Torch Nightly WHL Tests #154
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| name: Torch Nightly WHL Tests | |
| on: | |
| schedule: | |
| # GMT+8 21:00 every workday | |
| - cron: '0 14 * * 0-4' | |
| # GMT+8 0:00 Saturday | |
| - cron: '0 17 * * 5' | |
| workflow_dispatch: | |
| inputs: | |
| pytorch: | |
| required: false | |
| type: string | |
| default: 'nightly' | |
| description: Pytorch branch/commit | |
| ut: | |
| required: false | |
| type: string | |
| default: 'torch_xpu' | |
| description: UT scope. `op_regression,op_regression_dev1,op_extended,op_ut,torch_xpu`. Delimiter is comma | |
| suite: | |
| required: true | |
| type: string | |
| default: 'huggingface' | |
| description: Dynamo benchmarks test suite. `huggingface,timm_models,torchbench`. Delimiter is comma | |
| dt: | |
| required: true | |
| type: string | |
| default: 'float32' | |
| description: Data precision of the test. `float32,bfloat16,float16,amp_bf16,amp_fp16`. Delimiter is comma | |
| mode: | |
| required: true | |
| type: string | |
| default: 'inference' | |
| description: Test mode. `inference,training`. Delimiter is comma | |
| scenario: | |
| required: true | |
| type: string | |
| default: 'accuracy' | |
| description: Test scenario. `accuracy,performance`. Delimiter is comma | |
| model: | |
| required: false | |
| type: string | |
| default: '' | |
| description: Model. Will only run this one mode if set | |
| python: | |
| required: false | |
| type: string | |
| default: '3.10' | |
| description: Python version | |
| permissions: read-all | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.sha }}-${{ github.event_name }}-${{ inputs.pytorch }}-${{ inputs.ut }}-${{ inputs.suite }}-${{ inputs.dt }}-${{ inputs.mode }}-${{ inputs.scenario }}-${{ inputs.model }}-${{ inputs.python }} | |
| cancel-in-progress: true | |
| jobs: | |
| Linux-Nightly-Ondemand-UT-WHL-Tests: | |
| uses: ./.github/workflows/_linux_ut.yml | |
| with: | |
| ut: ${{ github.event_name == 'schedule' && 'op_regression,op_regression_dev1,op_extended,op_ut,torch_xpu' || inputs.ut }} | |
| python: ${{ github.event_name == 'schedule' && '3.10' || inputs.python }} | |
| pytorch: nightly_wheel | |
| runner: e2e_internal | |
| Linux-Nightly-Ondemand-E2E-WHL-Tests: | |
| runs-on: e2e_internal | |
| # Don't run on forked repos | |
| if: github.repository_owner == 'intel' | |
| timeout-minutes: 36000 | |
| env: | |
| pytorch: ${{ github.event_name == 'schedule' && 'nightly' || inputs.pytorch }} | |
| ut: ${{ github.event_name == 'schedule' && 'op_regression,op_regression_dev1,op_extended,op_ut,torch_xpu' || inputs.ut }} | |
| python: ${{ github.event_name == 'schedule' && '3.10' || inputs.python }} | |
| outputs: | |
| TORCH_BRANCH_ID: ${{ steps.installed.outputs.TORCH_BRANCH_ID }} | |
| TORCH_COMMIT_ID: ${{ steps.installed.outputs.TORCH_COMMIT_ID }} | |
| TORCH_XPU_OPS_COMMIT: ${{ steps.installed.outputs.TORCH_XPU_OPS_COMMIT }} | |
| TORCHBENCH_COMMIT_ID: ${{ steps.pinned.outputs.TORCHBENCH_COMMIT_ID }} | |
| TORCHVISION_COMMIT_ID: ${{ steps.pinned.outputs.TORCHVISION_COMMIT_ID }} | |
| TORCHAUDIO_COMMIT_ID: ${{ steps.pinned.outputs.TORCHAUDIO_COMMIT_ID }} | |
| TRANSFORMERS_VERSION: ${{ steps.pinned.outputs.TRANSFORMERS_VERSION }} | |
| TIMM_COMMIT_ID: ${{ steps.pinned.outputs.TIMM_COMMIT_ID }} | |
| TRITON_COMMIT_ID: ${{ steps.pinned.outputs.TRITON_COMMIT_ID }} | |
| DRIVER_VERSION: ${{ steps.pinned.outputs.DRIVER_VERSION }} | |
| KERNEL_VERSION: ${{ steps.pinned.outputs.KERNEL_VERSION }} | |
| BUNDLE_VERSION: ${{ steps.pinned.outputs.BUNDLE_VERSION }} | |
| OS_PRETTY_NAME: ${{ steps.pinned.outputs.OS_PRETTY_NAME }} | |
| GCC_VERSION: ${{ steps.pinned.outputs.GCC_VERSION }} | |
| TIMEOUT_MODELS: ${{ steps.summary.outputs.TIMEOUT_MODELS }} | |
| steps: | |
| - name: Checkout torch-xpu-ops | |
| uses: actions/checkout@v4 | |
| - name: Prepare Conda ENV | |
| run: | | |
| rm -rf ${HOME}/mengfeil/myvenv-e2e | |
| /usr/bin/python3.10 -m venv ${HOME}/mengfeil/myvenv-e2e | |
| source ${HOME}/mengfeil/myvenv-e2e/bin/activate | |
| # pip install mkl-static==2025.0.1 mkl-include==2025.0.1 | |
| pip install pandas scipy tqdm | |
| - name: Prepare Stock Pytorch | |
| id: installed | |
| run: | | |
| pwd | |
| source ${HOME}/mengfeil/myvenv-e2e/bin/activate | |
| pip install torch torchvision torchaudio --pre --index-url https://download.pytorch.org/whl/nightly/xpu | |
| echo "TORCH_BRANCH_ID=$(python -c 'import torch; print(torch.__version__)')" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| TORCH_COMMIT_ID=$(python -c 'import torch; print(torch.version.git_version)') | |
| echo "TORCH_COMMIT_ID=${TORCH_COMMIT_ID}" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| cd ../ && rm -rf pytorch | |
| git clone https://github.com/pytorch/pytorch pytorch | |
| cd pytorch && git checkout ${TORCH_COMMIT_ID} | |
| # apply PRs for stock pytorch | |
| pip install requests | |
| python ../torch-xpu-ops/.github/scripts/apply_torch_pr.py | |
| git status && git show -s | |
| pip install -r requirements.txt | |
| TORCH_XPU_OPS_COMMIT=$(<third_party/xpu.txt) | |
| echo "TORCH_XPU_OPS_COMMIT=${TORCH_XPU_OPS_COMMIT}" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| 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} | |
| - name: Identify pinned versions | |
| id: pinned | |
| run: | | |
| source ${HOME}/mengfeil/myvenv-e2e/bin/activate | |
| echo "TORCHVISION_COMMIT_ID=$(python -c 'import torchvision; print(torchvision.version.git_version)')" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "TORCHAUDIO_COMMIT_ID=$(python -c 'import torchaudio; print(torchaudio.version.git_version)')" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "TRITON_COMMIT_ID=$(python -c 'import triton; print(triton.__version__)')" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| cd ../pytorch | |
| echo "TORCHBENCH_COMMIT_ID=$(<third_party/torch-xpu-ops/.github/ci_commit_pins/torchbench.txt)" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "TRANSFORMERS_VERSION=$(<.ci/docker/ci_commit_pins/huggingface.txt)" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "TIMM_COMMIT_ID=$(<.ci/docker/ci_commit_pins/timm.txt)" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "MODEL_ONLY_NAME=${{ inputs.model }}" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "DRIVER_VERSION=$(dkms status 2>&1 |grep 'intel-i915-dkms' |sed 's/.*\///;s/,.*//')" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "KERNEL_VERSION=$(uname -rv 2>&1)" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "BUNDLE_VERSION=$(pip list |grep cmplr |head -n 1)" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| . /etc/os-release | |
| echo "OS_PRETTY_NAME=${PRETTY_NAME}" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo "GCC_VERSION=$(gcc -dumpversion)" |tee -a "${GITHUB_OUTPUT}" >> "${GITHUB_ENV}" | |
| echo ${GITHUB_ENV} | |
| - name: Show GITHUB_ENV | |
| run: | | |
| echo "$GITHUB_ENV" | |
| rm -rf ../pytorch/inductor_log | |
| rm -rf /tmp/torchinductor_* | |
| # Nihglty launch | |
| - name: Nightly Huggingface FP32/BF16/FP16 Inference & Training Accuracy Test | |
| if: github.event_name == 'schedule' && github.event.schedule == '0 14 * * 0-4' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: huggingface | |
| env_prepare: true | |
| dt: float32,bfloat16,float16,amp_bf16,amp_fp16 | |
| mode: inference,training | |
| scenario: accuracy | |
| pytorch: nightly_wheel | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| - name: Nightly Torchbench BF16 Training Accuracy Test | |
| if: github.event_name == 'schedule' && github.event.schedule == '0 14 * * 0-4' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: torchbench | |
| dt: bfloat16 | |
| mode: training | |
| scenario: accuracy | |
| pytorch: nightly_wheel | |
| env_prepare: true | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| - name: Nightly Timm_models FP16 Training Accuracy Test | |
| if: github.event_name == 'schedule' && github.event.schedule == '0 14 * * 0-4' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: timm_models | |
| dt: float16 | |
| mode: training | |
| scenario: accuracy | |
| pytorch: nightly_wheel | |
| env_prepare: true | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| # Weekly launch | |
| - name: Weekly Huggingface Full Test | |
| if: github.event_name == 'schedule' && github.event.schedule == '0 17 * * 5' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: huggingface | |
| env_prepare: true | |
| dt: float32,bfloat16,float16,amp_bf16,amp_fp16 | |
| mode: inference,training | |
| scenario: accuracy,performance | |
| pytorch: nightly_wheel | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| - name: Weekly Torchbench Full Test | |
| if: github.event_name == 'schedule' && github.event.schedule == '0 17 * * 5' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: torchbench | |
| env_prepare: true | |
| dt: float32,bfloat16,float16,amp_bf16,amp_fp16 | |
| mode: inference,training | |
| scenario: accuracy,performance | |
| pytorch: nightly_wheel | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| - name: Weekly Timm_models Full Test | |
| if: github.event_name == 'schedule' && github.event.schedule == '0 17 * * 5' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: timm_models | |
| env_prepare: true | |
| dt: float32,bfloat16,float16,amp_bf16,amp_fp16 | |
| mode: inference,training | |
| scenario: accuracy,performance | |
| pytorch: nightly_wheel | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| # On-demand launch | |
| - name: OnDemand Test (${{ inputs.suite }} ${{ inputs.dt }} ${{ inputs.mode }} ${{ inputs.scenario }}) | |
| if: github.event_name != 'schedule' | |
| uses: ./.github/actions/inductor-xpu-e2e-test | |
| with: | |
| suite: ${{ inputs.suite }} | |
| env_prepare: true | |
| dt: ${{ inputs.dt }} | |
| mode: ${{ inputs.mode }} | |
| scenario: ${{ inputs.scenario }} | |
| pytorch: nightly_wheel | |
| hf_token: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| - name: Summarize archieve files | |
| id: summary | |
| if: ${{ ! cancelled() }} | |
| run: | | |
| rm -rf ${{ github.workspace }}/upload_files | |
| cp -r ${{ github.workspace }}/../pytorch/inductor_log ${{ github.workspace }}/upload_files | |
| mkdir -p ${{ github.workspace }}/../../_backup/ && cd ${{ github.workspace }}/../../_backup/ | |
| find . -type f -name "*.tgz" -mtime +3 -delete # delete files older than 3 days | |
| tar zcf xpu-inductor-${GITHUB_RUN_ID}.tgz -C ${{ github.workspace }}/upload_files/ . # backup logs | |
| - name: Upload Inductor XPU E2E Data | |
| if: ${{ ! cancelled() }} | |
| uses: actions/upload-artifact@v4 | |
| with: | |
| name: Inductor-XPU-E2E-Data-${{ github.event.pull_request.number || github.sha }} | |
| path: ${{ github.workspace }}/upload_files |