From 150880e5e9bafc916f94289216741de19f07837b Mon Sep 17 00:00:00 2001
From: William Falcon <waf2107@columbia.edu>
Date: Mon, 20 Jul 2020 14:30:01 -0400
Subject: [PATCH] Add PTL to README.rst (#9594)

Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
---
 README.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.rst b/README.rst
index 9cdab3ef4..1d228b1a7 100644
--- a/README.rst
+++ b/README.rst
@@ -78,7 +78,7 @@ Tune Quick Start
 `Tune`_ is a library for hyperparameter tuning at any scale.
 
 - Launch a multi-node distributed hyperparameter sweep in less than 10 lines of code.
-- Supports any deep learning framework, including PyTorch, TensorFlow, and Keras.
+- Supports any deep learning framework, including PyTorch, `PyTorch Lightning <https://github.com/williamFalcon/pytorch-lightning>`_, TensorFlow, and Keras.
 - Visualize results with `TensorBoard <https://www.tensorflow.org/get_started/summaries_and_tensorboard>`__.
 - Choose among scalable SOTA algorithms such as `Population Based Training (PBT)`_, `Vizier's Median Stopping Rule`_, `HyperBand/ASHA`_.
 - Tune integrates with many optimization libraries such as `Facebook Ax <http://ax.dev>`_, `HyperOpt <https://github.com/hyperopt/hyperopt>`_, and `Bayesian Optimization <https://github.com/fmfn/BayesianOptimization>`_ and enables you to scale them transparently.