Ray-2.33.0

Ray Libraries

Ray Core

💫 Enhancements:

• Add "last exception" to error message when GCS connection fails in ray.init() (#46516)

🔨 Fixes:

• Add object back to memory store when object recovery is skipped (#46460)
• Task status should start with PENDING_ARGS_AVAIL when retry (#46494)
• Fix ObjectFetchTimedOutError (#46562)
• Make working_dir support files created before 1980 (#46634)
• Allow full path in conda runtime env. (#45550)
• Fix worker launch time formatting in state api (#43516)

Ray Data

🎉 New Features:

• Deprecate Dataset.get_internal_block_refs() (#46455)
• Add read API for reading Databricks table with Delta Sharing (#46072)
• Add support for objects to Arrow blocks (#45272)

💫 Enhancements:

• Change offsets to int64 and change to LargeList for ArrowTensorArray (#45352)
• Prevent from_pandas from combining input blocks (#46363)
• Update Dataset.count() to avoid unnecessarily keeping BlockRefs in-memory (#46369)
• Use Set to fix inefficient iteration over Arrow table columns (#46541)
• Add AWS Error UNKNOWN to list of retried write errors (#46646)
• Always print traceback for internal exceptions (#46647)
• Allow unknown estimate of operator output bundles and ProgressBar totals (#46601)
• Improve filesystem retry coverage (#46685)

🔨 Fixes:

• Replace lambda mutable default arguments (#46493)

📖 Documentation:

• Auto-generate Dataset API documentation (#46557)
• Update outdated ExecutionPlan docstring (#46638)

Ray Train

💫 Enhancements:

• Update run status and actor status for train runs. (#46395)

🔨 Fixes:

• Replace lambda default arguments (#46576)

📖 Documentation:

• Add MNIST training using KubeRay doc page (#46123)
• Add example of pre-training Llama model on Intel Gaudi (#45459)
• Fix tensorflow example by using ScalingConfig (#46565)

Ray Tune

🔨 Fixes:

• Replace lambda default arguments (#46596)

Ray Serve

🎉 New Features:

• Fully deprecate target_num_ongoing_requests_per_replica and max_concurrent_queries, respectively replaced by max_ongoing_requests and target_ongoing_requests (#46392 and #46427)
• Configure the task launched by the controller to build an application with Serve’s logging config (#46347)

RLlib

💫 Enhancements:

• Moving sampling coordination for batch_mode=complete_episodes to synchronous_parallel_sample. (#46321)
• Enable complex action spaces with stateful modules. (#46468)

🏗 Architecture refactoring:

• Enable multi-learner setup for hybrid stack BC. (#46436)
• Introduce Checkpointable API for RLlib components and subcomponents. (#46376)

🔨 Fixes:

• Replace Mapping typehint with Dict: #46474

📖 Documentation:

• More example scripts for new API stack: Two separate optimizers (w/ different learning rates). (#46540) and custom loss function. (#46445)

Dashboard

🔨 Fixes:

• Task end time showing the incorrect time (#46439)
• Events Table rows having really bad spacing (#46701)
• UI bugs in the serve dashboard page (#46599)

Thanks

Many thanks to all those who contributed to this release!

@alanwguo, @hongchaodeng, @anyscalesam, @brucebismarck, @bt2513, @woshiyyya, @terraflops1048576, @lorenzoritter, @omrishiv, @davidxia, @cchen777, @nono-Sang, @jackhumphries, @aslonnie, @JoshKarpel, @zjregee, @bveeramani, @khluu, @Superskyyy, @liuxsh9, @jjyao, @ruisearch42, @sven1977, @harborn, @saihaj, @zcin, @can-anyscale, @veekaybee, @chungen04, @WeichenXu123, @GeneDer, @sergey-serebryakov, @Bye-legumes, @scottjlee, @rynewang, @kevin85421, @cristianjd, @peytondmurray, @MortalHappiness, @MaxVanDijck, @simonsays1980, @mjovanovic9999