ray-project/ray ray-0.5.2

on GitHub

Breaking Changes

• Local mode has changed from ray.init(driver_mode=ray.PYTHON_MODE) to ray.init(local_mode=True) to improve clarity.

Autoscaler and Cluster Setup

• Added many convenience commands such as ray up, ray attach, ray exec, and ray rsync to simplify launching jobs with Ray.
• Added experimental support for local/on-prem clusters.

RLlib

• Added the IMPALA algorithm.
• Added the ARS algorithm.
• Added the A2C variant of A3C.
• Added support for distributional DQN.
• Made improvements to multiagent support.
• Added support for model-based rollouts and custom policies.
• Added initial set of reference Atari results.

Tune

• SearchAlgorithms can now be used separately from TrialSchedulers and are found in ray.tune.suggest.
• All TrialSchedulers have been consolidated under ray.tune.schedulers.
• Minor API changes:
  • For Experiment configuration, repeat has been renamed to num_samples.
  • Now, register_trainable is handled implicitly.