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f33b5a8d99
* show progress bar dependent on refresh_rate * test progress_bar_refresh control show bar * remove show_progress_bar from other tests * borda fixes * flake8 fix * changelog update prog bar refresh rate * move show_progress_bar to deprecated 0.9 api * rm show_progress_bar references, test deprecated * Update pytorch_lightning/trainer/__init__.py * fix test * changelog * minor CHANGELOG.md format * Update pytorch_lightning/trainer/__init__.py * Update pytorch_lightning/trainer/trainer.py Co-authored-by: Gerard Bentley <gbkh2015@mymail.pomona.edu> Co-authored-by: William Falcon <waf2107@columbia.edu> Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com> Co-authored-by: J. Borovec <jirka.borovec@seznam.cz>
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 AMP support
bash tests/install_AMP.sh
# 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:
- 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 (coverage is also installed as part of dev dependencies under tests/requirements.txt)
coverage run --source pytorch_lightning -m py.test pytorch_lightning tests examples -v --doctest-modules
# print coverage stats
coverage report -m
# exporting results
coverage xml