3627c5bfac | ||
---|---|---|
.. | ||
README.md | ||
_build-packages.yml | ||
_legacy-checkpoints.yml | ||
call-clear-cache.yml | ||
ci-check-md-links.yml | ||
ci-checkpoints.yml | ||
ci-pkg-install.yml | ||
ci-rtfd.yml | ||
ci-schema.yml | ||
ci-tests-fabric.yml | ||
ci-tests-pytorch.yml | ||
cleanup-caches.yml | ||
code-checks.yml | ||
docker-build.yml | ||
docs-build.yml | ||
docs-tutorials.yml | ||
labeler-issue.yml | ||
labeler-pr.yml | ||
probot-auto-cc.yml | ||
probot-check-group.yml | ||
release-nightly.yml | ||
release-pkg.yml | ||
tpu-tests.yml |
README.md
Continuous Integration and Delivery
Brief description of all our automation tools used for boosting development performances.
Unit and Integration Testing
workflow file | action | accelerator |
---|---|---|
.github/workflows/ci-tests-fabric.yml | Run all tests except for accelerator-specific and standalone. | CPU |
.github/workflows/ci-tests-pytorch.yml | Run all tests except for accelerator-specific and standalone. | CPU |
.github/workflows/ci-tests-data.yml | Run unit and integration tests with data pipelining. | CPU |
.azure-pipelines/gpu-tests-fabric.yml | Run only GPU-specific tests, standalone*, and examples. | GPU |
.azure-pipelines/gpu-tests-pytorch.yml | Run only GPU-specific tests, standalone*, and examples. | GPU |
.azure-pipelines/gpu-benchmarks.yml | Run speed/memory benchmarks for parity with vanila PyTorch. | GPU |
.github/workflows/ci-flagship-apps.yml | Run end-2-end tests with full applications, including deployment to the production cloud. | CPU |
.github/workflows/ci-tests-pytorch.yml | Run all tests except for accelerator-specific, standalone and slow tests. | CPU |
.github/workflows/tpu-tests.yml | Run only TPU-specific tests. Requires that the PR title contains '[TPU]' | TPU |
* Each standalone test needs to be run in separate processes to avoid unwanted interactions between test cases.
-
Accelerators used in CI
- GPU: 2 x NVIDIA RTX 3090
- TPU: Google TPU v4-8
-
To check which versions of Python or PyTorch are used for testing in our CI, see the corresponding workflow files or checkgroup config file at
.github/checkgroup.yml
.
Documentation
workflow file | action |
---|---|
.github/workflows/docs-build.yml | Run doctest, linkcheck and full HTML build. |
.github/workflows/ci-rtfd.yml | Append link to the PR description with temporaty ReadTheDocs build docs. |
.github/workflows/ci-check-md-links.yml .github/markdown.links.config.json |
Validate links in markdown files. |
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/docker-build.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/ci-checkpoints.yml | Build checkpoints that are will be tested on release to ensure backwards-compatibility |
The published Docker Hub project is https://hub.docker.com/r/pytorchlightning/pytorch_lightning.
Deployment
workflow file | action |
---|---|
.github/workflows/docs-build.yml | Build the docs for each project and puch it to GCS with automatics deployment. |
.github/workflows/docker-build.yml | Build docker images used for releases and push them to the Docker Hub. |
.github/workflows/release-pkg.yml | Publish a release to PyPI and upload to the GH release page as artifact. |
.github/workflows/_legacy-checkpoints.yml | Add on request generate legacy checkpoints and upload them to AWS S3. |
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. |
.github/workflows/probot-check-group.yml .github/checkgroup.yml |
Checks whether the relevant jobs were successfully run based on the changed files in the PR |
.pre-commit-config.yaml | It applies a set of linters and formatters and can be registered with your local dev. If needed bot pushc changes to each PRs. |
.github/workflows/labeler-pr.yml, .github/label-change.yml | Integration of https://github.com/actions/labeler |
.github/workflows/labeler-issue.yml | Parse user provided lightning version and set it as label. |