-extensions
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fi
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else
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pip install "\$pkg"
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retry pip install -q numpy protobuf typing-extensions
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fi
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fi
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if [[ "$PACKAGE_TYPE" == libtorch ]]; then
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pkg="\$(ls /final_pkgs/*-latest.zip)"
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unzip "\$pkg" -d /tmp
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cd /tmp/libtorch
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fi
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if [[ "$GPU_ARCH_TYPE" == xpu ]]; then
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# Refer https://www.intel.com/content/www/us/en/developer/articles/tool/pytorch-prerequisites-for-intel-gpu/2-5.html
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source /opt/intel/oneapi/pytorch-gpu-dev-0.5/oneapi-vars.sh
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source /opt/intel/oneapi/pti/latest/env/vars.sh
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fi
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# Test the package
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/builder/check_binary.sh
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# Clean temp files
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cd /builder && git clean -ffdx
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# =================== The above code will be executed inside Docker container ===================
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EOL
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echo
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echo
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echo "The script that will run in the next step is:"
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cat "${OUTPUT_SCRIPT}"
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