4 GPU Integration Test #5164
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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 | |
# install torchtitan to test the files in ./scripts, currently just for memory estimation | |
python -m pip install -e . | |
mkdir artifacts-to-be-uploaded | |
python ./test_runner.py artifacts-to-be-uploaded --ngpu 4 |