mirror of
https://github.com/wassname/pytorch-lightning.git
synced 2026-09-22 13:30:11 +08:00
3f09b32df3
* initial structure * rebase * incorporate suggestions * update CHANGELOG.md * initial docs * fixes based on reviews * added trainer arg * update docs * added saving/restore of model state * initial tests * fix styling * added more tests * fix docs, backward compatility and progressbar * fix styling * docs update * updates based on review * changed saving to standard functions * consistent naming * fix formatting * improve docs, added support for nested fields, improve codecov * update CHANGELOG.md * Update lr_finder.rst * Update pytorch_lightning/trainer/trainer.py * Update trainer.py * Update CHANGELOG.md * Update path * restoring * test * attribs * docs * doc typo Co-authored-by: Nicki Skafte <nugginea@gmail.com> 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