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README.md
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README.md
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@ -9,14 +9,14 @@
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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/williamFalcon/pytorch-lightning)
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[](https://github.com/williamFalcon/pytorch-lightning/tree/master/tests#running-coverage)
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[](https://travis-ci.org/PytorchLightning/pytorch-lightning)
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[](https://ci.appveyor.com/project/PytorchLightning/pytorch-lightning)
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[](https://github.com/PytorchLightning/pytorch-lightning/tree/master/tests#running-coverage)
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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://join.slack.com/t/pytorch-lightning/shared_invite/enQtODU5ODIyNTUzODQwLTFkMDg5Mzc1MDBmNjEzMDgxOTVmYTdhYjA1MDdmODUyOTg2OGQ1ZWZkYTQzODhhNzdhZDA3YmNhMDhlMDY4YzQ)
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[](https://github.com/williamFalcon/pytorch-lightning/blob/master/LICENSE)
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[](https://github.com/PytorchLightning/pytorch-lightning/blob/master/LICENSE)
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[](https://shields.io/)
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<!--
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@ -40,7 +40,7 @@ pip install pytorch-lightning
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## What is it?
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Lightning is a very lightweight wrapper on PyTorch that decouples the science code from the engineering code. It's more of a style-guide than a framework. By refactoring your code, we can automate most of the non-research code.
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To use Lightning, simply refactor your research code into the [LightningModule](https://github.com/williamFalcon/pytorch-lightning#how-do-i-do-use-it) format (the science) and Lightning will automate the rest (the engineering). Lightning guarantees tested, correct, modern best practices for the automated parts.
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To use Lightning, simply refactor your research code into the [LightningModule](https://github.com/PytorchLightning/pytorch-lightning#how-do-i-do-use-it) format (the science) and Lightning will automate the rest (the engineering). Lightning guarantees tested, correct, modern best practices for the automated parts.
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- If you are a researcher, Lightning is infinitely flexible, you can modify everything down to the way .backward is called or distributed is set up.
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- If you are a scientist or production team, lightning is very simple to use with best practice defaults.
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@ -56,7 +56,7 @@ This is how lightning separates the science (red) from the engineering (blue).
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You're probably tired of switching frameworks at this point. But it is a very quick process to refactor into the Lightning format (ie: hours). [Check out this tutorial](https://towardsdatascience.com/how-to-refactor-your-pytorch-code-to-get-these-42-benefits-of-pytorch-lighting-6fdd0dc97538)
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## Starting a new project?
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[Use our seed-project aimed at reproducibility!](https://github.com/williamFalcon/pytorch-lightning-conference-seed)
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[Use our seed-project aimed at reproducibility!](https://github.com/PytorchLightning/pytorch-lightning-conference-seed)
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## Why do I want to use lightning?
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Every research project starts the same, a model, a training loop, validation loop, etc. As your research advances, you're likely to need distributed training, 16-bit precision, checkpointing, gradient accumulation, etc.
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@ -66,17 +66,17 @@ Lightning sets up all the boilerplate state-of-the-art training for you so you c
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---
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## README Table of Contents
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- [How do I use it](https://github.com/williamFalcon/pytorch-lightning#how-do-i-do-use-it)
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- [What lightning automates](https://github.com/williamFalcon/pytorch-lightning#what-does-lightning-control-for-me)
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- [Tensorboard integration](https://github.com/williamFalcon/pytorch-lightning#tensorboard)
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- [Lightning features](https://github.com/williamFalcon/pytorch-lightning#lightning-automates-all-of-the-following-each-is-also-configurable)
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- [Examples](https://github.com/williamFalcon/pytorch-lightning#examples)
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- [Tutorials](https://github.com/williamFalcon/pytorch-lightning#tutorials)
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- [Contributing](https://github.com/williamFalcon/pytorch-lightning/blob/master/.github/CONTRIBUTING.md)
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- [Bleeding edge install](https://github.com/williamFalcon/pytorch-lightning#bleeding-edge)
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- [Lightning Design Principles](https://github.com/williamFalcon/pytorch-lightning#lightning-design-principles)
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- [Asking for help](https://github.com/williamFalcon/pytorch-lightning#asking-for-help)
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- [FAQ](https://github.com/williamFalcon/pytorch-lightning#faq)
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- [How do I use it](https://github.com/PytorchLightning/pytorch-lightning#how-do-i-do-use-it)
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- [What lightning automates](https://github.com/PytorchLightning/pytorch-lightning#what-does-lightning-control-for-me)
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- [Tensorboard integration](https://github.com/PytorchLightning/pytorch-lightning#tensorboard)
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- [Lightning features](https://github.com/PytorchLightning/pytorch-lightning#lightning-automates-all-of-the-following-each-is-also-configurable)
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- [Examples](https://github.com/PytorchLightning/pytorch-lightning#examples)
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- [Tutorials](https://github.com/PytorchLightning/pytorch-lightning#tutorials)
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- [Contributing](https://github.com/PytorchLightning/pytorch-lightning/blob/master/.github/CONTRIBUTING.md)
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- [Bleeding edge install](https://github.com/PytorchLightning/pytorch-lightning#bleeding-edge)
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- [Lightning Design Principles](https://github.com/PytorchLightning/pytorch-lightning#lightning-design-principles)
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- [Asking for help](https://github.com/PytorchLightning/pytorch-lightning#asking-for-help)
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- [FAQ](https://github.com/PytorchLightning/pytorch-lightning#faq)
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---
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@ -347,10 +347,10 @@ Lightning also adds a text column with all the hyperparameters for this experime
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- [Run test set](https://williamfalcon.github.io/pytorch-lightning/Trainer/Testing%20loop/)
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## Examples
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- [GAN](https://github.com/williamFalcon/pytorch-lightning/tree/master/pl_examples/domain_templates/gan.py)
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- [MNIST](https://github.com/williamFalcon/pytorch-lightning/tree/master/pl_examples/basic_examples)
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- [Other projects using Lightning](https://github.com/williamFalcon/pytorch-lightning/network/dependents?package_id=UGFja2FnZS0zNzE3NDU4OTM%3D)
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- [Multi-node](https://github.com/williamFalcon/pytorch-lightning/tree/master/pl_examples/multi_node_examples)
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- [GAN](https://github.com/PytorchLightning/pytorch-lightning/tree/master/pl_examples/domain_templates/gan.py)
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- [MNIST](https://github.com/PytorchLightning/pytorch-lightning/tree/master/pl_examples/basic_examples)
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- [Other projects using Lightning](https://github.com/PytorchLightning/pytorch-lightning/network/dependents?package_id=UGFja2FnZS0zNzE3NDU4OTM%3D)
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- [Multi-node](https://github.com/PytorchLightning/pytorch-lightning/tree/master/pl_examples/multi_node_examples)
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## Tutorials
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- [Basic Lightning use](https://towardsdatascience.com/supercharge-your-ai-research-with-pytorch-lightning-337948a99eec)
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@ -364,7 +364,7 @@ Welcome to the Lightning community!
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If you have any questions, feel free to:
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1. [read the docs](https://williamfalcon.github.io/pytorch-lightning/).
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2. [Search through the issues](https://github.com/williamFalcon/pytorch-lightning/issues?utf8=%E2%9C%93&q=my++question).
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2. [Search through the issues](https://github.com/PytorchLightning/pytorch-lightning/issues?utf8=%E2%9C%93&q=my++question).
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3. [Ask on stackoverflow](https://stackoverflow.com/questions/ask?guided=false) with the tag pytorch-lightning.
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If no one replies to you quickly enough, feel free to post the stackoverflow link to our Gitter chat!
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@ -415,18 +415,18 @@ Nope. Please use anaconda or miniconda.
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If you can't wait for the next release, install the most up to date code with:
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* using GIT (locally clone whole repo with full history)
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```bash
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pip install git+https://github.com/williamFalcon/pytorch-lightning.git@master --upgrade
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pip install git+https://github.com/PytorchLightning/pytorch-lightning.git@master --upgrade
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```
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* using instant zip (last state of the repo without git history)
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```bash
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pip install https://github.com/williamFalcon/pytorch-lightning/archive/master.zip --upgrade
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pip install https://github.com/PytorchLightning/pytorch-lightning/archive/master.zip --upgrade
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```
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### Any release installation
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You can also install any past release from this repository:
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```bash
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pip install https://github.com/williamFalcon/pytorch-lightning/archive/0.4.4.zip --upgrade
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pip install https://github.com/PytorchLightning/pytorch-lightning/archive/0.4.4.zip --upgrade
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```
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## Bibtex
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year = {2019},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/williamFalcon/pytorch-lightning}}
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howpublished = {\url{https://github.com/PytorchLightning/pytorch-lightning}}
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}
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```
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