Files
pytorch-lightning/tests
22a7264e9a improve partial Codecov (#1172)
* ignore in setup

* show report

* abs imports

* abstract pass

* cover loggers

* doctest trains

* locals

* pass

* revert tensorboard

* use tensorboardX

* revert tensorboardX

* fix trains

* Add TrainsLogger.set_credentials (#1179)

* Add TrainsLogger.set_credentials to control trains server configuration and authentication from code. Sync trains package version.
Fix CI Trains tests

* Add global TrainsLogger set_bypass_mode (#1187)

* Add global TrainsLogger set_bypass_mode skips all external communication

Co-authored-by: bmartinn <>

* rm some no-cov

Co-authored-by: Martin.B <51887611+bmartinn@users.noreply.github.com>
2020-03-19 09:14:29 -04:00
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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 tests/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:

  1. At least 2 GPUs.
  2. 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 (coverage is also installed as part of dev dependencies under tests/requirements.txt)
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