ray-0.6.1

Core

• Added experimental option to limit Redis memory usage. #3499
• Added option for restarting failed actors. #3332
• Fixed Plasma TensorFlow operator memory leak. #3448
• Fixed compatibility issue with TensorFlow and PyTorch. #3574
• Miscellaneous code refactoring and cleanup. #3563 #3564 #3461 #3511
• Documentation. #3427 #3535 #3138
• Several stability improvements. #3592 #3597

RLlib

• Multi-GPU support for Multi-agent PPO. #3479
• Unclipped actions are sent to learner. #3496
• rllib rollout now also preprocesses observations. #3512
• Basic Offline Data API added. #3473
• Improvements to metrics reporting in DQN. #3491
• AsyncSampler no longer auto-concats. #3556
• QMIX Implementation (Experimental). #3548
• IMPALA performance improvements. #3402
• Better error messages. #3444
• PPO performance improvements. #3552

Autoscaler

• Bug fixes, botocore handling fix. #3454 #3503 #3447

Ray Tune

• Lambdas now require tune.function wrapper. #3457
• Custom loggers, sync functions, and trial names are now supported. #3465
• Improvements to fault tolerance. #3414
• Variant Generator docs clarification. #3583
• trial_resources now renamed to resources_per_trial. #3580

Modin

• Modin 0.2.5 is now bundled with Ray
  • import modin after import ray
  • Modin 0.2.5 release notes
• Greater than memory support for object store. #3450

Known Issues

• Object broadcasts on large clusters are inefficient. #2945