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<p align="center">
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<a href="https://williamfalcon.github.io/pytorch-lightning/">
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<img alt="" src="https://github.com/williamFalcon/pytorch-lightning/blob/master/docs/source/_static/lightning_logo.png" width="50">
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</a>
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</p>
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<h3 align="center">
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PyTorch Lightning
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</h3>
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<p align="center">
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The PyTorch Keras for ML researchers. More control. Less boilerplate.
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</p>
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<p align="center">
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<a href="https://badge.fury.io/py/pytorch-lightning"><img src="https://badge.fury.io/py/pytorch-lightning.svg" alt="PyPI version" height="18"></a>
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<a href="https://pepy.tech/project/pytorch-lightning"><img src="https://pepy.tech/badge/pytorch-lightning" alt="PyPI version" height="18"></a>
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<a href="https://pepy.tech/project/pytorch-lightning"><img src="https://img.shields.io/badge/python-3.6-blue.svg" alt="Supported Python Version" height="18"></a>
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<a href="https://github.com/williamFalcon/pytorch-lightning/blob/master/tests/README.md#running-coverage"><img src="https://github.com/williamFalcon/pytorch-lightning/blob/master/coverage.svg"></a>
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<a href="https://travis-ci.org/williamFalcon/pytorch-lightning"><img src="https://travis-ci.org/williamFalcon/pytorch-lightning.svg?branch=master"></a>
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<a href="https://williamfalcon.github.io/pytorch-lightning/"><img src="https://readthedocs.org/projects/pytorch-lightning/badge/?version=latest"></a>
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<a href="https://github.com/williamFalcon/pytorch-lightning/blob/master/LICENSE"><img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"></a>
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</p>
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# PyTorch Lightning
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**The PyTorch Keras for ML researchers. More control. Less boilerplate.**
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[](https://badge.fury.io/py/pytorch-lightning)
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[](https://pepy.tech/project/pytorch-lightning)
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[](https://travis-ci.org/williamFalcon/pytorch-lightning)
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[](https://ci.appveyor.com/project/Borda/pytorch-lightning)
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[](https://codecov.io/gh/Borda/pytorch-lightning)
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[](https://www.codefactor.io/repository/github/borda/pytorch-lightning)
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[](https://pytorch-lightning.readthedocs.io/en/latest)
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[](https://github.com/williamFalcon/pytorch-lightning/blob/master/LICENSE)
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Simple installation from PyPI
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```bash
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pip install pytorch-lightning
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```
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Everything in gray!
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You define the blue parts using the LightningModule interface:
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<p align="center">
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<a href="https://github.com/williamFalcon/pytorch-lightning/blob/master/docs/source/_static/overview_flat.jpg">
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<img alt="" src="https://github.com/williamFalcon/pytorch-lightning/blob/master/docs/source/_static/overview_flat.jpg" height="700px">
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</a>
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</p>
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```{.python}
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# what to do in the training loop
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## Tensorboard
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Lightning is fully integrated with tensorboard.
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<p align="center">
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<a href="https://williamfalcon.github.io/pytorch-lightning/Trainer/Logging/#tensorboard-support">
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<img alt="" src="https://github.com/williamFalcon/pytorch-lightning/blob/master/docs/source/_static/tf_loss.png" width="900px">
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</a>
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</p>
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Lightning also adds a text column with all the hyperparameters for this experiment.
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<p align="center">
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<a href="https://williamfalcon.github.io/pytorch-lightning/Trainer/Logging/#tensorboard-support">
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<img alt="" src="https://github.com/williamFalcon/pytorch-lightning/blob/master/docs/source/_static/tf_tags.png" width="900px">
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</a>
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</p>
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Simply note the path you set for the Experiment
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``` {.python}
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