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integration.yml
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name: integration
on:
repository_dispatch:
type: [integration-test-command]
jobs:
integration-py3:
container:
image: nvcr.io/nvidia/pytorch:20.12-py3 # CUDA 11.1
options: --gpus all
runs-on: [self-hosted, linux, x64, common]
steps:
# checkout the pull request branch
- uses: actions/checkout@v2
with:
token: ${{ secrets.PR_MAINTAIN }}
repository: ${{ github.event.client_payload.pull_request.head.repo.full_name }}
ref: ${{ github.event.client_payload.pull_request.head.ref }}
- name: cache weekly timestamp
id: pip-cache
run: |
echo "::set-output name=datew::$(date '+%Y-%V')"
- name: cache for pip
uses: actions/cache@v2
id: cache
with:
path: |
~/.cache/pip
~/.cache/torch
key: docker-py3-pip-${{ steps.pip-cache.outputs.datew }}
- name: Install the dependencies
run: |
which python
python -m pip install --upgrade pip wheel
python -m pip uninstall -y torch torchvision
python -m pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111 -f https://download.pytorch.org/whl/torch_stable.html
python -m pip install -r requirements-dev.txt
- name: Run integration tests
run: |
python -m pip list
nvidia-smi
export CUDA_VISIBLE_DEVICES=$(python -m tests.utils)
echo $CUDA_VISIBLE_DEVICES
trap 'if pgrep python; then pkill python; fi;' ERR
python -c $'import torch\na,b=torch.zeros(1,device="cuda:0"),torch.zeros(1,device="cuda:1");\nwhile True:print(a,b)' > /dev/null &
python -c "import torch; print(torch.__version__); print('{} of GPUs available'.format(torch.cuda.device_count()))"
python -c 'import torch; print(torch.rand(5,3, device=torch.device("cuda:0")))'
BUILD_MONAI=1 ./runtests.sh --build --net
BUILD_MONAI=1 ./runtests.sh --build --unittests --disttests
if pgrep python; then pkill python; fi
shell: bash
- name: Add reaction
uses: peter-evans/create-or-update-comment@v1
with:
token: ${{ secrets.PR_MAINTAIN }}
repository: ${{ github.event.client_payload.github.payload.repository.full_name }}
comment-id: ${{ github.event.client_payload.github.payload.comment.id }}
reaction-type: rocket