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Add PTL to README.rst (#9594)

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Co-authored-by: Richard Liaw <rliaw@berkeley.edu>
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William Falcon
2020-07-20 11:30:01 -07:00
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co-authored by Richard Liaw
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@@ -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.