Move CI from CircleCI to Github Actions #3
Workflow file for this run
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| name: Integration tests with release version of PyTorch on Linux CPU and CUDA | ||
| on: | ||
| pull_request: | ||
| push: | ||
| branches: | ||
| - main | ||
| workflow_dispatch: | ||
| jobs: | ||
| integration_test_cpu: | ||
| strategy: | ||
| matrix: | ||
| python_version: ["3.9"] | ||
| fail-fast: false | ||
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | ||
| with: | ||
| runner: linux.2xlarge | ||
| repository: pytorch/opacus | ||
| timeout: 60 | ||
| script: | | ||
| echo '::group::Create conda env with correct Python version' | ||
| set -x | ||
| PYTHON_VERSION="${{ matrix.python_version }}" | ||
| conda create --yes --quiet -n test python="${PYTHON_VERSION}" | ||
| conda activate test | ||
| python --version | grep "${PYTHON_VERSION}" | ||
| echo '::endgroup::' | ||
| echo '::group::Install dependencies via pip, including extra deps.' | ||
| apt-get install apt | ||
| ./scripts/install_via_pip.sh | ||
| echo '::endgroup::' | ||
| echo '::group::Runs MNIST example end to end' | ||
| mkdir -p runs/mnist/data | ||
| mkdir -p runs/mnist/test-reports | ||
| echo "Using $(python -V)" | ||
| echo "Using $(pip -V)" | ||
| python examples/mnist.py --lr 0.25 --sigma 0.7 -c 1.5 --batch-size 64 --epochs 1 --data-root runs/mnist/data --n-runs 1 --device <<parameters.device>> | ||
| python -c "import torch; accuracy = torch.load('run_results_mnist_0.25_0.7_1.5_64_1.pt'); exit(0) if (accuracy[0]>0.78 and accuracy[0]<0.95) else exit(1)" | ||
| echo '::endgroup::' | ||
| mnist: | ||
| strategy: | ||
| matrix: | ||
| python_version: ["3.9"] | ||
| cuda_arch_version: ["11.8"] | ||
| fail-fast: false | ||
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | ||
| with: | ||
| runner: linux.g5.4xlarge.nvidia.gpu | ||
| gpu-arch-type: cuda | ||
| gpu-arch-version: ${{ matrix.cuda_arch_version }} | ||
| repository: pytorch/opacus | ||
| timeout: 60 | ||
| script: | | ||
| echo '::group::Create conda env with correct Python version' | ||
| set -x | ||
| PYTHON_VERSION="${{ matrix.python_version }}" | ||
| conda create --yes --quiet -n test python="${PYTHON_VERSION}" | ||
| conda activate test | ||
| python --version | grep "${PYTHON_VERSION}" | ||
| echo '::endgroup::' | ||
| echo "::group::Install dependencies via pip, including extra deps." | ||
| apt-get install apt | ||
| ./scripts/install_via_pip.sh | ||
| echo "::endgroup::" | ||
| echo "::group::Run nvidia-smi" | ||
| nvidia-smi | ||
| echo "::endgroup::" | ||
| echo "::group::Run mnist example end to end" | ||
| mkdir -p runs/mnist/data | ||
| mkdir -p runs/mnist/test-reports | ||
| echo "Using $(python -V)" | ||
| echo "Using $(pip -V)" | ||
| python examples/mnist_lightning.py fit --trainer.accelerator cuda --model.lr 0.25 --model.sigma 0.7 --model.max_per_sample_grad_norm 1.5 --model.sample_rate 0.004 --trainer.max_epochs 1 --data.data_dir runs/mnist/data --data.sample_rate 0.004 | ||
| echo "::endgroup::" | ||
| cifar10: | ||
| strategy: | ||
| matrix: | ||
| python_version: ["3.9"] | ||
| cuda_arch_version: ["11.8"] | ||
| fail-fast: false | ||
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | ||
| with: | ||
| runner: linux.g5.4xlarge.nvidia.gpu | ||
| gpu-arch-type: cuda | ||
| gpu-arch-version: ${{ matrix.cuda_arch_version }} | ||
| repository: pytorch/opacus | ||
| timeout: 60 | ||
| script: | | ||
| echo '::group::Create conda env with correct Python version' | ||
| set -x | ||
| PYTHON_VERSION="${{ matrix.python_version }}" | ||
| conda create --yes --quiet -n test python="${PYTHON_VERSION}" | ||
| conda activate test | ||
| python --version | grep "${PYTHON_VERSION}" | ||
| echo '::endgroup::' | ||
| echo "::group::Install dependencies via pip, including extra deps." | ||
| apt-get install apt | ||
| ./scripts/install_via_pip.sh | ||
| echo "::endgroup::" | ||
| echo "::group::Run nvidia-smi" | ||
| nvidia-smi | ||
| echo "::endgroup::" | ||
| echo "::group::Run cifar10 example end to end" | ||
| mkdir -p runs/cifar10/data | ||
| mkdir -p runs/cifar10/logs | ||
| mkdir -p runs/cifar10/test-reports | ||
| echo "Using $(python -V)" | ||
| echo "Using $(pip -V)" | ||
| pip install tensorboard | ||
| python examples/cifar10.py --lr 0.1 --sigma 1.5 -c 10 --batch-size 2000 --epochs 10 --data-root runs/cifar10/data --log-dir runs/cifar10/logs --device cuda | ||
| python -c "import torch; model = torch.load('model_best.pth.tar'); exit(0) if (model['best_acc1']>0.4 and model['best_acc1']<0.49) else exit(1)" | ||
| python examples/cifar10.py --lr 0.1 --sigma 1.5 -c 10 --batch-size 2000 --epochs 10 --data-root runs/cifar10/data --log-dir runs/cifar10/logs --device cuda --grad_sample_mode no_op | ||
| python -c "import torch; model = torch.load('model_best.pth.tar'); exit(0) if (model['best_acc1']>0.4 and model['best_acc1']<0.49) else exit(1)" | ||
| echo "::endgroup::" | ||
| imdb: | ||
|
Check failure on line 127 in .github/workflows/integration-tests.yml
|
||
| strategy: | ||
| matrix: | ||
| python_version: ["3.9"] | ||
| cuda_arch_version: ["11.8"] | ||
| fail-fast: false | ||
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | ||
| with: | ||
| runner: linux.g5.4xlarge.nvidia.gpu | ||
| gpu-arch-type: cuda | ||
| gpu-arch-version: ${{ matrix.cuda_arch_version }} | ||
| repository: pytorch/opacus | ||
| timeout: 60 | ||
| script: | | ||
| echo '::group::Create conda env with correct Python version' | ||
| set -x | ||
| PYTHON_VERSION="${{ matrix.python_version }}" | ||
| conda create --yes --quiet -n test python="${PYTHON_VERSION}" | ||
| conda activate test | ||
| python --version | grep "${PYTHON_VERSION}" | ||
| echo '::endgroup::' | ||
| echo "::group::Install dependencies via pip, including extra deps." | ||
| apt-get install apt | ||
| ./scripts/install_via_pip.sh | ||
| echo "::endgroup::" | ||
| echo "::group::Run nvidia-smi" | ||
| nvidia-smi | ||
| echo "::endgroup::" | ||
| echo "::group::Run imdb example end to end" | ||
| mkdir -p runs/imdb/data | ||
| mkdir -p runs/imdb/test-reports | ||
| echo "Using $(python -V)" | ||
| echo "Using $(pip -V)" | ||
| pip install --user datasets transformers | ||
| python examples/imdb.py --lr 0.02 --sigma 1.0 -c 1.0 --batch-size 64 --max-sequence-length 256 --epochs 2 --data-root runs/imdb/data --device cuda | ||
| python -c "import torch; accuracy = torch.load('run_results_imdb_classification.pt'); exit(0) if (accuracy>0.54 and accuracy<0.66) else exit(1)" | ||
| echo "::endgroup::" | ||
| charlstm: | ||
| strategy: | ||
| matrix: | ||
| python_version: ["3.9"] | ||
| cuda_arch_version: ["11.8"] | ||
| fail-fast: false | ||
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | ||
| with: | ||
| runner: linux.g5.4xlarge.nvidia.gpu | ||
| gpu-arch-type: cuda | ||
| gpu-arch-version: ${{ matrix.cuda_arch_version }} | ||
| repository: pytorch/opacus | ||
| timeout: 60 | ||
| script: | | ||
| echo '::group::Create conda env with correct Python version' | ||
| set -x | ||
| PYTHON_VERSION="${{ matrix.python_version }}" | ||
| conda create --yes --quiet -n test python="${PYTHON_VERSION}" | ||
| conda activate test | ||
| python --version | grep "${PYTHON_VERSION}" | ||
| echo '::endgroup::' | ||
| echo "::group::Install dependencies via pip, including extra deps." | ||
| apt-get install apt | ||
| ./scripts/install_via_pip.sh | ||
| echo "::endgroup::" | ||
| echo "::group::Run nvidia-smi" | ||
| nvidia-smi | ||
| echo "::endgroup::" | ||
| echo "::group::Run charlstm example end to end" | ||
| mkdir -p runs/charlstm/data | ||
| wget https://download.pytorch.org/tutorial/data.zip -O runs/charlstm/data/data.zip | ||
| unzip runs/charlstm/data/data.zip -d runs/charlstm/data | ||
| rm runs/charlstm/data/data.zip | ||
| mkdir -p runs/charlstm/test-reports | ||
| echo "Using $(python -V)" | ||
| echo "Using $(pip -V)" | ||
| pip install scikit-learn | ||
| python examples/char-lstm-classification.py --epochs=20 --learning-rate=2.0 --hidden-size=128 --delta=8e-5 --batch-size 400 --n-layers=1 --sigma=1.0 --max-per-sample-grad-norm=1.5 --data-root="runs/charlstm/data/data/names/" --device="cuda" --test-every 5 | ||
| python -c "import torch; accuracy = torch.load('run_results_chr_lstm_classification.pt'); exit(0) if (accuracy>0.60 and accuracy<0.80) else exit(1)" | ||
| echo "::endgroup::" | ||
| dcgan: | ||
| strategy: | ||
| matrix: | ||
| python_version: ["3.9"] | ||
| cuda_arch_version: ["11.8"] | ||
| fail-fast: false | ||
| uses: pytorch/test-infra/.github/workflows/linux_job.yml@main | ||
| with: | ||
| runner: linux.g5.4xlarge.nvidia.gpu | ||
| gpu-arch-type: cuda | ||
| gpu-arch-version: ${{ matrix.cuda_arch_version }} | ||
| repository: pytorch/opacus | ||
| timeout: 60 | ||
| script: | | ||
| echo '::group::Create conda env with correct Python version' | ||
| set -x | ||
| PYTHON_VERSION="${{ matrix.python_version }}" | ||
| conda create --yes --quiet -n test python="${PYTHON_VERSION}" | ||
| conda activate test | ||
| python --version | grep "${PYTHON_VERSION}" | ||
| echo '::endgroup::' | ||
| echo "::group::Install dependencies via pip, including extra deps." | ||
| apt-get install apt | ||
| ./scripts/install_via_pip.sh | ||
| echo "::endgroup::" | ||
| echo "::group::Run nvidia-smi" | ||
| nvidia-smi | ||
| echo "::endgroup::" | ||
| echo "::group::Run dcgan example end to end" | ||
| mkdir -p runs/dcgan/data | ||
| mkdir -p runs/dcgan/test-reports | ||
| echo "Using $(python -V) ($(which python))" | ||
| echo "Using $(pip -V) ($(which pip))" | ||
| python examples/dcgan.py --lr 2e-4 --sigma 0.7 -c 1.5 --batch-size 32 --epochs 1 --data-root runs/dcgan/data --device cuda | ||
| echo "::endgroup::" | ||
