From 715737cc06a2057c5a0e37b58f85a24b667a78ec Mon Sep 17 00:00:00 2001 From: Eric Liang Date: Sat, 23 Dec 2017 00:31:33 -0800 Subject: [PATCH] [docs] Add backlinks from hyperopt / rl algorithm examples to the built-on Ray libraries (#1356) --- .gitignore | 1 + doc/source/example-a3c.rst | 4 ++++ doc/source/example-hyperopt.rst | 5 +++++ doc/source/example-policy-gradient.rst | 5 +++++ 4 files changed, 15 insertions(+) diff --git a/.gitignore b/.gitignore index 8d41e61e2..9a813c64f 100644 --- a/.gitignore +++ b/.gitignore @@ -18,6 +18,7 @@ /src/common/format/*_generated.h /src/plasma/format/*_generated.h /src/local_scheduler/format/*_generated.h +/src/ray/gcs/format/*_generated.h # Redis temporary files *dump.rdb diff --git a/doc/source/example-a3c.rst b/doc/source/example-a3c.rst index 096619f19..665d49a36 100644 --- a/doc/source/example-a3c.rst +++ b/doc/source/example-a3c.rst @@ -11,6 +11,10 @@ View the `code for this example`_. .. _`Universe Starter Agent`: https://github.com/openai/universe-starter-agent .. _`code for this example`: https://github.com/ray-project/ray/tree/master/python/ray/rllib/a3c +.. note:: + + For an overview of Ray's reinforcement learning library, see `Ray RLlib `__. + To run the application, first install **ray** and then some dependencies: .. code-block:: bash diff --git a/doc/source/example-hyperopt.rst b/doc/source/example-hyperopt.rst index 950281c19..89eafa162 100644 --- a/doc/source/example-hyperopt.rst +++ b/doc/source/example-hyperopt.rst @@ -2,6 +2,11 @@ Hyperparameter Optimization =========================== This document provides a walkthrough of the hyperparameter optimization example. + +.. note:: + + To learn about Ray's built-in hyperparameter optimization framework, see `Ray.tune `__. + To run the application, first install some dependencies. .. code-block:: bash diff --git a/doc/source/example-policy-gradient.rst b/doc/source/example-policy-gradient.rst index 02f47a570..806764560 100644 --- a/doc/source/example-policy-gradient.rst +++ b/doc/source/example-policy-gradient.rst @@ -4,6 +4,11 @@ Policy Gradient Methods This code shows how to do reinforcement learning with policy gradient methods. View the `code for this example`_. +.. note:: + + For an overview of Ray's reinforcement learning library, see `Ray RLlib `__. + + To run this example, you will need to install `TensorFlow with GPU support`_ (at least version ``1.0.0``) and a few other dependencies.