Ray 0.8.1 Release Notes

Highlights

• ObjectIDs corresponding to ray.put() objects and task returns are now reference counted locally in Python and when passed into a remote task as an argument. ObjectIDs that have a nonzero reference count will not be evicted from the object store. Note that references for ObjectIDs passed into remote tasks inside of other objects (e.g., f.remote((ObjectID,)) or f.remote([ObjectID])) are not currently accounted for. (#6554)
• asyncio actor support: actors can now define async def method and Ray will run multiple method invocations in the same event loop. The maximum concurrency level can be adjusted with ActorClass.options(max_concurrency=2000).remote().
• asyncio ObjectID support: Ray ObjectIDs can now be directly awaited using the Python API. await my_object_id is similar to ray.get(my_object_id), but allows context switching to make the operation non-blocking. You can also convert an ObjectID to a asyncio.Future using ObjectID.as_future().
• Added experimental parallel iterators API (#6644, #6726): ParallelIterators can be used to more convienently load and process data into Ray actors. See the documentation for details.
• Added multiprocessing.Pool API (#6194): Ray now supports the multiprocessing.Pool API out of the box, so you can scale existing programs up from a single node to a cluster by only changing the import statment. See the documentation for details.

Core

• Deprecated Python 2 (#6581, #6601, #6624, #6665)
• Fixed bug when failing to import remote functions or actors with args and kwargs (#6577)
• Many improvements to the dashboard (#6493, #6516, #6521, #6574, #6590, #6652, #6671, #6683, #6810)
• Progress towards Windows compatibility (#6446, #6548, #6653, #6706)
• Redis now binds to localhost and has a password set by default (#6481)
• Added actor.__ray_kill__() to terminate actors immediately (#6523)
• Added 'ray stat' command for debugging (#6622)
• Added documentation for fault tolerance behavior (#6698)
• Treat static methods as class methods instead of instance methods in actors (#6756)

RLlib

• DQN distributional model: Replace all legacy tf.contrib imports with tf.keras.layers.xyz or tf.initializers.xyz (#6772)
• SAC site changes (#6759)
• PG unify/cleanup tf vs torch and PG functionality test cases (tf + torch) (#6650)
• SAC for Mujoco Environments (#6642)
• Tuple action dist tensors not reduced properly in eager mode (#6615)
• Changed foreach_policy to foreach_trainable_policy (#6564)
• Wrapper for the dm_env interface (#6468)

Tune

• Get checkpoints paths for a trial after tuning (#6643)
• Async restores and S3/GCP-capable trial FT (#6376)
• Usability errors PBT (#5972)
• Demo exporting trained models in pbt examples (#6533)
• Avoid duplication in TrialRunner execution (#6598)
• Update params for optimizer in reset_config (#6522)
• Support Type Hinting for py3 (#6571)

Other Libraries

• [serve] Pluggable Queueing Policy (#6492)
• [serve] Added BackendConfig (#6541)
• [sgd] Fault tolerance support for pytorch + revamp documentation (#6465)

Thanks

We thank the following contributors for their work on this release:

@chaokunyang, @Qstar, @simon-mo, @wlx65003, @stephanie-wang, @alindkhare, @ashione, @harrisonfeng, @JingGe, @pcmoritz, @zhijunfu, @BalaBalaYi, @kfstorm, @richardliaw, @mitchellstern, @michaelzhiluo, @ziyadedher, @istoica, @EyalSel, @ffbin, @raulchen, @edoakes, @chenk008, @frthjf, @mslapek, @gehring, @hhbyyh, @zzyunzhi, @zhu-eric, @MissiontoMars, @sven1977, @walterddr, @micafan, @inventormc, @robertnishihara, @ericl, @ZhongxiaYan, @mehrdadn, @jovany-wang, @ujvl, @bharatpn