ray-2.20.0
版本发布时间: 2024-05-02 05:58:22
ray-project/ray最新发布版本:ray-2.34.0(2024-08-01 02:02:13)
Ray Libraries
Ray Data
💫 Enhancements:
- Dedupe repeated schema during
ParquetDatasource
metadata prefetching (#44750) - Update
map_groups
implementation to better handle large outputs (#44862) - Deprecate
prefetch_batches
arg ofiter_rows
and change default value (#44982) - Adding in default behavior to false for creating dirs on s3 writes (#44972)
- Make internal UDF names more descriptive (#44985)
- Make
name
a required argument forAggregateFn
(#44880)
📖 Documentation:
- Add key concepts to and revise "Data Internals" page (#44751)
Ray Train
💫 Enhancements:
- Setup XGBoost
CommunicatorContext
automatically (#44883) - Track Train Run Info with
TrainStateActor
(#44585)
📖 Documentation:
- Add documentation for
accelerator_type
(#44882) - Update Ray Train example titles (#44369)
Ray Tune
💫 Enhancements:
- Remove trial table when running Ray Train in a Jupyter notebook (#44858)
- Clean up temporary checkpoint directories for class Trainables (ex: RLlib) (#44366)
📖 Documentation:
- Fix minor doc format issues (#44865)
- Remove outdated ScalingConfig references (#44918)
Ray Serve
💫 Enhancements:
- Handle push metric interval is now configurable with environment variable RAY_SERVE_HANDLE_METRIC_PUSH_INTERVAL_S (#32920)
- Improve performance of developer API serve.get_app_handle (#44812)
🔨 Fixes:
- Fix memory leak in handles for autoscaling deployments (the leak happens when
- RAY_SERVE_COLLECT_AUTOSCALING_METRICS_ON_HANDLE=1) (#44877)
RLlib
🎉 New Features:
- Introduce
MetricsLogger
, a unified API for users of RLlib to log custom metrics and stats in all of RLlib’s components (Algorithm, EnvRunners, and Learners). Rolled out for new API stack for Algorithm (training_step
) and EnvRunners (custom callbacks).Learner
(custom loss functions) support in progress. #44888, #44442 - Introduce “inference-only” (slim) mode for RLModules that run inside an EnvRunner (and thus don’t require value-functions or target networks): #44797
💫 Enhancements:
- MultiAgentEpisodeReplayBuffer for new API stack (preparation for multi-agent support of SAC and DQN): #44450
- AlgorithmConfig cleanup and renaming of properties and methods for better consistency/transparency: #44896
🔨 Fixes:
Ray Core and Ray Clusters
💫 Enhancements:
- Report GCS internal pubsub buffer metrics and cap message size (#44749)
🔨 Fixes:
- Fix task submission never return when network partition happens (#44692)
- Fix incorrect use of ssh port forward option. (#44973)
- Make sure dashboard will exit if grpc server fails (#44928)
- Make sure dashboard agent will exit if grpc server fails (#44899)
Thanks @can-anyscale, @hongchaodeng, @zcin, @marwan116, @khluu, @bewestphal, @scottjlee, @andrewsykim, @anyscalesam, @MortalHappiness, @justinvyu, @JoshKarpel, @woshiyyya, @rynewang, @Abirdcfly, @omatthew98, @sven1977, @marcelocarmona, @rueian, @mattip, @angelinalg, @aslonnie, @matthewdeng, @abizjakpro, @simonsays1980, @jjyao, @terraflops1048576, @hongpeng-guo, @stephanie-wang, @bw-matthew, @bveeramani, @ruisearch42, @kevin85421, @Tongruizhe
Many thanks to all those who contributed to this release!