From 74a2a5822a12a847cf449de0ec45e5b818d87104 Mon Sep 17 00:00:00 2001 From: William Falcon Date: Sun, 1 Mar 2020 22:27:37 -0500 Subject: [PATCH] Update README.md --- README.md | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index d97ebd1339..1c29d267b1 100644 --- a/README.md +++ b/README.md @@ -51,10 +51,12 @@ pip install pytorch-lightning ## Demo [Copy and run this COLAB!](https://colab.research.google.com/drive/1F_RNcHzTfFuQf-LeKvSlud6x7jXYkG31#scrollTo=HOk9c4_35FKg) -## What is it? -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. +## What is it? +Lightning is a way to organize your PyTorch code to decouple the science code from the engineering. It's more of a style-guide than a framework. By refactoring your code, we can automate most of the non-research code. Lightning guarantees tested, correct, modern best practices for the automated parts. -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. +Here's an example of how to organize PyTorch code into the LightningModule. + +![PT to PL](docs/source/_images/mnist_imgs/pt_to_pl.jpg) - 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. - If you are a scientist or production team, lightning is very simple to use with best practice defaults.