一个针对强化学习和深度学习所设计的大规模分布式计算框架。

Simon Mo e4854b11f9 Revert "[gRPC] Migrate raylet client implementation to grpc (#5120)" 5 年之前
.github 6f737e6a50 Add CODEOWNERS file (#5259) 5 年之前
bazel 9c00616cdc Retry and exception for hang on memory store full (#5143) 5 年之前
ci 3bdd114282 [rllib] Better example rnn envs (#5300) 5 年之前
dev fd71ffde2f Improve release process 0.7.2 (#5187) 5 年之前
doc a62c5f40f6 [rllib] Document ModelV2 and clean up the models/ directory (#5277) 5 年之前
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java e4854b11f9 Revert "[gRPC] Migrate raylet client implementation to grpc (#5120)" 5 年之前
kubernetes 80b976efcb Ray namespace added for k8s (#4111) 5 年之前
python e4854b11f9 Revert "[gRPC] Migrate raylet client implementation to grpc (#5120)" 5 年之前
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README.rst

.. image:: https://github.com/ray-project/ray/raw/master/doc/source/images/ray_header_logo.png

.. 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

.. image:: https://img.shields.io/badge/pypi-0.7.1-blue.svg
:target: https://pypi.org/project/ray/

|

**Ray is a fast and simple framework for building and running distributed applications.**


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:

- `Tune`_: Hyperparameter Optimization Framework
- `RLlib`_: Scalable Reinforcement Learning
- `Distributed Training `__

.. _`Tune`: http://ray.readthedocs.io/en/latest/tune.html
.. _`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
----------------

- `ray-dev@googlegroups.com`_: For discussions about development or any general
questions.
- `StackOverflow`_: For questions about how to use Ray.
- `GitHub Issues`_: For reporting bugs and feature requests.
- `Pull Requests`_: For submitting code contributions.

.. _`ray-dev@googlegroups.com`: https://groups.google.com/forum/#!forum/ray-dev
.. _`GitHub Issues`: https://github.com/ray-project/ray/issues
.. _`StackOverflow`: https://stackoverflow.com/questions/tagged/ray
.. _`Pull Requests`: https://github.com/ray-project/ray/pulls