Ray 0.8.5

0.8.5

Ray 0.8.5

Added 5
  • You can now cancel remote tasks using the ray.cancel API
  • Experimental support for recovering objects that were lost from the Ray distributed memory store by setting lineage_pinning_enabled: 1 in the internal config
  • New ZOOpt search algorithm added to Tune
  • Add delete_endpoint and delete_backend APIs to Serve
  • Added tutorials for serving models in Tensorflow/Keras, PyTorch, and Scikit-Learn in Serve
Changed 9
  • PyTorch support in RLlib has reached parity with TensorFlow
  • Improved callbacks API in RLlib
  • Enable Ray distributed reference counting in RLlib
  • Search algorithms in Tune are refactored to make them easier to extend
  • Use dictionary to update backend config in Serve
  • Made serve clusters tolerant to process failures
Fixed 3
  • TensorboardX errors are now handled safely in Tune
  • Bug fix in PBT checkpointing in Tune
  • Fix GPU Reservations in SLURM usage in SGD
Deprecated 1
  • max_concurrent argument in Tune search algorithms is deprecated
Highlight
Core
  • Task cancellation is now available for locally submitted tasks. (#7699)
  • Experimental support for recovering objects that were lost from the Ray distributed memory store. You can try this out by setting lineage_pinning_enabled: 1 in the internal config. (#7733)
RLlib
  • PyTorch support has now reached parity with TensorFlow. (#7926, #8188, #8120, #8101, #8106, #8104, #8082, #7953, #7984, #7836, #7597, #7797)
  • Improved callbacks API. (#6972)
  • Enable Ray distributed reference counting. (#8037)
  • Work towards customizable distributed training workflows. (#7958, #8077)
Tune
  • Documentation has improved with a new format. (#8083, #8201, #7716)
  • Search algorithms are refactored to make them easier to extend, deprecating max_concurrent argument. (#7037, #8258, #8285)
  • TensorboardX errors are now handled safely. (#8174)
  • Bug fix in PBT checkpointing. (#7794)
  • New ZOOpt search algorithm added. (#7960)
Serve
  • Improved APIs.
    • Add delete_endpoint and delete_backend. (#8252, #8256)
    • Use dictionary to update backend config. (#8202)
  • Added overview section to the documentation.
  • Added tutorials for serving models in Tensorflow/Keras, PyTorch, and Scikit-Learn.
  • Made serve clusters tolerant to process failures. (#8116, #8008,#7970,#7936)
SGD
  • New Semantic Segmentation and HuggingFace GLUE Fine-tuning Examples. (#7792, #7825)
  • Fix GPU Reservations in SLURM usage. (#8157)
  • Update learning rate scheduler stepping parameter. (#8107)
  • Make serialization of data creation optional. (#8027)
  • Automatic DDP wrapping is now optional. (#7875)
Others Projects
  • Progress towards the highly available and fault tolerant control plane. (#8144, #8119, #8145, #7909, #7949, #7771, #7557, #7675)
  • Progress towards the Ray streaming library. (#8044, #7827, #7955, #7961, #7348)
  • Autoscaler improvement. (#8178, #8168, #7986, #7844, #7717)
  • Progress towards Java support. (#8014)
  • Progress towards the Window compatibility. (#8237, #8186)
  • Progress towards cross language support. (#7711)
Thanks

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

@simon-mo, @robertnishihara, @BalaBalaYi, @ericl, @kfstorm, @tirkarthi, @nflu, @ffbin, @chaokunyang, @ijrsvt, @pcmoritz, @mehrdadn, @sven1977, @iamhatesz, @nmatthews-asapp, @mitchellstern, @edoakes, @anabranch, @billowkiller, @eisber, @ujvl, @allenyin55, @yncxcw, @deanwampler, @DavidMChan, @ConeyLiu, @micafan, @rkooo567, @datayjz, @wizardfishball, @sumanthratna, @ashione, @marload, @stephanie-wang, @richardliaw, @jovany-wang, @MissiontoMars, @aannadi, @fyrestone, @JarnoRFB, @wumuzi520, @roireshef, @acxz, @gramhagen, @Servon-Lee, @ClarkZinzow, @mfitton, @maximsmol, @janblumenkamp, @istoica

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