History

Aljoscha Steffens 9eb1907151 separate requirements for logger dependencies (#792 ) * added file that contains information on the minimal versions needed for the supported loggers * copied minimal version, combined files, deleted duplicates * sorted functions in tests/test_loggers.py to be consistent * expanded wandb logging test; added minimal versions for requirements-extra.txt; increased the amount of training data that is used for tests * formatting * added requirements-extra.txt to MANIFEST.in * reverted wandb test; ensured minimal version for dependencies in requirements-extra.txt in ci-testing.yml		2020-02-21 13:30:27 -05:00
..
models	new way of passing dataloaders (#759 )	2020-02-19 06:00:08 -05:00
README.md	update org paths & convert logos (#685 )	2020-01-20 14:50:31 -05:00
__init__.py	added init to test folder	2019-07-24 21:32:31 -04:00
conftest.py	Fix amp tests (#661 )	2020-01-05 14:34:25 -05:00
requirements.txt	separate requirements for logger dependencies (#792 )	2020-02-21 13:30:27 -05:00
test_amp.py	Enable TPU support (#868 )	2020-02-17 16:01:20 -05:00
test_cpu_models.py	drop torchvision, tests only (#797 )	2020-02-10 22:47:18 -05:00
test_gpu_models.py	Enable TPU support (#868 )	2020-02-17 16:01:20 -05:00
test_logging.py	separate requirements for logger dependencies (#792 )	2020-02-21 13:30:27 -05:00
test_profiler.py	clean up tests/test_profiler.py (#867 )	2020-02-19 07:09:28 -05:00
test_restore_models.py	drop torchvision, tests only (#797 )	2020-02-10 22:47:18 -05:00
test_trainer.py	new way of passing dataloaders (#759 )	2020-02-19 06:00:08 -05:00

README.md

PyTorch-Lightning Tests

Most PL tests train a full MNIST model under various trainer conditions (ddp, ddp2+amp, etc...). This provides testing for most combinations of important settings. The tests expect the model to perform to a reasonable degree of testing accuracy to pass.

Running tests

The automatic travis tests ONLY run CPU-based tests. Although these cover most of the use cases, run on a 2-GPU machine to validate the full test-suite.

To run all tests do the following:

git clone https://github.com/PyTorchLightning/pytorch-lightning
cd pytorch-lightning

# install module locally
pip install -e .

# install dev deps
pip install -r requirements.txt

# run tests
py.test -v

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.
NVIDIA-apex installed.

Running Coverage

Make sure to run coverage on a GPU machine with at least 2 GPUs and NVIDIA apex installed.

cd pytorch-lightning

# generate coverage 
pip install coverage
coverage run --source pytorch_lightning -m py.test pytorch_lightning tests examples -v --doctest-modules

# print coverage stats
coverage report -m

# exporting resulys
coverage xml
codecov -t 17327163-8cca-4a5d-86c8-ca5f2ef700bc  -v