4 GPU Integration Test #2113
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| name: 4 GPU Integration Test | |
| on: | |
| push: | |
| branches: [ main ] | |
| pull_request: | |
| schedule: | |
| # Runs hourly | |
| - cron: '0 * * * *' | |
| concurrency: | |
| group: unit-test${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_number || github.ref }} | |
| cancel-in-progress: true | |
| defaults: | |
| run: | |
| shell: bash -l -eo pipefail {0} | |
| jobs: | |
| build-test: | |
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | |
| with: | |
| runner: linux.g5.12xlarge.nvidia.gpu | |
| gpu-arch-type: cuda | |
| gpu-arch-version: "12.1" | |
| # This image is faster to clone than the default, but it lacks CC needed by triton | |
| # (1m25s vs 2m37s). | |
| docker-image: torchtitan-ubuntu-20.04-clang12 | |
| repository: pytorch/torchtitan | |
| upload-artifact: outputs | |
| script: | | |
| set -eux | |
| # The generic Linux job chooses to use base env, not the one setup by the image | |
| CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]") | |
| conda activate "${CONDA_ENV}" | |
| pip config --user set global.progress_bar off | |
| python -m pip install --force-reinstall --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121 | |
| USE_CPP=0 python -m pip install git+https://github.com/pytorch/ao.git | |
| mkdir artifacts-to-be-uploaded | |
| python ./test_runner.py artifacts-to-be-uploaded --ngpu 4 |