Upgrade to RAPIDS 24.10 #39
Workflow file for this run
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| name: "GPU CI/CD" | |
| on: | |
| pull_request: | |
| branches: | |
| # We can run gpuCI on any PR targeting these branches | |
| - 'main' | |
| - '[rv][0-9].[0-9].[0-9]' | |
| - '[rv][0-9].[0-9].[0-9]rc[0-9]' | |
| # PR has to be labeled with "gpuCI" label | |
| # If new commits are added, the "gpuCI" label has to be removed and re-added to rerun gpuCI | |
| types: [ labeled ] | |
| jobs: | |
| # First, we build and push a NeMo-Curator container | |
| build-container: | |
| # "build-container" job is run if the "gpuci" label is added to the PR | |
| if: ${{ github.event.label.name == 'gpuci' }} | |
| uses: ./.github/workflows/_build_container.yml | |
| # Then, we run our PyTests in the container we just built | |
| run-gpu-tests: | |
| needs: build-container | |
| # This is the tag on our Azure runner found in Actions -> Runners -> Self-hosted runners | |
| # It has 2 A100 GPUs | |
| runs-on: self-hosted-azure | |
| # "run-gpu-tests" job is run if the "gpuci" label is added to the PR | |
| if: ${{ github.event.label.name == 'gpuci' }} | |
| steps: | |
| # If something went wrong during the last cleanup, this step ensures any existing container is removed | |
| - name: Remove existing container if it exists | |
| run: | | |
| if [ "$(docker ps -aq -f name=nemo-curator-container)" ]; then | |
| docker rm -f nemo-curator-container | |
| fi | |
| # This runs the container which was pushed by build-container, which we call "nemo-curator-container" | |
| # `--gpus all` ensures that all of the GPUs from our self-hosted-azure runner are available in the container | |
| # We use "github.run_id" to identify the PR with the commits we want to run the PyTests with | |
| # `bash -c "sleep infinity"` keeps the container running indefinitely without exiting | |
| - name: Run Docker container | |
| run: | | |
| docker run --gpus all --name nemo-curator-container -d nemoci.azurecr.io/nemo_curator_container:${{ github.run_id }} bash -c "sleep infinity" | |
| # Expect `whoami` to be "azureuser" | |
| # Expect `nvidia-smi` to show our 2 A100 GPUs | |
| - name: Check GPUs | |
| run: | | |
| whoami | |
| docker exec nemo-curator-container nvidia-smi | |
| # In the virtual environment (called "curator") we created in the container, | |
| # list all of our packages. Useful for debugging | |
| - name: Verify installations | |
| run: | | |
| docker exec nemo-curator-container conda run -n curator pip list | |
| # In the virtual environment (called "curator") we created in the container, | |
| # run our PyTests marked with `@pytest.mark.gpu` | |
| # We specify the `rootdir` to help locate the "pyproject.toml" file (which is in the root directory of the repository), | |
| # and then the directory where the PyTests are located | |
| - name: Run PyTests with GPU mark | |
| run: | | |
| docker exec nemo-curator-container conda run -n curator pytest -m gpu --rootdir /opt/NeMo-Curator /opt/NeMo-Curator/tests | |
| # After running `docker stop`, the container remains in an exited state | |
| # It is still present on our system and could be restarted with `docker start` | |
| # Thus, we use `docker rm` to permanently removed it from the system | |
| - name: Cleanup | |
| run: | | |
| docker stop nemo-curator-container && docker rm nemo-curator-container |