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Author
Last Commit
Oct. 23, 2018
Created
Oct. 25, 2016

Ray

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

Ray is easy to install: pip install ray

Example Use

Basic Python Distributed with Ray
# Execute f serially.


def f():
    time.sleep(1)
    return 1



results = [f() for i in range(4)]
# Execute f in parallel.

@ray.remote
def f():
    time.sleep(1)
    return 1


ray.init()
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

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.

More Information

Getting Involved

Latest Releases
ray-0.5.3
 Sep. 28 2018
ray-0.5.3
 Sep. 25 2018
ray-0.5.2
 Aug. 29 2018
ray-0.5.1
 Aug. 28 2018
ray-0.5.0
 Jul. 6 2018