Ray 2.37.0

2.37.0

Ray-2.37.0

Added 8
  • Allow control of some serve configuration via env vars
  • Add restart-failed-env option to EnvRunners
  • Add episode sampling to EpisodeReplayBuffer
  • Add SelfSupervisedLossAPI for RLModules that bring their own loss
  • Add InferenceOnlyAPI
  • Allow custom NCCL group for aDAG
  • Support buffered input for aDAG
  • Support multi node multi reader for aDAG
Changed 9
  • Simplify custom metadata provider API
  • Change counts of metrics to rates of metrics
  • Refactor custom optimizer rules
  • Update run status and add stack trace to TrainRunInfo
  • Faster detection of dead replicas
  • Store episodes in state form for offline RL
Fixed 4
  • Throw exception for non-streaming HF datasets with override_num_blocks argument
  • Remove ineffective retry code in plan_read_op
  • Fix incorrect pending task size if outputs are empty
  • Fix component id logging field

Ray Libraries

Ray Data

💫 Enhancements:

  • Simplify custom metadata provider API (#47575)
  • Change counts of metrics to rates of metrics (#47236)
  • Throw exception for non-streaming HF datasets with "override_num_blocks" argument (#47559)
  • Refactor custom optimizer rules (#47605)

🔨 Fixes:

  • Remove ineffective retry code in plan_read_op (#47456)
  • Fix incorrect pending task size if outputs are empty (#47604)
Ray Train

💫 Enhancements:

  • Update run status and add stack trace to TrainRunInfo (#46875)
Ray Serve

💫 Enhancements:

  • Allow control of some serve configuration via env vars (#47533)
  • [serve] Faster detection of dead replicas (#47237)

🔨 Fixes:

  • [Serve] fix component id logging field (#47609)
RLlib

💫 Enhancements:

  • New API stack:
    • Add restart-failed-env option to EnvRunners. (#47608)
    • Offline RL: Store episodes in state form. (#47294)
    • Offline RL: Replace GAE in MARWILOfflinePreLearner with GeneralAdvantageEstimation connector in learner pipeline. (#47532)
    • Off-policy algos: Add episode sampling to EpisodeReplayBuffer. (#47500)
    • RLModule APIs: Add SelfSupervisedLossAPI for RLModules that bring their own loss and InferenceOnlyAPI. (#47581, #47572)
Ray Core

💫 Enhancements:

  • [aDAG] Allow custom NCCL group for aDAG (#47141)
  • [aDAG] support buffered input (#47272)
  • [aDAG] Support multi node multi reader (#47480)
  • [Core] Make is_gpu, is_actor, root_detached_id fields late bind to workers. (#47212)
  • [Core] Reconstruct actor to run lineage reconstruction triggered actor task (#47396)
  • [Core] Optimize GetAllJobInfo API for performance (#47530)

🔨 Fixes:

  • [aDAG] Fix ranks ordering for custom NCCL group (#47594)
Ray Clusters

📖 Documentation:

  • [KubeRay] add a guide for deploying vLLM with RayService (#47038)

Thanks

Many thanks to all those who contributed to this release! @ruisearch42, @andrewsykim, @timkpaine, @rkooo567, @WeichenXu123, @GeneDer, @sword865, @simonsays1980, @angelinalg, @sven1977, @jjyao, @woshiyyya, @aslonnie, @zcin, @omatthew98, @rueian, @khluu, @justinvyu, @bveeramani, @nikitavemuri, @chris-ray-zhang, @liuxsh9, @xingyu-long, @peytondmurray, @rynewang

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