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Use torch generic workflow for CI
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ghstack-source-id: 008612abbfe85656a1cae9ef590710687744bfd6
Pull Request resolved: #325
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wconstab committed May 14, 2024
1 parent 7f92f45 commit e1f5e99
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50 changes: 20 additions & 30 deletions .github/workflows/unit_test_4gpu.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -9,34 +9,24 @@ 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:
unit_tests_4gpu:
runs-on: linux.g5.12xlarge.nvidia.gpu
strategy:
matrix:
python-version: ['3.10']
steps:
- name: Check out repo
uses: actions/checkout@v3
- name: Setup conda env
uses: conda-incubator/setup-miniconda@v2
with:
auto-update-conda: true
miniconda-version: "latest"
activate-environment: test
python-version: ${{ matrix.python-version }}
- name: Update pip
run: python -m pip install --upgrade pip
- name: Install dependencies
run: |
pip3 install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121
python -m pip install -r requirements.txt
python -m pip install -r dev-requirements.txt
- name: Run test_runner.py
run: python ./test_runner.py
- name: Upload Coverage to Codecov
uses: codecov/codecov-action@v3
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"
docker-image: "nvidia/cuda:12.4.1-runtime-ubuntu22.04"
repository: "pytorch/torchtitan"
upload-artifact: "outputs"
script: |
pip3 install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu121
python -m pip install -r requirements.txt
python -m pip install -r dev-requirements.txt
python ./test_runner.py
mv outputs artifacts-to-be-uploaded
# TODO the below were not ported over to the 'generic workflow' - do they matter?

# - name: Upload Coverage to Codecov
# uses: codecov/codecov-action@v3

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