hunk.code_window:             a = None
               try:
                   if a_name in covered_a and o_name in covered_o:
                       stat = "skip"  # speed up tests by avoiding full grid
                   else:
                       a = get_agent_class(alg)(config=config, env="stub_env")
                       if alg not in ["DDPG", "ES", "ARS", "SAC"]:
  
hunk.labels: keep keep keep add keep keep keep
hunk.after_edit:                 # TODO(sven): Add necessary torch distributions.
                   elif torch and a_name in ["tuple", "multidiscrete"]:
                       stat = "unsupported"
  
hunk.file_path: rllib/tests/test_supported_spaces.py
hunk.type: add
file: ---
  layout: post
  title: "Ray: 0.5 Release"
  excerpt: "This post announces the release of Ray 0.5."
  date: 2018-07-06 14:00:00
  ---
  
  We are pleased to announce the 0.5 release of [Ray][1]. To upgrade to the latest
  version, run
  
  ```
  pip install -U ray
  ```
  
  ## Refactoring
  
  One primary development is a substantial refactoring of the backend, which is
  currently off by default, but can be turned on by starting Ray with the
  environment variable `RAY_USE_XRAY=1`. This will be turned on soon after more
  testing and development and will be on by default in the next release. Some
  highlights of the refactor include the following:
  - Merging the "local scheduler" and the "plasma manager" into a single "raylet"
    process (consisting of a "node manager" and an "object manager").
  - Faster object transfers by using multiple threads to send objects in chunks.
  - The introduction of a "lineage cache" to improve latency by removing the
    global control store from the scheduling critical path.
  - The removal of the global scheduler (which is replaced by direct node-manager
    to node-manager communication)
  - Providing a standardized table-based interface to the Redis-backed global
    control store.
  - A preliminary approach for automatically flushing global control store
    metadata to avoid out-of-memory errors for long-running jobs.
  
  Note that the refactoring is currently under development and does not yet
  support fault tolerance.
  
  ## RLlib Improvements
  
  A number of improvements have been made to [RLlib][2]:
  - Added DDPG [[1877]](https://github.com/ray-project/ray/pull/1877).
  - Added a policy server example [[2232]](https://github.com/ray-project/ray/pull/2232).
  - Multi-agent support [[2286]](https://github.com/ray-project/ray/pull/2286).
  - Modular policy graphs [[2294]](https://github.com/ray-project/ray/pull/2294).
  - RNN support [[2299]](https://github.com/ray-project/ray/pull/2299).
  - Vectorized environments [[2170]](https://github.com/ray-project/ray/pull/2170).
  - Many bug fixes.
  
  ## Tune
  
  A number of improvements have been made to [Tune][3]:
  - HyperOpt integration [[1763]](https://github.com/ray-project/ray/pull/1763).
  - Many bug fixes and improvements.
  
  ## Pandas on Ray
  
  Pandas on Ray has moved to the [Modin][5] project and will continue to be
  developed there.
  
  ## Autoscaler
  
  The [autoscaler][6] has grown more mature and now supports Google Cloud
  Platform:
  - Support for GCP [[2061]](https://github.com/ray-project/ray/pull/2061).
  - Many bug fixes and additional features.
  
  ## Java
  
  Ray now supports Java thanks to contributions from [Ant Financial][4]:
  - Support for Java (e.g., [[2092]](https://github.com/ray-project/ray/pull/2092) [[2094]](https://github.com/ray-project/ray/pull/2094) [[2151]](https://github.com/ray-project/ray/pull/2151) [[2171]](https://github.com/ray-project/ray/pull/2171) [[2225]](https://github.com/ray-project/ray/pull/2225) [[2245]](https://github.com/ray-project/ray/pull/2245)).
  
  ## Other Features
  
  - A named actors prototype [[2129]](https://github.com/ray-project/ray/pull/2129).
  - Usage of airspeed velocity for regression testing [[2113]](https://github.com/ray-project/ray/pull/2113).
  - More efficient serialization of numpy arrays [[1889]](https://github.com/ray-project/ray/pull/1889).
  
  
  [1]: https://github.com/ray-project/ray
  [2]: http://ray.readthedocs.io/en/latest/rllib.html
  [3]: http://ray.readthedocs.io/en/latest/tune.html
  [4]: https://www.antfin.com/
  [5]: https://github.com/modin-project/modin
  [6]: http://ray.readthedocs.io/en/latest/autoscaling.html
  