Fixed failing tests on pytorch nightly using torch.load #229
Workflow file for this run
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name: Run HVD-specific unit tests on GPUs | |
on: | |
push: | |
paths: | |
- "ignite/**" | |
- "tests/ignite/**" | |
- "tests/run_gpu_tests.sh" | |
- "tests/run_code_style.sh" | |
- "examples/**.py" | |
- "requirements-dev.txt" | |
- ".github/workflows/gpu-hvd-tests.yml" | |
workflow_dispatch: | |
concurrency: | |
# <workflow_name>-<branch_name>-<true || commit_sha (if branch is protected)> | |
group: gpu-hvd-tests-${{ github.ref_name }}-${{ !(github.ref_protected) || github.sha }} | |
cancel-in-progress: true | |
# Cherry-picked from https://github.com/pytorch/test-infra/blob/main/.github/workflows/linux_job.yml | |
jobs: | |
gpu-hvd-tests: | |
strategy: | |
matrix: | |
pytorch-channel: [pytorch] | |
fail-fast: false | |
env: | |
DOCKER_IMAGE: "pytorch/conda-builder:cuda12.1" | |
REPOSITORY: ${{ github.repository }} | |
PR_NUMBER: ${{ github.event.pull_request.number }} | |
runs-on: linux.8xlarge.nvidia.gpu | |
timeout-minutes: 60 | |
steps: | |
- name: Clean workspace | |
run: | | |
echo "::group::Cleanup debug output" | |
sudo rm -rfv "${GITHUB_WORKSPACE}" | |
mkdir -p "${GITHUB_WORKSPACE}" | |
echo "::endgroup::" | |
- name: Checkout repository (pytorch/test-infra) | |
uses: actions/checkout@v3 | |
with: | |
# Support the use case where we need to checkout someone's fork | |
repository: pytorch/test-infra | |
path: test-infra | |
- name: Setup Linux | |
uses: ./test-infra/.github/actions/setup-linux | |
- name: Pull docker image | |
uses: ./test-infra/.github/actions/pull-docker-image | |
with: | |
docker-image: ${{ env.DOCKER_IMAGE }} | |
- name: Checkout repository (${{ github.repository }}) | |
uses: actions/checkout@v3 | |
with: | |
# Support the use case where we need to checkout someone's fork | |
repository: ${{ github.repository }} | |
ref: ${{ github.ref }} | |
path: ${{ github.repository }} | |
fetch-depth: 1 | |
- name: Start Pytorch container | |
working-directory: ${{ github.repository }} | |
run: | | |
docker run --name pthd --gpus=all --rm \ | |
--cap-add=SYS_PTRACE \ | |
--detach \ | |
--ipc=host \ | |
--security-opt seccomp=unconfined \ | |
--shm-size=2g \ | |
--tty \ | |
--ulimit stack=10485760:83886080 \ | |
-v $PWD:/work \ | |
-w /work \ | |
${DOCKER_IMAGE} | |
script=$(cat << EOF | |
set -xe | |
nvidia-smi | |
ls -alh | |
conda --version | |
python --version | |
EOF | |
) | |
docker exec -t pthd /bin/bash -c "${script}" | |
- name: Install PyTorch and dependencies | |
continue-on-error: false | |
run: | | |
script=$(cat << EOF | |
set -xe | |
# Install PyTorch | |
if [ "${{ matrix.pytorch-channel }}" == "pytorch" ]; then | |
pip install --upgrade torch torchvision --index-url https://download.pytorch.org/whl/cu121 | |
else | |
pip install --upgrade --pre torch torchvision --index-url https://download.pytorch.org/whl/nightly/cu121 | |
fi | |
python -c "import torch; print(torch.__version__, ', CUDA is available: ', torch.cuda.is_available()); exit(not torch.cuda.is_available())" | |
pip list | |
# Install dependencies | |
pip install -r requirements-dev.txt | |
pip install -e . | |
EOF | |
) | |
docker exec -t pthd /bin/bash -c "${script}" | |
- name: Install Horovod with NCCL GPU ops | |
run: | | |
script=$(cat << EOF | |
set -xe | |
# Can't build Horovod with recent pytorch due to pytorch required C++17 standard | |
# and horovod is still using C++14 | |
# HOROVOD_GPU_OPERATIONS=NCCL HOROVOD_WITH_PYTORCH=1 pip install horovod[pytorch] | |
# Using a similar hack as described here: | |
# https://github.com/horovod/horovod/issues/3941#issuecomment-1732505345 | |
git clone --recursive https://github.com/horovod/horovod.git /horovod | |
cd /horovod | |
sed -i "s/CMAKE_CXX_STANDARD 14/CMAKE_CXX_STANDARD 17/g" CMakeLists.txt | |
sed -i "s/CMAKE_CXX_STANDARD 14/CMAKE_CXX_STANDARD 17/g" horovod/torch/CMakeLists.txt | |
HOROVOD_GPU_OPERATIONS=NCCL HOROVOD_WITH_PYTORCH=1 python setup.py install | |
horovodrun --check-build | |
pip list | |
EOF | |
) | |
docker exec -t pthd /bin/bash -c "${script}" | |
- name: Run GPU and CPU Unit HVD Tests | |
run: | | |
script=$(cat << EOF | |
set -xe | |
bash tests/run_gpu_tests.sh 2 hvd | |
CUDA_VISIBLE_DEVICES="" pytest --cov ignite --cov-append --cov-report term-missing --cov-report xml -vvv tests/ignite -m distributed -k hvd | |
EOF | |
) | |
docker exec -t pthd /bin/bash -c "${script}" | |
- name: Upload coverage to Codecov | |
uses: codecov/codecov-action@v3 | |
with: | |
file: ${{ github.repository }}/coverage.xml | |
flags: gpu-2 | |
fail_ci_if_error: false | |
- name: Run examples in container | |
continue-on-error: false | |
run: | | |
SCRIPT=$(cat << EOF | |
set -xe | |
# Install additional example dependencies | |
pip install fire | |
# Check training on CIFAR10, run with horovod backend using horovodrun | |
# initial run | |
CI=1 horovodrun -np 2 python -u examples/cifar10/main.py run --backend=horovod --checkpoint_every=200 --stop_iteration=500 | |
# resume | |
CI=1 horovodrun -np 2 python examples/cifar10/main.py run --checkpoint_every=200 --num_epochs=7 --resume-from=/tmp/output-cifar10/resnet18_backend-horovod-2_stop-on-500/training_checkpoint_400.pt | |
# Check training on CIFAR10 using spawn | |
# initial run | |
CI=1 python -u examples/cifar10/main.py run --backend=horovod --nproc_per_node=2 --checkpoint_every=200 --stop_iteration=500 | |
# resume | |
CI=1 python -u examples/cifar10/main.py run --backend=horovod --nproc_per_node=2 --checkpoint_every=200 --num_epochs=7 --resume-from=/tmp/output-cifar10/resnet18_backend-horovod-2_stop-on-500/training_checkpoint_400.pt | |
EOF | |
) | |
docker exec -t pthd /bin/bash -c "${script}" | |
- name: Teardown Linux | |
if: ${{ always() }} | |
uses: ./test-infra/.github/actions/teardown-linux |