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_linux_ut.yml
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name: Linux UT Test
on:
workflow_call:
inputs:
pytorch:
required: false
type: string
default: 'main'
description: Pytorch branch/commit
keep_torch_xpu_ops:
required: false
type: string
default: 'false'
description: Keep torch-xpu-ops pin. `true` means use pined commit
triton:
required: false
type: string
default: ''
description: Triton commit. Use pytorch pined commit by default
ut:
required: true
type: string
default: ''
description: UT scope. `op_regression,op_regression_dev1,op_extended,op_ut,torch_xpu` Delimiter is comma
abi:
required: false
type: string
default: 1
description: ABI version. Default abi as 1.
python:
required: false
type: string
default: '3.10'
description: Python version
runner:
required: true
type: string
default: 'linux.idc.xpu'
description: Runner label
driver:
required: false
type: string
default: 'lts'
description: Driver lts/rolling
permissions: read-all
jobs:
Torch-XPU-UT-Tests:
runs-on: ${{ inputs.runner }}
timeout-minutes: 900
env:
NEOReadDebugKeys: ${{ inputs.driver == 'rolling' && '1' || '0' }}
DisableScratchPages: ${{ inputs.driver == 'rolling' && '1' || '0' }}
steps:
- name: Checkout torch-xpu-ops
uses: actions/checkout@v4
- name: Prepare Stock Pytorch
run: |
pwd
which conda && conda clean -ay
conda remove --all -y -n xpu_op_${ZE_AFFINITY_MASK} || \
rm -rf $(dirname ${CONDA_EXE})/../envs/xpu_op_${ZE_AFFINITY_MASK}
conda create -n xpu_op_${ZE_AFFINITY_MASK} python=${{ inputs.python }} cmake ninja -y
source activate xpu_op_${ZE_AFFINITY_MASK}
cd ../ && rm -rf pytorch
pip install requests
git clone https://github.com/pytorch/pytorch pytorch
if [ "${{ inputs.pytorch }}" != "nightly_wheel" ]; then
cd pytorch && git checkout $(echo ${{ inputs.pytorch }})
# apply PRs for stock pytorch
python ../torch-xpu-ops/.github/scripts/apply_torch_pr.py
git status && git show -s
git submodule sync && git submodule update --init --recursive
if [[ ${{ inputs.keep_torch_xpu_ops }} == 'true' ]]; then
echo "Don't replace torch-xpu-ops!"
else
rm -rf third_party/torch-xpu-ops && cp -r ../torch-xpu-ops third_party/
# Workaround for torch-xpu-ops ci test
sed -i "s/checkout --quiet \${TORCH_XPU_OPS_COMMIT}/log -n 1/g" caffe2/CMakeLists.txt
fi
fi
- name: Triton Installation
run: |
source activate xpu_op_${ZE_AFFINITY_MASK}
cd ../pytorch
TRITON_REPO="https://github.com/intel/intel-xpu-backend-for-triton"
if [ -z ${{ inputs.triton }} ]; then
TRITON_COMMIT_ID="$(<.ci/docker/ci_commit_pins/triton-xpu.txt)"
else
TRITON_COMMIT_ID="${{ inputs.triton }}"
fi
echo ${TRITON_REPO}@${TRITON_COMMIT_ID}
if [ "${{ inputs.pytorch }}" != "nightly_wheel" ]; then
pip install --force-reinstall "git+${TRITON_REPO}@${TRITON_COMMIT_ID}#subdirectory=python"
fi
- name: Build Pytorch XPU
run: |
source activate xpu_op_${ZE_AFFINITY_MASK}
source .github/scripts/env.sh ${{ inputs.pytorch }}
pip install mkl-static==2025.0.1 mkl-include==2025.0.1
if [[ ${{ inputs.abi }} == '0' ]]; then
export _GLIBCXX_USE_CXX11_ABI=0
else
export _GLIBCXX_USE_CXX11_ABI=1
fi
if [ "${{ inputs.pytorch }}" != "nightly_wheel" ]; then
cd ../pytorch
export CMAKE_PREFIX_PATH=${CMAKE_PREFIX_PATH}:${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
pip install -r requirements.txt
WERROR=1 python setup.py bdist_wheel
pip install --force-reinstall dist/*.whl
git clone https://github.com/pytorch/vision && cd vision && python setup.py install && cd ..
else
pip install torch torchvision torchaudio --pre --index-url https://download.pytorch.org/whl/nightly/xpu
TORCH_COMMIT_ID=$(python -c 'import torch; print(torch.version.git_version)')
cd ../pytorch
git reset --hard && git checkout ${TORCH_COMMIT_ID}
TORCH_XPU_OPS_COMMIT=$(<third_party/xpu.txt)
rm -rf third_party/torch-xpu-ops
git clone https://github.com/intel/torch-xpu-ops.git third_party/torch-xpu-ops
cd third_party/torch-xpu-ops
git checkout ${TORCH_XPU_OPS_COMMIT}
cd ../..
fi
pip install -r .ci/docker/requirements-ci.txt
- name: Torch Config
run: |
source activate xpu_op_${ZE_AFFINITY_MASK}
source .github/scripts/env.sh ${{ inputs.pytorch }}
python -c "import torch; print(torch.__config__.show())"
python -c "import torch; print(torch.__config__.parallel_info())"
python -c "import torch; print(torch.__config__.torch.xpu.device_count())"
python -c "import triton; print(triton.__version__)"
cd ..
python pytorch/torch/utils/collect_env.py
rm -rf /tmp/torchinductor_*
rm -rf ~/.triton/cache
- name: Run XPU OP Examples
if: contains(inputs.ut, 'op_regression') || github.event_name == 'schedule'
run: |
cd ${{ github.workspace }}
xpu-smi discovery
source .github/scripts/env.sh ${{ inputs.pytorch }}
source activate xpu_op_${ZE_AFFINITY_MASK}
cd ${{ github.workspace }}
cd test/regressions
pip install pytest
timeout 8000 pytest -v
- name: Run XPU OP Regressions test on device 1
if: contains(inputs.ut, 'op_regression_dev1') || github.event_name == 'schedule'
run: |
cd ${{ github.workspace }}
xpu-smi discovery
source .github/scripts/env.sh ${{ inputs.pytorch }}
source activate xpu_op_${ZE_AFFINITY_MASK}
export ZE_AFFINITY_MASK_OLD=${ZE_AFFINITY_MASK}
unset ZE_AFFINITY_MASK
cd ${{ github.workspace }}
cd test/regressions
pip install pytest
timeout 8000 pytest -v test_operation_on_device_1.py
export ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK_OLD}
- name: Run XPU OP Extended UT
if: contains(inputs.ut, 'op_extended') || github.event_name == 'schedule'
run: |
source .github/scripts/env.sh ${{ inputs.pytorch }}
source activate xpu_op_${ZE_AFFINITY_MASK}
export PYTORCH_TEST_WITH_SLOW=1
cd ../pytorch/third_party/torch-xpu-ops/test/xpu/extended/
timeout 10000 python run_test_with_skip.py
- name: Run XPU OP UT
if: contains(inputs.ut, 'op_ut') || github.event_name == 'schedule'
run: |
source .github/scripts/env.sh ${{ inputs.pytorch }}
source activate xpu_op_${ZE_AFFINITY_MASK}
export PYTORCH_ENABLE_XPU_FALLBACK=1
export PYTORCH_TEST_WITH_SLOW=1
cd ../pytorch/third_party/torch-xpu-ops/test/xpu
timeout 10000 python run_test_with_skip.py
# Cases run with a on-demand white list, since some suites are too
# slow to go through all operators on CPU. So add cases on-demand
# when XPU implementatoin is done.
# test_foreach, test_decomp
timeout 10000 python run_test_with_only.py
- name: Run Torch XPU UT
if: contains(inputs.ut, 'torch_xpu') || github.event_name == 'schedule'
run: |
source .github/scripts/env.sh ${{ inputs.pytorch }}
source activate xpu_op_${ZE_AFFINITY_MASK}
cd ../pytorch
TEST_REPORTS_DIR=$(pwd)/test/test-reports
rm -rf "$TEST_REPORTS_DIR" && mkdir -p "$TEST_REPORTS_DIR"
# Run Pytorch XPU binary UT
for xpu_case in build/bin/*{xpu,sycl}*; do
if [[ "$xpu_case" != *"*"* && "$xpu_case" != *.so && "$xpu_case" != *.a ]]; then
case_name=$(basename "$xpu_case")
echo "Testing ${case_name} ..."
"$xpu_case" --gtest_output=xml:"$TEST_REPORTS_DIR"/"$case_name".xml
fi
done
# Run Pytorch XPU python UT
export PYTORCH_TEST_WITH_SLOW=1
export PYTORCH_TESTING_DEVICE_ONLY_FOR="xpu"
test_cmd="python test/run_test.py --include "
# All Inductor UT under test/inductor
for test in $(ls test/inductor | grep test);
do
test_cmd="${test_cmd} inductor/$test";
done
# All xpu ut under test/xpu
for test in $(ls test/xpu | grep test);
do
test_cmd="${test_cmd} xpu/$test";
done
if [ -f "test/test_xpu.py" ]; then
test_cmd="${test_cmd} test_xpu.py"
fi
eval $test_cmd