openfl/.github/workflows/gandlf.yml at develop · scngupta-dsp/openfl · GitHub

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# This workflow will install Python dependencies, run tests and lint with a single version of Python
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions

name: GaNDLF TaskRunner E2E

on:
  workflow_call:
  workflow_dispatch:

permissions:
  contents: read

env:
  # A workaround for long FQDN names provided by GitHub actions.
  FQDN: "localhost"

jobs:
  gandlf_seg_test:
    name: GaNDLF Segmentation Test (torch/mnist, 3.10)
    if: github.event.pull_request.draft == false
    runs-on: ubuntu-latest
    timeout-minutes: 15

    env:
      MODEL_NAME: "gandlf_seg_test"
      NUM_ROUNDS: 3
      NUM_COLLABORATORS: 2

    steps:
    - uses: actions/checkout@v4

    - name: Set up Python 3.10
      uses: actions/setup-python@v5
      with:
        python-version: "3.10"

    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install paramiko
        pip install .
        pip install -r test-requirements.txt

    - name: Create gandlf and results directories
      run: |
        mkdir -p gandlf $HOME/results

    - name: Install GaNDLF repository
      uses: actions/checkout@v4
      with:
        repository: 'mlcommons/GaNDLF'
        fetch-depth: 2  # needed for detecting changes
        submodules: 'recursive'
        path: 'gandlf'

    - name: GaNDLF Test Pre-Requisites
      run: |
        cd gandlf
        pwd
        pip install -e .
        pip uninstall onnx -y
        cat ./GANDLF/version.py
        echo "Download data and Split CSVs into training and validation"
        pytest -k "prepare_data_for_ci"
        head -n 1 testing/data/train_2d_rad_segmentation.csv > $HOME/results/valid.csv
        tail -n +9 testing/data/train_2d_rad_segmentation.csv >> $HOME/results/valid.csv
        head -n 8 testing/data/train_2d_rad_segmentation.csv > $HOME/results/train.csv
        cp testing/config_segmentation.yaml $HOME/results/config_segmentation.yaml
        sed -i 's/# n_channels: 3/num_channels: 3/g' $HOME/results/config_segmentation.yaml

    - name: Run GanDLF Segmentation Test
      id: run_tests
      run: |
        python -m pytest -s tests/end_to_end/test_suites/gandlf_seg_tests.py \
        -k test_gandlf_segmentation --model_name ${{ env.MODEL_NAME }} \
        --num_rounds ${{ env.NUM_ROUNDS }} --num_collaborators ${{ env.NUM_COLLABORATORS }}
        echo "Task runner end to end test run completed"

    - name: Create Tar (exclude folders - cert/data/__pycache__, files - tensor.db/workspace.tar/*.csv)
      id: tar_files
      if: ${{ always() }}
      run: |
        tar -cvf result.tar --exclude="cert" --exclude="data" --exclude="__pycache__" --exclude="tensor.db" --exclude="workspace.tar" --exclude="*.csv" $HOME/results

    - name: Upload Artifacts
      id: upload_artifacts
      uses: actions/upload-artifact@v4
      if: ${{ always() }}
      with:
        name: gandlf_artifacts
        path: result.tar