Ray === .. raw:: html Fork me on GitHub *Ray is a fast and simple framework for building and running distributed applications.* Ray is easy to install: ``pip install ray`` Example Use ----------- +------------------------------------------------+----------------------------------------------------+ | **Basic Python** | **Distributed with Ray** | +------------------------------------------------+----------------------------------------------------+ |.. code-block:: python |.. code-block:: python | | | | | # Execute f serially. | # Execute f in parallel. | | | | | | @ray.remote | | def f(): | def f(): | | time.sleep(1) | time.sleep(1) | | return 1 | return 1 | | | | | | | | | ray.init() | | results = [f() for i in range(4)] | results = ray.get([f.remote() for i in range(4)]) | +------------------------------------------------+----------------------------------------------------+ To launch a Ray cluster, either privately, on AWS, or on GCP, `follow these instructions `_. View the `codebase on GitHub`_. .. _`codebase on GitHub`: https://github.com/ray-project/ray Ray comes with libraries that accelerate deep learning and reinforcement learning development: - `Tune`_: Scalable Hyperparameter Search - `RLlib`_: Scalable Reinforcement Learning - `Distributed Training `__ .. _`Tune`: tune.html .. _`RLlib`: rllib.html .. toctree:: :maxdepth: 1 :caption: Installation installation.rst deploy-on-kubernetes.rst install-on-docker.rst installation-troubleshooting.rst .. toctree:: :maxdepth: 1 :caption: Getting Started tutorial.rst api.rst actors.rst using-ray-with-gpus.rst signals.rst async_api.rst .. toctree:: :maxdepth: 1 :caption: Cluster Usage autoscaling.rst using-ray-on-a-cluster.rst .. toctree:: :maxdepth: 1 :caption: Tune tune.rst tune-usage.rst tune-schedulers.rst tune-searchalg.rst tune-package-ref.rst tune-design.rst tune-examples.rst tune-contrib.rst .. toctree:: :maxdepth: 1 :caption: RLlib rllib.rst rllib-training.rst rllib-env.rst rllib-models.rst rllib-algorithms.rst rllib-offline.rst rllib-concepts.rst rllib-examples.rst rllib-dev.rst rllib-package-ref.rst .. toctree:: :maxdepth: 1 :caption: Other Libraries distributed_training.rst pandas_on_ray.rst .. toctree:: :maxdepth: 1 :caption: Examples example-rl-pong.rst example-policy-gradient.rst example-parameter-server.rst example-newsreader.rst example-resnet.rst example-a3c.rst example-lbfgs.rst example-evolution-strategies.rst example-cython.rst example-streaming.rst using-ray-with-tensorflow.rst .. toctree:: :maxdepth: 1 :caption: Design internals-overview.rst serialization.rst fault-tolerance.rst plasma-object-store.rst resources.rst tempfile.rst .. toctree:: :maxdepth: 1 :caption: Help troubleshooting.rst user-profiling.rst security.rst development.rst profiling.rst contact.rst