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e3001a0929
* Add tests for distributed backend config * Refactor set_distributed_mode * Use gloo backend on cpu * Use 127.0.0.1 instead of 127.0.0.2 Not totally clear on why this is necessary, but it seemt to work * Update LightningDDP so that it works with CPU * Add ddp_cpu backend and num_processes Trainer arg * PEP8 * Fix test skipping. Inequalities are hard :/ * Skip ddp_cpu test on Windows * Make a few more cases fall back to ddp_cpu * New function name * Flake8 * Don't test distributed on MacOS with torch < 1.3 Support for distributed in MacOS was added in Torch 1.3.0 * Add ddp_cpu and num_processes to docs * Parametrize trainer config tests * Tweak warning Co-Authored-By: Jirka Borovec <Borda@users.noreply.github.com> * Remove redundant test * Replace pass branches with comments * Add missing warnings import * save_path -> root_dir * Use new rank_zero_warn * Whitespace * Apply suggestions from code review * formatting 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