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Jirka BorovecandIr1dXD 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

__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

README.md

Update README.md

2019-10-23 06:13:31 -04:00

requirements.txt

Fix setup-doc for pypi (#472 )

2019-11-09 00:59:14 -05:00

test_amp.py

speed-up testing (#504 )

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test_cpu_models.py

speed-up testing (#504 )

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test_gpu_models.py

speed-up testing (#504 )

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test_logging.py

speed-up testing (#504 )

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test_restore_models.py

speed-up testing (#504 )

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test_trainer.py

speed-up testing (#504 )

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utils.py

speed-up testing (#504 )

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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