self-scheduled.yml

name: Self-hosted runner (scheduled)

# Note that each job's dependencies go into a corresponding docker file.
#
# For example for `run_all_tests_torch_cuda_extensions_gpu` the docker image is
# `huggingface/transformers-pytorch-deepspeed-latest-gpu`, which can be found at
# `docker/transformers-pytorch-deepspeed-latest-gpu/Dockerfile`

on:
  repository_dispatch:
  schedule:
    - cron: "17 2 * * *"
  push:
    branches:
      - run_scheduled_ci*

env:
  HF_HOME: /mnt/cache
  TRANSFORMERS_IS_CI: yes
  OMP_NUM_THREADS: 8
  MKL_NUM_THREADS: 8
  RUN_SLOW: yes
  # For gated repositories, we still need to agree to share information on the Hub repo. page in order to get access.
  # This token is created under the bot `hf-transformers-bot`.
  HF_HUB_READ_TOKEN: ${{ secrets.HF_HUB_READ_TOKEN }}
  SIGOPT_API_TOKEN: ${{ secrets.SIGOPT_API_TOKEN }}
  TF_FORCE_GPU_ALLOW_GROWTH: true
  RUN_PT_TF_CROSS_TESTS: 1
  CUDA_VISIBLE_DEVICES: 0,1
  NUM_SLICES: 2

jobs:
  setup:
    name: Setup
    strategy:
      matrix:
        machine_type: [single-gpu, multi-gpu]
    runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
    container:
      image: huggingface/transformers-all-latest-gpu
      options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
    outputs:
      folder_slices: ${{ steps.set-matrix.outputs.folder_slices }}
      slice_ids: ${{ steps.set-matrix.outputs.slice_ids }}
    steps:
      - name: Update clone
        working-directory: /transformers
        run: |
          git fetch && git checkout ${{ github.sha }}

      - name: Cleanup
        working-directory: /transformers
        run: |
          rm -rf tests/__pycache__
          rm -rf tests/models/__pycache__
          rm -rf reports

      - name: Show installed libraries and their versions
        working-directory: /transformers
        run: pip freeze

      - id: set-matrix
        name: Identify models to test
        working-directory: /transformers/tests
        run: |
          echo "folder_slices=$(python3 ../utils/split_model_tests.py --num_splits ${{ env.NUM_SLICES }})" >> $GITHUB_OUTPUT
          echo "slice_ids=$(python3 -c 'd = list(range(${{ env.NUM_SLICES }})); print(d)')" >> $GITHUB_OUTPUT

      - name: NVIDIA-SMI
        run: |
          nvidia-smi

  run_tests_gpu:
    name: " "
    needs: setup
    strategy:
      fail-fast: false
      matrix:
        machine_type: [single-gpu, multi-gpu]
        slice_id: ${{ fromJSON(needs.setup.outputs.slice_ids) }}
    uses: ./.github/workflows/model_jobs.yml
    with:
      folder_slices: ${{ needs.setup.outputs.folder_slices }}
      machine_type: ${{ matrix.machine_type }}
      slice_id: ${{ matrix.slice_id }}
    secrets: inherit

  run_examples_gpu:
    name: Examples directory
    strategy:
      fail-fast: false
      matrix:
        machine_type: [single-gpu]
    runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
    container:
      image: huggingface/transformers-all-latest-gpu
      options: --gpus 0 --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
    needs: setup
    steps:
      - name: Update clone
        working-directory: /transformers
        run: git fetch && git checkout ${{ github.sha }}

      - name: Reinstall transformers in edit mode (remove the one installed during docker image build)
        working-directory: /transformers
        run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .

      - name: NVIDIA-SMI
        run: |
          nvidia-smi

      - name: Environment
        working-directory: /transformers
        run: |
          python3 utils/print_env.py

      - name: Show installed libraries and their versions
        working-directory: /transformers
        run: pip freeze

      - name: Run examples tests on GPU
        working-directory: /transformers
        run: |
          pip install -r examples/pytorch/_tests_requirements.txt
          python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_examples_gpu examples/pytorch

      - name: Failure short reports
        if: ${{ failure() }}
        continue-on-error: true
        run: cat /transformers/reports/${{ matrix.machine_type }}_examples_gpu/failures_short.txt

      - name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_examples_gpu"
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: ${{ matrix.machine_type }}_run_examples_gpu
          path: /transformers/reports/${{ matrix.machine_type }}_examples_gpu

  run_pipelines_torch_gpu:
    name: PyTorch pipelines
    strategy:
      fail-fast: false
      matrix:
        machine_type: [single-gpu, multi-gpu]
    runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
    container:
      image: huggingface/transformers-pytorch-gpu
      options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
    needs: setup
    steps:
      - name: Update clone
        working-directory: /transformers
        run: git fetch && git checkout ${{ github.sha }}

      - name: Reinstall transformers in edit mode (remove the one installed during docker image build)
        working-directory: /transformers
        run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .

      - name: NVIDIA-SMI
        run: |
          nvidia-smi

      - name: Environment
        working-directory: /transformers
        run: |
          python3 utils/print_env.py

      - name: Show installed libraries and their versions
        working-directory: /transformers
        run: pip freeze

      - name: Run all pipeline tests on GPU
        working-directory: /transformers
        run: |
          python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ matrix.machine_type }}_tests_torch_pipeline_gpu tests/pipelines

      - name: Failure short reports
        if: ${{ failure() }}
        continue-on-error: true
        run: cat /transformers/reports/${{ matrix.machine_type }}_tests_torch_pipeline_gpu/failures_short.txt

      - name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_tests_torch_pipeline_gpu"
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: ${{ matrix.machine_type }}_run_tests_torch_pipeline_gpu
          path: /transformers/reports/${{ matrix.machine_type }}_tests_torch_pipeline_gpu

  run_pipelines_tf_gpu:
    name: TensorFlow pipelines
    strategy:
      fail-fast: false
      matrix:
        machine_type: [single-gpu, multi-gpu]
    runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
    container:
      image: huggingface/transformers-tensorflow-gpu
      options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
    needs: setup
    steps:
      - name: Update clone
        working-directory: /transformers
        run: |
          git fetch && git checkout ${{ github.sha }}

      - name: Reinstall transformers in edit mode (remove the one installed during docker image build)
        working-directory: /transformers
        run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .

      - name: NVIDIA-SMI
        run: |
          nvidia-smi

      - name: Environment
        working-directory: /transformers
        run: |
          python3 utils/print_env.py

      - name: Show installed libraries and their versions
        working-directory: /transformers
        run: pip freeze

      - name: Run all pipeline tests on GPU
        working-directory: /transformers
        run: |
          python3 -m pytest -n 1 -v --dist=loadfile --make-reports=${{ matrix.machine_type }}_tests_tf_pipeline_gpu tests/pipelines

      - name: Failure short reports
        if: ${{ always() }}
        run: |
          cat /transformers/reports/${{ matrix.machine_type }}_tests_tf_pipeline_gpu/failures_short.txt

      - name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_tests_tf_pipeline_gpu"
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: ${{ matrix.machine_type }}_run_tests_tf_pipeline_gpu
          path: /transformers/reports/${{ matrix.machine_type }}_tests_tf_pipeline_gpu

  run_all_tests_torch_cuda_extensions_gpu:
    name: Torch CUDA extension tests
    strategy:
      fail-fast: false
      matrix:
        machine_type: [single-gpu, multi-gpu]
    runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
    needs: setup
    container:
      image: huggingface/transformers-pytorch-deepspeed-latest-gpu
      options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
    steps:
      - name: Update clone
        working-directory: /workspace/transformers
        run: git fetch && git checkout ${{ github.sha }}

      - name: Reinstall transformers in edit mode (remove the one installed during docker image build)
        working-directory: /workspace/transformers
        run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .

      - name: Remove cached torch extensions
        run: rm -rf /github/home/.cache/torch_extensions/

      # To avoid unknown test failures
      - name: Pre build DeepSpeed *again*
        working-directory: /workspace
        run: |
          python3 -m pip uninstall -y deepspeed
          DS_DISABLE_NINJA=1 DS_BUILD_CPU_ADAM=1 DS_BUILD_FUSED_ADAM=1 python3 -m pip install deepspeed --global-option="build_ext" --global-option="-j8" --no-cache -v --disable-pip-version-check

      - name: NVIDIA-SMI
        run: |
          nvidia-smi

      - name: Environment
        working-directory: /workspace/transformers
        run: |
          python utils/print_env.py

      - name: Show installed libraries and their versions
        working-directory: /workspace/transformers
        run: pip freeze

      - name: Run all tests on GPU
        working-directory: /workspace/transformers
        run: |
          python -m pytest -v --make-reports=${{ matrix.machine_type }}_tests_torch_cuda_extensions_gpu tests/deepspeed tests/extended

      - name: Failure short reports
        if: ${{ failure() }}
        continue-on-error: true
        run: cat /workspace/transformers/reports/${{ matrix.machine_type }}_tests_torch_cuda_extensions_gpu/failures_short.txt

      - name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_tests_torch_cuda_extensions_gpu_test_reports"
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: ${{ matrix.machine_type }}_run_tests_torch_cuda_extensions_gpu_test_reports
          path: /workspace/transformers/reports/${{ matrix.machine_type }}_tests_torch_cuda_extensions_gpu

  run_tests_quantization_torch_gpu:
    name: Quantization tests
    strategy:
      fail-fast: false
      matrix:
        machine_type: [single-gpu, multi-gpu]
    runs-on: ['${{ matrix.machine_type }}', nvidia-gpu, t4, daily-ci]
    container:
      image: huggingface/transformers-quantization-latest-gpu
      options: --gpus all --shm-size "16gb" --ipc host -v /mnt/cache/.cache/huggingface:/mnt/cache/
    needs: setup
    steps:
      - name: Update clone
        working-directory: /transformers
        run: git fetch && git checkout ${{ github.sha }}

      - name: Reinstall transformers in edit mode (remove the one installed during docker image build)
        working-directory: /transformers
        run: python3 -m pip uninstall -y transformers && python3 -m pip install -e .

      - name: NVIDIA-SMI
        run: |
          nvidia-smi

      - name: Environment
        working-directory: /transformers
        run: |
          python3 utils/print_env.py

      - name: Show installed libraries and their versions
        working-directory: /transformers
        run: pip freeze

      - name: Run quantization tests on GPU
        working-directory: /transformers
        run: |
          python3 -m pytest -v --make-reports=${{ matrix.machine_type }}_tests_quantization_torch_gpu tests/quantization

      - name: Failure short reports
        if: ${{ failure() }}
        continue-on-error: true
        run: cat /transformers/reports/${{ matrix.machine_type }}_tests_quantization_torch_gpu/failures_short.txt

      - name: "Test suite reports artifacts: ${{ matrix.machine_type }}_run_tests_quantization_torch_gpu"
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: ${{ matrix.machine_type }}_run_tests_quantization_torch_gpu
          path: /transformers/reports/${{ matrix.machine_type }}_tests_quantization_torch_gpu

  run_extract_warnings:
    name: Extract warnings in CI artifacts
    runs-on: ubuntu-22.04
    if: always()
    needs: [
      setup,
      run_tests_gpu,
      run_examples_gpu,
      run_pipelines_tf_gpu,
      run_pipelines_torch_gpu,
      run_all_tests_torch_cuda_extensions_gpu,
      run_tests_quantization_torch_gpu,
    ]
    steps:
      - name: Checkout transformers
        uses: actions/checkout@v3
        with:
          fetch-depth: 2

      - name: Install transformers
        run: pip install transformers

      - name: Show installed libraries and their versions
        run: pip freeze

      - name: Create output directory
        run: mkdir warnings_in_ci

      - uses: actions/download-artifact@v3
        with:
          path: warnings_in_ci

      - name: Show artifacts
        run: echo "$(python3 -c 'import os; d = os.listdir(); print(d)')"
        working-directory: warnings_in_ci

      - name: Extract warnings in CI artifacts
        run: |
          python3 utils/extract_warnings.py --workflow_run_id ${{ github.run_id }} --output_dir warnings_in_ci --token ${{ secrets.ACCESS_REPO_INFO_TOKEN }} --from_gh
          echo "$(python3 -c 'import os; import json; fp = open("warnings_in_ci/selected_warnings.json"); d = json.load(fp); d = "\n".join(d) ;print(d)')"

      - name: Upload artifact
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: warnings_in_ci
          path: warnings_in_ci/selected_warnings.json

  send_results:
    name: Send results to webhook
    runs-on: ubuntu-22.04
    if: always()
    needs: [
      setup,
      run_tests_gpu,
      run_examples_gpu,
      run_pipelines_tf_gpu,
      run_pipelines_torch_gpu,
      run_all_tests_torch_cuda_extensions_gpu,
      run_tests_quantization_torch_gpu,
      run_extract_warnings
    ]
    steps:
      - name: Preliminary job status
        shell: bash
        # For the meaning of these environment variables, see the job `Setup`
        run: |
          echo "Setup status: ${{ needs.setup.result }}"

      - uses: actions/checkout@v3
      - uses: actions/download-artifact@v3
      - name: Send message to Slack
        env:
          CI_SLACK_BOT_TOKEN: ${{ secrets.CI_SLACK_BOT_TOKEN }}
          CI_SLACK_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID }}
          CI_SLACK_CHANNEL_ID_DAILY: ${{ secrets.CI_SLACK_CHANNEL_ID_DAILY }}
          CI_SLACK_CHANNEL_DUMMY_TESTS: ${{ secrets.CI_SLACK_CHANNEL_DUMMY_TESTS }}
          CI_SLACK_REPORT_CHANNEL_ID: ${{ secrets.CI_SLACK_CHANNEL_ID_DAILY }}
          ACCESS_REPO_INFO_TOKEN: ${{ secrets.ACCESS_REPO_INFO_TOKEN }}
          CI_EVENT: scheduled
          CI_SHA: ${{ github.sha }}
          CI_WORKFLOW_REF: ${{ github.workflow_ref }}
          SETUP_STATUS: ${{ needs.setup.result }}
        # We pass `needs.setup.outputs.matrix` as the argument. A processing in `notification_service.py` to change
        # `models/bert` to `models_bert` is required, as the artifact names use `_` instead of `/`.
        run: |
          sudo apt-get install -y curl
          pip install slack_sdk
          pip show slack_sdk
          python utils/notification_service.py "${{ needs.setup.outputs.folder_slices }}"

      # Upload complete failure tables, as they might be big and only truncated versions could be sent to Slack.
      - name: Failure table artifacts
        if: ${{ always() }}
        uses: actions/upload-artifact@v3
        with:
          name: prev_ci_results
          path: prev_ci_results