wassname/ray

mirror of https://github.com/wassname/ray.git synced 2026-06-29 22:51:19 +08:00

T

Robert Nishihara 39b7abefc5 Fix test failures in actor_test.py. (#317 )

2017-03-01 23:26:39 -08:00

Updated tfutils to use new op naming (#284 )

2017-02-15 17:47:53 -08:00

help cmake find right python interpreter on mac (#251 )

2016-07-11 12:16:10 -07:00

Docker Updates (#308 )

2017-02-28 18:57:51 -08:00

Docker Updates (#308 )

2017-02-28 18:57:51 -08:00

Move documentation to ReadTheDocs. (#326 )

2017-02-27 21:14:31 -08:00

Move documentation to ReadTheDocs. (#326 )

2017-02-27 21:14:31 -08:00

Rename photon -> local scheduler. (#322 )

2017-02-27 12:24:07 -08:00

Make Ray code C++ compatible (#321 )

2017-03-01 01:17:24 -08:00

Fix test failures in actor_test.py. (#317 )

2017-03-01 23:26:39 -08:00

Windows compatibility (#57 )

2016-11-22 17:04:24 -08:00

Rename photon -> local scheduler. (#322 )

2017-02-27 12:24:07 -08:00

.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

.editorconfig

Update Windows support (#317 )

2016-07-28 13:11:13 -07:00

.gitignore

Switch build system to use CMake completely. (#200 )

2017-01-17 16:56:40 -08:00

.travis.yml

Move documentation to ReadTheDocs. (#326 )

2017-02-27 21:14:31 -08:00

build-docker.sh

Docker Updates (#308 )

2017-02-28 18:57:51 -08:00

build.sh

Adding flatbuffers and migrating flatcc to flatbuffers for plasma (#325 )

2017-02-28 18:47:40 -08:00

CMakeLists.txt

Rename photon -> local scheduler. (#322 )

2017-02-27 12:24:07 -08:00

LICENSE

Change license to Apache 2 (#20 )

2016-11-01 23:19:06 -07:00

pylintrc

adding pylint (#233 )

2016-07-08 12:39:11 -07:00

Ray.sln

Windows compatibility (#57 )

2016-11-22 17:04:24 -08:00

README.md

Move documentation to ReadTheDocs. (#326 )

2017-02-27 21:14:31 -08:00

README.md

Ray

Ray is an experimental distributed execution engine. It is under development and not ready to be used.

The goal of Ray is to make it easy to write machine learning applications that run on a cluster while providing the development and debugging experience of working on a single machine.

View the documentation.

Description

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Readme Multiple Licenses 111 MiB

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C++ 28.8%

Java 8.5%

TypeScript 1.7%

Starlark 1.4%

Other 2.8%