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setup_logger: add optional arg encoding for FileHandler (#3240) #520

setup_logger: add optional arg encoding for FileHandler (#3240)

setup_logger: add optional arg encoding for FileHandler (#3240) #520

Workflow file for this run

name: Run 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-tests.yml"
workflow_dispatch:
concurrency:
# <workflow_name>-<branch_name>-<true || commit_sha (if branch is protected)>
group: gpu-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-tests:
strategy:
matrix:
pytorch-channel: [pytorch, pytorch-nightly]
fail-fast: false
env:
DOCKER_IMAGE: "pytorch/conda-builder:cuda12.1"
REPOSITORY: ${{ github.repository }}
PR_NUMBER: ${{ github.event.pull_request.number }}
runs-on: linux.8xlarge.nvidia.gpu
timeout-minutes: 45
steps:
- name: Clean workspace
run: |
echo "::group::Cleanup debug output"
sudo rm -rfv "${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: Run GPU Unit Tests
continue-on-error: false
run: |
script=$(cat << EOF
set -xe
bash tests/run_gpu_tests.sh 2
EOF
)
docker exec -t pthd /bin/bash -c "${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 without backend
## initial run
CI=1 python examples/cifar10/main.py run --checkpoint_every=200 --stop_iteration=500
## resume
CI=1 python examples/cifar10/main.py run --checkpoint_every=200 --num_epochs=7 --resume-from=/tmp/output-cifar10/resnet18_backend-None-1_stop-on-500/training_checkpoint_400.pt
# Check training on cifar10, run with NCCL backend using torchrun
## initial run
CI=1 torchrun --nproc_per_node=2 examples/cifar10/main.py run --backend=nccl --checkpoint_every=200 --stop_iteration=500
## resume
CI=1 torchrun --nproc_per_node=2 examples/cifar10/main.py run --backend=nccl --checkpoint_every=200 --num_epochs=7 --resume-from=/tmp/output-cifar10/resnet18_backend-nccl-2_stop-on-500/training_checkpoint_400.pt
# Check training on cifar10, run with NCCL backend using spawn
## initial run
CI=1 python -u examples/cifar10/main.py run --backend=nccl --nproc_per_node=2 --checkpoint_every=200 --stop_iteration=500
## resume
CI=1 python -u examples/cifar10/main.py run --backend=nccl --nproc_per_node=2 --checkpoint_every=200 --num_epochs=7 --resume-from=/tmp/output-cifar10/resnet18_backend-nccl-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