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* Code for Supporting Shared Models * Running (with vnet modification) - needs to be tested for performance * Small fix for jenkins * Linting * linting * Summaries * Small refactoring + generalized to more domains * Addressing changes * Addressing changes * Update envs.py * Addressing changes * convnet * final touches * Merge - new model * final linting * Changing iterations back * Policy option removed, fixed small things * Nits * nit * Linting * Linting
Implement object table notification subscriptions and switch to using Redis modules for object table. (#134)
Ray
===
.. image:: https://travis-ci.org/ray-project/ray.svg?branch=master
:target: https://travis-ci.org/ray-project/ray
.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
:target: http://ray.readthedocs.io/en/latest/?badge=latest
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Ray is a flexible, high-performance distributed execution framework.
View the `documentation`_.
.. _`documentation`: http://ray.readthedocs.io/en/latest/index.html
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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