ray-project/ray ray-0.7.1

on GitHub

Core

• Change global state API. #4857
  • ray.global_state.client_table() -> ray.nodes()
  • ray.global_state.task_table() -> ray.tasks()
  • ray.global_state.object_table() -> ray.objects()
  • ray.global_state.chrome_tracing_dump() -> ray.timeline()
  • ray.global_state.cluster_resources() -> ray.cluster_resources()
  • ray.global_state.available_resources() -> ray.available_resources()
• Export remote functions lazily. #4898
• Begin moving worker code to C++. #4875, #4899, #4898
• Upgrade arrow to latest master. #4858
• Upload wheels to S3 under <branch-name>/<commit-id>. #4949
• Add hash table to Redis-Module. #4911
• Initial support for distributed training with PyTorch. #4797

Tune

• Disallow setting resources_per_trial when it is already configured. #4880
• Initial experiment tracking support. #4362

RLlib

• Begin deprecating Python 2 support in RLlib. #4832
• TensorFlow 2 compatibility. #4802
• Allow Torch policies access to full action input dict in extra_action_out_fn. #4894
• Allow access to batches prior to postprocessing. #4871
• Port algorithms to build_trainer() pattern. #4823
• Rename PolicyEvaluator -> RolloutWorker. #4820
• Rename PolicyGraph -> Policy, move from evaluation/ to policy/. #4819
• Support continuous action distributions in IMPALA/APPO. #4771

(Revision: 6/23/2019 - Accidentally included commits that were not part of the release.)