8.4 KiB
8.4 KiB
Continuous Integration and Delivery
Unit and Integration Testing
| workflow name | workflow file | action | accelerator* | (Python, PyTorch) | OS |
|---|---|---|---|---|---|
| Test PyTorch full | .github/workflows/ci-pytorch-test-full.yml | Run all tests except for accelerator-specific, standalone and slow tests. | CPU | (3.7, 1.9), (3.7, 1.12), (3.9, 1.9), (3.9, 1.12) | linux, mac, windows |
| Test PyTorch with Conda | .github/workflows/ci-pytorch-test-conda.yml | Same as ci-pytorch-test-full.yml but with dependencies installed with conda. | CPU | (3.8, 1.9), (3.8, 1.10), (3.8, 1.11), (3.9, 1.12) | linux |
| Test slow | .github/workflows/ci-pytorch-test-slow.yml | Run only slow tests. Slow tests usually need to spawn threads and cannot be speed up or simplified. | CPU | (3.7, 1.11) | linux, mac, windows |
| pytorch-lightning (IPUs) | .azure-pipelines/ipu-tests.yml | Run only IPU-specific tests. | IPU | (3.8, 1.9) | linux |
| pytorch-lightning (HPUs) | .azure-pipelines/hpu-tests.yml | Run only HPU-specific tests. | HPU | (3.8, 1.10) | linux |
| pytorch-lightning (GPUs) | .azure-pipelines/gpu-tests.yml | Run all CPU and GPU-specific tests, standalone, and examples. Each standalone test needs to be run in separate processes to avoid unwanted interactions between test cases. | GPU | (3.9, 1.12) | linux |
| PyTorchLightning.Benchmark | .azure-pipelines/gpu-benchmark.yml | Run speed/memory benchmarks for parity with pure PyTorch. | GPU | (3.9, 1.12) | linux |
| test-on-tpus | .circleci/config.yml | Run only TPU-specific tests. | TPU | (3.7, 1.12) | linux |
- *Accelerators used in CI
- GPU: 2 x NVIDIA Tesla V100
- TPU: Google GKE TPUv3
- IPU: Colossus MK1 IPU
- HPU: Intel Habana Gaudi SYS-420GH-TNGR which has 8 Gaudi accelerators
Documentation
| workflow file | action |
|---|---|
| .github/workflows/docs-checks.yml | Run doctest. |
Code Quality
| workflow file | action |
|---|---|
| .codecov.yml | Measure test coverage with codecov.io |
| .github/workflows/code-checks.yml | Check Python typing with MyPy. |
| .github/workflows/ci-schema.yml | Validate the syntax of workflow files. |
Others
| workflow file | action |
|---|---|
| .github/workflows/cicd-pytorch-dockers.yml | Build docker images used for testing in CI. If run on nightly schedule, push to the Docker Hub. |
| .github/workflows/ci-pkg-install.yml | Test if pytorch-lightning is successfully installed using pip. |
| .github/workflows/events-recurrent.yml | Terminate TPU jobs that live more than one hour to avoid possible resource exhaustion due to hangs. |
Deployment
| workflow file | action |
|---|---|
| .github/workflows/release-pypi.yml | Publish a release to PyPI. |
| .github/workflows/release-docker.yml | Build Docker images from dockers/*/Dockerfile and publish them on hub.docker.com. |
| .github/workflows/legacy-checkpoints.yml | App on request generate legacy checkpoints and upload them to AWS S3. |
| .github/workflows/events-nightly.yml | Publish the package to TestPyPI. Publish Docker images on hub.docker.com. |
Bots
| workflow file | action |
|---|---|
| .github/mergify.yml | Label PRs as conflicts or ready, and request reviews if needed. |
| .github/stale.yml | Close inactive issues/PRs sometimes after adding the "won't fix" label to them. |
| .github/workflows/probot-auto-cc.yml, .github/lightning-probot.yml | Notify maintainers of interest depending on labels added to an issue We utilize lightning-probot forked from PyTorch’s probot. |
| .pre-commit-config.yaml | pre-commit.ci runs a set of linters and formatters, such as black, flake8 and isort. When formatting is applied, the bot pushes a commit with its change. This configuration is also used for running pre-commit locally. |
| .github/workflows/ci-pr-gatekeeper.yml | Prevent PRs from merging into master without any Grid.ai employees’ approval. |