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Ray v0.6.1 Release Notes

Release Date: 2018-12-24 // over 5 years ago

  • 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

    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
    • 👍 Greater than memory support for object store. #3450

    Known Issues

    • Object broadcasts on large clusters are inefficient. #2945