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@amogkam amogkam released this 22 Apr 22:28
· 1 commit to releases/1.3.0 since this release
ray-1.3.0
2a02b97

Release v1.3.0 Notes

Highlights

Ray Cluster Launcher

💫Enhancements:

  • Observability improvements (#14816, #14608)
  • Worker nodes no longer killed on autoscaler failure (#14424)
  • Better validation for min_workers and max_workers (#13779)
  • Auto detect memory resource for AWS and K8s (#14567)
  • On autoscaler failure, propagate error message to drivers (#14219)
  • Avoid launching GPU nodes when the workload only has CPU tasks (#13776)
  • Autoscaler/GCS compatibility (#13970, #14046, #14050)
  • Testing (#14488, #14713)
  • Migration of configs to multi-node-type format (#13814, #14239)
  • Better config validation (#14244, #13779)
  • Node-type max workers defaults infinity (#14201)

🔨 Fixes:

Ray Client

💫Enhancements:

🔨 Fixes:

  • Hook runtime context (#13750)
  • Fix mutual recursion (#14122)
  • Set gRPC max message size (#14063)
  • Monitor stream errors (#13386)
  • Fix dependencies (#14654)
  • Fix ray.get ctrl-c (#14425)
  • Report error deserialization errors (#13749)
  • Named actor refcounting fix (#14753)
  • RayTaskError serialization (#14698)
  • Multithreading fixes (#14701)

Ray Core

🎉 New Features:

🔨 Fixes:

  • Ray is now using c++14.
  • Fixed high CPU breaking raylets with heartbeat missing errors (#13963, #14301)
  • Fixed high CPU issues from raylet during object transfer (#13724)
  • Improvement in placement group APIs including better Java support (#13821, #13858, #13582, #15049, #13821)

Ray Data Processing

🎉 New Features:

  • Object spilling is turned on by default. Check out the documentation.
  • Dask-on-Ray and Spark-on-Ray are fully ready to use. Please try them out and give us feedback!
  • Dask-on-Ray is now compatible with Dask 2021.4.0.
  • Dask-on-Ray now works natively with dask.persist().

🔨 Fixes:

🏗 Architecture refactoring:

  • Various architectural improvements in object spilling and memory management. For more details, check out the whitepaper.
  • Locality-aware scheduling is turned on by default.
  • Moved from centralized GCS-based object directory protocol to decentralized owner-to-owner protocol, yielding better cluster scalability.

RLlib

🎉 New Features:

  • R2D2 implementation for torch and tf. (#13933)
  • PlacementGroup support (all RLlib algos now return PlacementGroupFactory from Trainer.default_resource_request). (#14289)
  • Multi-GPU support for tf-DQN/PG/A2C. (#13393)

💫Enhancements:

  • Documentation: Update documentation for Curiosity's support of continuous actions (#13784); CQL documentation (#14531)
  • Attention-wrapper works with images and supports prev-n-actions/rewards options. (#14569)
  • rllib rollout runs in parallel by default via Trainer’s evaluation worker set. (#14208)
  • Add env rendering (customizable) and video recording options (for non-local mode; >0 workers; +evaluation-workers) and episode media logging. (#14767, #14796)
  • Allow SAC to use custom models as Q- or policy nets and deprecate "state-preprocessor" for image spaces. (#13522)
  • Example Scripts: Add coin game env + matrix social dilemma env + tests and examples (shoutout to Maxime Riché!). (#14208); Attention net (#14864); Serve + RLlib. (#14416); Env seed (#14471); Trajectory view API (enhancements and tf2 support). (#13786); Tune trial + checkpoint selection. (#14209)
  • DDPG: Add support for simplex action space. (#14011)
  • Others: on_learn_on_batch callback allows custom metrics. (#13584); Add TorchPolicy.export_model(). (#13989)

🔨 Fixes:

🏗 Architecture refactoring:

  • Remove all non-trajectory view API code. (#14860)
  • Obsolete UsageTrackingDict in favor of SampleBatch. (#13065)

Tune

🎉 New Features:

  • We added a new searcher HEBOSearcher (#14504, #14246, #13863, #14427)
  • Tune is now natively compatible with the Ray Client (#13778, #14115, #14280)
  • Tune now uses Ray’s Placement Groups underneath the hood. This will enable much faster autoscaling and training (for distributed trials) (#13906, #15011, #14313)

💫Enhancements:

  • Checkpointing improvements (#13376, #13767)
  • Optuna Search Algorithm improvements (#14731, #14387)
  • tune.with_parameters now works with Class API (#14532)

🔨Fixes:

SGD

  • Add fault tolerance during worker startup (#14724)

Serve

🎉 New Features:

  • Added metadata to default logger in backend replicas (#14251)
  • Added more metrics for ServeHandle stats (#13640)
  • Deprecated system-level batching in favor of @serve.batch (#14610, #14648)
  • Beta support for Serve with Ray client (#14163)
  • Use placement groups to bypass autoscaler throttling (#13844)
  • Deprecate client-based API in favor of process-wide singleton (#14696)
  • Add initial support for FastAPI ingress (#14754)

🔨 Fixes:

  • Fix ServeHandle serialization (#13695)

🏗 Architecture refactoring:

  • Refactor BackendState to support backend versioning and add more unit testing (#13870, #14658, #14740, #14748)
  • Optimize long polling to be per-key (#14335)

Dashboard

🎉 New Features:

  • Dashboard now supports being served behind a reverse proxy. (#14012)
  • Disk and network metrics are added to prometheus. (#14144)

💫Enhancements:

Thanks

Many thanks to all those who contributed to this release:
@geraint0923, @iycheng, @yurirocha15, @brian-yu, @harryge00, @ijrsvt, @wumuzi520, @suquark, @simon-mo, @clarkzinzow, @RaphaelCS, @FarzanT, @ob, @ashione, @ffbin, @robertnishihara, @SongGuyang, @zhe-thoughts, @rkooo567, @ezra-h, @acxz, @clay4444, @QuantumMecha, @jirkafajfr, @wuisawesome, @Qstar, @guykhazma, @devin-petersohn, @jeroenboeye, @ConeyLiu, @dependabot[bot], @fyrestone, @micahtyong, @javi-redondo, @Manuscrit, @mxz96102, @EscapeReality846089495, @WangTaoTheTonic, @stanislav-chekmenev, @architkulkarni, @Yard1, @tchordia, @zhisbug, @Bam4d, @niole, @yiranwang52, @thomasjpfan, @DmitriGekhtman, @gabrieleoliaro, @jparkerholder, @kfstorm, @andrew-rosenfeld-ts, @erikerlandson, @Crissman, @raulchen, @sumanthratna, @Catch-Bull, @chaokunyang, @krfricke, @raoul-khour-ts, @sven1977, @kathryn-zhou, @AmeerHajAli, @jovany-wang, @amogkam, @antoine-galataud, @tgaddair, @randxie, @ChaceAshcraft, @ericl, @cassidylaidlaw, @TanjaBayer, @lixin-wei, @lena-kashtelyan, @cathrinS, @qicosmos, @richardliaw, @rmsander, @jCrompton, @mjschock, @pdames, @barakmich, @michaelzhiluo, @stephanie-wang, @edoakes

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