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Ray-2.23.0

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@khluu khluu released this 22 May 23:37
· 1336 commits to master since this release
a0947ea

Ray Libraries

Ray Data

🎉 New Features:

  • Add support for using GPUs with map_groups (#45305)
  • Add support for using actors with map_groups (#45310)

💫 Enhancements:

  • Refine exception handling from arrow data conversion (#45294)

🔨 Fixes:

  • Fix Ray databricks UC reader with dynamic Databricks notebook scope token (#45153)
  • Fix bug where you can't return objects and array from UDF (#45287 )
  • Fix bug where map_groups triggers execution during input validation (#45314)

Ray Tune

🔨 Fixes:

  • [tune] Fix PB2 scheduler error resulting from trying to sort by Trial objects (#45161)

Ray Serve

🔨 Fixes:

  • Log application unhealthy errors at error level instead of warning level (#45211)

RLLib

💫 Enhancements:

  • Examples and tuned_examples learning test for new API stack are now “self-executable” (don’t require a third-party script anymore to run them). + WandB support. (#45023)

🔨 Fixes:

  • Fix result dict “spam” (duplicate, deprecated keys, e.g. “sampler_results” dumped into top level). (#45330)

📖 Documentation:

  • Add example for training with fractional GPUs on new API stack. (#45379)
  • Cleanup examples folder and remove deprecated sub directories. (#45327)

Ray Core

💫 Enhancements:

  • [Logs] Add runtime env started logs to job driver (#45255)
  • ray.util.collective support torch.bfloat16 (#39845)
  • [Core] Better propagate node death information (#45128)

🔨 Fixes:

  • [Core] Fix worker process leaks after job finishes (#44214)

Many thanks to all those who contributed to this release: @hongchaodeng, @khluu, @antoni-jamiolkowski, @ameroyer, @bveeramani, @can-anyscale, @WeichenXu123, @peytondmurray, @jackhumphries, @kevin85421, @jjyao, @robcaulk, @rynewang, @scottsun94, @swang, @GeneDer, @zcin, @ruisearch42, @aslonnie, @angelinalg, @raulchen, @ArthurBook, @sven1977, @wuxibin89