flower/.github/workflows/datasets-e2e.yml at main · flwrlabs/flower · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
name: Datasets-E2E

on:
  push:
    branches:
      - main
    paths:
      - "datasets/flwr_datasets/**"
  pull_request:
    branches:
      - main
    paths:
      - "datasets/flwr_datasets/**"

concurrency:
  group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.event.pull_request.number || github.ref }}
  cancel-in-progress: true

env:
  FLWR_TELEMETRY_ENABLED: 0
  UV_NO_MANAGED_PYTHON: 1
  UV_PYTHON_DOWNLOADS: never

jobs:
  frameworks:
    runs-on: ubuntu-22.04
    timeout-minutes: 10
    # Using approach described here:
    # https://docs.github.com/en/actions/using-jobs/using-a-matrix-for-your-jobs
    strategy:
      matrix:
        include:
          - directory: pytorch

          - directory: tensorflow

          - directory: scikit-learn

    name: Framework / ${{matrix.directory}}

    defaults:
      run:
        working-directory: datasets/e2e/${{ matrix.directory }}

    steps:
      - uses: actions/checkout@v5
      - name: Bootstrap
        uses: ./.github/actions/bootstrap
        with:
          python-version: 3.10.19
          uv-skip: "false"
          poetry-skip: "true"
      - name: Free Disk Space (Ubuntu)
        uses: jlumbroso/free-disk-space@v1.3.1
        with:
          tool-cache: false
          android: true
          dotnet: true
          haskell: true
          large-packages: false
          docker-images: false
          swap-storage: false
      - name: Install dependencies (system)
        run: |
          sudo apt-get update
          sudo apt-get install -y ffmpeg
      - name: Install dependencies
        run: uv sync --frozen
      - name: Run tests
        run: uv run python -m unittest discover -p '*_test.py'