test_containers_singularity_gpu.yml

name: CI-Test in AWS for GPU

on:
  workflow_dispatch:

jobs:
  deploy-runner:
    runs-on: ubuntu-latest
    steps:
      - uses: iterative/setup-cml@v1
      - uses: actions/checkout@v3
      - name: Deploy runner on EC2
        env:
          REPO_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
          AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
          AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
        run: |
          cml runner \
            --cloud=aws \
            --cloud-region=us-east-2 \
            --cloud-type=g4dn.xlarge \
            --labels=cml-gpu
  test-gpu-sorters:
    needs: deploy-runner
    runs-on: [self-hosted, cml-gpu]
    timeout-minutes: 360 # 6h
    container:
      image: docker://iterativeai/cml:0-dvc2-base1-gpu
      options: --privileged --gpus all
    steps:
      - uses: actions/checkout@v3

      - name: Install dependencies
        run: |
          sudo apt-get update
          sudo apt-get install -y wget squashfs-tools
          python -m pip install -U pip  # Official recommended way
          pip install pytest
          pip install -e .[full]
          pip install spython

      - uses: eWaterCycle/setup-singularity@v7
        with:
          singularity-version: 3.8.3

      - name: Run test singularity containers with GPU
        env:
          REPO_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
        run: |
          pytest -vv --capture=tee-sys -rA src/spikeinterface/sorters/external/tests/test_singularity_containers_gpu.py