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Jirka Borovec ea59a99426 update org paths & convert logos (#685)
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2020-01-20 14:50:31 -05:00

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Markdown

# 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:
```bash
git clone https://github.com/PyTorchLightning/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:
1. At least 2 GPUs.
2. [NVIDIA-apex](https://github.com/NVIDIA/apex#linux) installed.
## Running Coverage
Make sure to run coverage on a GPU machine with at least 2 GPUs and NVIDIA apex installed.
```bash
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
```