Ray is a flexible, high-performance distributed execution framework.
Ray comes with libraries that accelerate deep learning and reinforcement learning development:
- Ray Tune: Hyperparameter Optimization Framework
- Ray RLlib: A Scalable Reinforcement Learning Library
- Ray can be installed on Linux and Mac with
pip install ray.
- To build Ray from source, see the instructions for Ubuntu and Mac.
|Basic Python||Distributed with Ray|
import time def f(): time.sleep(1) return 1 # Execute f serially. results = [f() for i in range(4)]
import time import ray ray.init() @ray.remote def f(): time.sleep(1) return 1 # Execute f in parallel. object_ids = [f.remote() for i in range(4)] results = ray.get(object_ids)