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ad4b03bf7fa3e8a9bee58a874e109c37105245a0
* new path for python build * add flag * build tar using git archive * no exit from start_ray.sh * update Docker instructions * update build docker script * add git revision * fix typo * bug fixes and clarifications * mend * add objectmanager ports to docker instructions * rewording * Small updates to documentation.
Implement object table notification subscriptions and switch to using Redis modules for object table. (#134)
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.
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