106 lines
3.7 KiB
Markdown
106 lines
3.7 KiB
Markdown
# PyTorch-Lightning Tests
|
|
|
|
Most of the tests in PyTorch Lightning train a [BoringModel](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/tests/helpers/boring_model.py) under various trainer conditions (ddp, ddp2+amp, etc...). Want to add a new test case and not sure how? [Talk to us!](https://www.pytorchlightning.ai/community)
|
|
|
|
## Running tests
|
|
|
|
**Local:** Testing your work locally will help you speed up the process since it allows you to focus on particular (failing) test-cases.
|
|
To setup a local development environment, install both local and test dependencies:
|
|
|
|
```bash
|
|
# clone the repo
|
|
git clone https://github.com/Lightning-AI/lightning.git
|
|
cd lightning
|
|
|
|
# install required depedencies
|
|
export PACKAGE_NAME=pytorch
|
|
python -m pip install ".[dev, examples]"
|
|
# install pre-commit (optional)
|
|
python -m pip install pre-commit
|
|
pre-commit install
|
|
```
|
|
|
|
Additionally, for testing backward compatibility with older versions of PyTorch Lightning, you also need to download all saved version-checkpoints from the public AWS storage. Run the following script to get all saved version-checkpoints:
|
|
|
|
```bash
|
|
bash .actions/pull_legacy_checkpoints.sh
|
|
```
|
|
|
|
Note: These checkpoints are generated to set baselines for maintaining backward compatibility with legacy versions of PyTorch Lightning. Details of checkpoints for back-compatibility can be found [here](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/legacy/README.md).
|
|
|
|
You can run the full test suite in your terminal via this make script:
|
|
|
|
```bash
|
|
make test
|
|
```
|
|
|
|
Note: if your computer does not have multi-GPU or TPU these tests are skipped.
|
|
|
|
**GitHub Actions:** For convenience, you can also use your own GHActions building which will be triggered with each commit.
|
|
This is useful if you do not test against all required dependency versions.
|
|
|
|
**Docker:** Another option is to utilize the [pytorch lightning cuda base docker image](https://hub.docker.com/repository/docker/pytorchlightning/pytorch_lightning/tags?page=1&name=cuda). You can then run:
|
|
|
|
```bash
|
|
python -m pytest src/pytorch_lightning tests/tests_pytorch -v
|
|
```
|
|
|
|
You can also run a single test as follows:
|
|
|
|
```bash
|
|
python -m pytest -v tests/tests_pytorch/trainer/test_trainer_cli.py::test_default_args
|
|
```
|
|
|
|
### Conditional Tests
|
|
|
|
To test models that require GPU make sure to run the above command on a GPU machine.
|
|
The GPU machine must have at least 2 GPUs to run distributed tests.
|
|
|
|
Note that this setup will not run tests that require specific packages installed
|
|
such as Horovod, FairScale, NVIDIA/apex, NVIDIA/DALI, etc.
|
|
You can rely on our CI to make sure all these tests pass.
|
|
|
|
### Standalone Tests
|
|
|
|
There are certain standalone tests, which you can run using:
|
|
|
|
```bash
|
|
PL_RUN_STANDALONE_TESTS=1 python -m pytest -v tests/tests_pytorch/trainer/
|
|
# or
|
|
./tests/run_standalone_tests.sh tests/tests_pytorch/trainer/
|
|
```
|
|
|
|
## Running Coverage
|
|
|
|
Make sure to run coverage on a GPU machine with at least 2 GPUs and NVIDIA apex installed.
|
|
|
|
```bash
|
|
cd pytorch-lightning
|
|
|
|
# generate coverage (coverage is also installed as part of dev dependencies under requirements/pytorch/devel.txt)
|
|
coverage run --source pytorch_lightning -m pytest src/pytorch_lightning tests/tests_pytorch pl_examples -v
|
|
|
|
# print coverage stats
|
|
coverage report -m
|
|
|
|
# exporting results
|
|
coverage xml
|
|
```
|
|
|
|
## Building test image
|
|
|
|
You can build it on your own, note it takes lots of time, be prepared.
|
|
|
|
```bash
|
|
git clone <git-repository>
|
|
docker image build -t pytorch_lightning:devel-torch1.9 -f dockers/cuda-extras/Dockerfile --build-arg TORCH_VERSION=1.9 .
|
|
```
|
|
|
|
To build other versions, select different Dockerfile.
|
|
|
|
```bash
|
|
docker image list
|
|
docker run --rm -it pytorch_lightning:devel-torch1.9 bash
|
|
docker image rm pytorch_lightning:devel-torch1.9
|
|
```
|