Add A10g workflow to gain access to A10G GPU #2
Workflow file for this run
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| name: TorchBench Test on A10G | |
| on: | |
| workflow_dispatch: | |
| pull_request: | |
| types: | |
| - labeled | |
| jobs: | |
| linux-test-a10g: | |
| # Don't run on forked repos | |
| # Only run on PR labeled 'with-ssh' | |
| if: github.repository_owner == 'pytorch' && contains(github.event.pull_request.labels.*.name, 'with-ssh') | |
| runs-on: linux.g5.4xlarge.nvidia.gpu | |
| timeout-minutes: 240 | |
| environment: docker-s3-upload | |
| env: | |
| CONDA_ENV: "pr-test-cuda" | |
| TEST_CONFIG: "cuda" | |
| HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }} | |
| steps: | |
| - name: Checkout TorchBench | |
| uses: actions/checkout@v3 | |
| - name: Setup SSH (Click me for login details) | |
| uses: pytorch/test-infra/.github/actions/setup-ssh@main | |
| with: | |
| github-secret: ${{ secrets.TORCHBENCH_ACCESS_TOKEN }} | |
| - name: Install Conda | |
| run: | | |
| bash ./.ci/torchbench/install-conda.sh | |
| - name: Install TorchBench | |
| run: | | |
| bash ./.ci/torchbench/install.sh | |
| - name: Wait for SSH session to end | |
| run: | | |
| bash ./.ci/torchbench/check-ssh.sh | |
| - name: Clean up Conda env | |
| if: always() | |
| run: | | |
| . ${HOME}/miniconda3/etc/profile.d/conda.sh | |
| conda remove -n "${CONDA_ENV}" --all | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }} | |
| cancel-in-progress: true |