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Eric Liang 9a479b3a63
[rllib] Document creating an ensemble of envs; also add vector_index attribute to env config (#2513)
This also removes the async resetting code in VectorEnv. While that improves benchmark performance slightly, it substantially complicates env configuration and probably isn't worth it for most envs.

This makes it easy to efficiently support setups like Joint PPO: https://s3-us-west-2.amazonaws.com/openai-assets/research-covers/retro-contest/gotta_learn_fast_report.pdf

For example, for 188 envs, you could do something like num_envs: 10, num_envs_per_worker: 19.
2018-08-01 16:29:27 -07:00
.github Add docs for contributors. (#1191) 2017-11-10 00:40:19 -08:00
.travis [rllib] format with yapf (#2427) 2018-07-19 15:30:36 -07:00
cmake/Modules Upgrade arrow to include the plasma TensorFlow op (#2412) 2018-07-18 12:33:02 -07:00
doc [rllib] Document creating an ensemble of envs; also add vector_index attribute to env config (#2513) 2018-08-01 16:29:27 -07:00
docker [tune] Fix Categorical Space + Add Keras Example (#2401) 2018-07-17 23:52:52 +02:00
examples [rllib] _init renamed to _build_layers in example 2018-07-12 19:21:58 +02:00
java improve java api doc (#2508) 2018-07-29 20:41:11 -07:00
python [rllib] Document creating an ensemble of envs; also add vector_index attribute to env config (#2513) 2018-08-01 16:29:27 -07:00
site Add parameter server blog post. (#2398) 2018-07-16 21:51:39 -07:00
src [Issues 2403][xray] Fix raylet performance issues on scheduling queue (#2438) 2018-08-01 14:41:20 -07:00
test Introduce constant for ID_SIZE in python code. (#2517) 2018-07-31 12:40:53 -07:00
thirdparty/scripts Upgrade arrow to include pytorch fix (#2522) 2018-07-30 20:20:18 -07:00
.clang-format Implement object table notification subscriptions and switch to using Redis modules for object table. (#134) 2016-12-18 18:19:02 -08:00
.gitignore update to slf4j, remove DynamicLog (#2384) 2018-07-09 23:33:59 -07:00
.style.yapf YAPF, take 3 (#2098) 2018-05-19 16:07:28 -07:00
.travis.yml [xray] Implement task lease table, logic for deciding when to reconstruct a task (#2497) 2018-07-30 14:42:28 -07:00
build-docker.sh adding -x flag for better debugging during builds (#1079) 2017-10-04 13:56:14 -07:00
build.sh unify build dir for Python and Java (#2171) 2018-06-01 16:28:27 -07:00
CMakeLists.txt Upgrade arrow to include the plasma TensorFlow op (#2412) 2018-07-18 12:33:02 -07:00
CONTRIBUTING.rst Replace special single quote with regular single quote. (#1693) 2018-03-10 20:36:01 -08:00
LICENSE [rllib] Basic port of baselines/deepq to rllib (#709) 2017-07-07 18:37:00 +00:00
pylintrc adding pylint (#233) 2016-07-08 12:39:11 -07:00
README.rst Update Travis CI badge from travis-ci.org to travis-ci.com. (#2155) 2018-05-29 16:44:02 -07:00
scripts Improve yapf speed and document its usage (#2160) 2018-06-05 20:22:11 -07:00
setup_thirdparty.sh Use absolute path to get to thirdparty dir (#2442) 2018-07-20 15:12:25 -07:00

Ray
===

.. image:: https://travis-ci.com/ray-project/ray.svg?branch=master
    :target: https://travis-ci.com/ray-project/ray

.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
    :target: http://ray.readthedocs.io/en/latest/?badge=latest

|

Ray is a flexible, high-performance distributed execution framework.


Ray is easy to install: ``pip install ray``

Example Use
-----------

+------------------------------------------------+----------------------------------------------------+
| **Basic Python**                               | **Distributed with Ray**                           |
+------------------------------------------------+----------------------------------------------------+
|.. code-block:: python                          |.. code-block:: python                              |
|                                                |                                                    |
|  # Execute f serially.                         |  # Execute f in parallel.                          |
|                                                |                                                    |
|                                                |  @ray.remote                                       |
|  def f():                                      |  def f():                                          |
|      time.sleep(1)                             |      time.sleep(1)                                 |
|      return 1                                  |      return 1                                      |
|                                                |                                                    |
|                                                |                                                    |
|                                                |  ray.init()                                        |
|  results = [f() for i in range(4)]             |  results = ray.get([f.remote() for i in range(4)]) |
+------------------------------------------------+----------------------------------------------------+


Ray comes with libraries that accelerate deep learning and reinforcement learning development:

- `Ray Tune`_: Hyperparameter Optimization Framework
- `Ray RLlib`_: Scalable Reinforcement Learning

.. _`Ray Tune`: http://ray.readthedocs.io/en/latest/tune.html
.. _`Ray RLlib`: http://ray.readthedocs.io/en/latest/rllib.html

Installation
------------

Ray can be installed on Linux and Mac with ``pip install ray``.

To build Ray from source or to install the nightly versions, see the `installation documentation`_.

.. _`installation documentation`: http://ray.readthedocs.io/en/latest/installation.html

More Information
----------------

- `Documentation`_
- `Tutorial`_
- `Blog`_
- `Ray paper`_
- `Ray HotOS paper`_

.. _`Documentation`: http://ray.readthedocs.io/en/latest/index.html
.. _`Tutorial`: https://github.com/ray-project/tutorial
.. _`Blog`: https://ray-project.github.io/
.. _`Ray paper`: https://arxiv.org/abs/1712.05889
.. _`Ray HotOS paper`: https://arxiv.org/abs/1703.03924

Getting Involved
----------------

- Ask questions on our mailing list `ray-dev@googlegroups.com`_.
- Please report bugs by submitting a `GitHub issue`_.
- Submit contributions using `pull requests`_.

.. _`ray-dev@googlegroups.com`: https://groups.google.com/forum/#!forum/ray-dev
.. _`GitHub issue`: https://github.com/ray-project/ray/issues
.. _`pull requests`: https://github.com/ray-project/ray/pulls