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Jirka Borovec 47659daa5f speed-up testing (#504 ) * extend CI timeout * add short MNIST * lower dataset and stop thr * refactor imports * formatting * early stop * play params * play params * minor refactoring # Conflicts: # pytorch_lightning/testing/__init__.py # pytorch_lightning/testing/lm_test_module.py # pytorch_lightning/testing/lm_test_module_base.py # pytorch_lightning/testing/lm_test_module_mixins.py # pytorch_lightning/testing/model.py # pytorch_lightning/testing/model_base.py # pytorch_lightning/testing/model_mixins.py # pytorch_lightning/testing/test_module.py # pytorch_lightning/testing/test_module_base.py # pytorch_lightning/testing/test_module_mixins.py * typo Co-Authored-By: Ir1dXD <sirius.caffrey@gmail.com> * Revert "refactor imports" This reverts commit `b86aee92` * update imports		2019-11-28 12:06:05 -05:00
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README.md	Update README.md	2019-10-23 06:13:31 -04:00
__init__.py	added init to test folder	2019-07-24 21:32:31 -04:00
debug.py	Minor imports cleaning (#402 )	2019-10-22 11:32:40 +03:00
requirements.txt	Fix setup-doc for pypi (#472 )	2019-11-09 00:59:14 -05:00
test_amp.py	speed-up testing (#504 )	2019-11-28 12:06:05 -05:00
test_cpu_models.py	speed-up testing (#504 )	2019-11-28 12:06:05 -05:00
test_gpu_models.py	speed-up testing (#504 )	2019-11-28 12:06:05 -05:00
test_logging.py	speed-up testing (#504 )	2019-11-28 12:06:05 -05:00
test_restore_models.py	speed-up testing (#504 )	2019-11-28 12:06:05 -05:00
test_trainer.py	speed-up testing (#504 )	2019-11-28 12:06:05 -05:00
utils.py	speed-up testing (#504 )	2019-11-28 12:06:05 -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/williamFalcon/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