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Ray v0.6.2 Release Notes

Release Date: 2019-01-17 // over 5 years ago

  • 💥 Breaking Changes

    • ⏱ The timeout argument of ray.wait now uses seconds instead of milliseconds. #3706

    Core

    • 0️⃣ Limit default redis max memory to 10GB. #3630
    • Define a Node class to manage Ray processes. #3733
    • Garbage collection of actor dummy objects. #3593
    • Split profile table among many keys in the GCS. #3676
    • 🐳 Automatically try to figure out the memory limit in a docker container. #3605
    • 👌 Improve multi-threading support. #3672
    • ⚠ Push a warning to all users when large number of workers have been started. #3645
    • 🔨 Refactor code ray.ObjectID code. #3674

    Tune

    • 🔄 Change log handling for Tune. #3661
    • 👍 Tune now supports resuming from cluster failure. #3309, #3725, #3657, #3681
    • 👌 Support Configuration Merging for Suggestion Algorithms. #3584
    • 👌 Support nested PBT mutations. #3455

    RLlib

    • ➕ Add starcraft multiagent env as example. #3542
    • 👍 Allow development without needing to compile Ray. #3623
    • 📚 Documentation for I/O API and multi-agent improvements. #3650
    • Export policy model checkpoint. #3637
    • 🔨 Refactor PyTorch custom model support. #3634

    Autoscaler

    • ➕ Add an initial_workers option. #3530
    • ➕ Add kill and get IP commands to CLI for testing. #3731
    • 🔧 GCP allow manual network configuration. #3748

    Known Issues:

    • Object broadcasts on large clusters are inefficient. #2945