docker.yml

# Builds the Dockerfile and runs the reproducibility tests inside the image, so
# the container is checked, not only described. Runs when the image's inputs change.
name: Docker image

on:
  push:
    branches: [ master ]
    paths: [ "Dockerfile", "pyproject.toml", "poetry.lock", ".github/workflows/docker.yml" ]
  pull_request:
    branches: [ master ]
    paths: [ "Dockerfile", "pyproject.toml", "poetry.lock", ".github/workflows/docker.yml" ]
  workflow_dispatch:

permissions:
  contents: read

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

jobs:
  docker:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
        with:
          persist-credentials: false
      # The image is about 7 GB (torch bundles its CUDA libraries); make room.
      - name: Free runner disk space
        run: sudo rm -rf /usr/share/dotnet /usr/local/lib/android /opt/ghc /opt/hostedtoolcache/CodeQL
      - name: Build image
        run: docker build -t bindsnet .
      # Runners have no GPU, and the image's CUDA torch build can segfault there while
      # preloading CUDA (see .github/scripts/use_cpu_torch.sh), so the test container
      # swaps in the CPU build of the same version; everything else is the image as built.
      - name: Run reproducibility tests in the image
        run: >-
          docker run --rm bindsnet bash -c
          ".github/scripts/use_cpu_torch.sh python && python -m pytest -q test/repro"