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Bump ray[default,rllib] from 2.5.0 to 2.10.0 #74

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@dependabot dependabot bot commented on behalf of github Apr 1, 2024

Bumps ray[default,rllib] from 2.5.0 to 2.10.0.

Release notes

Sourced from ray[default,rllib]'s releases.

Ray-2.10.0

Release Highlights

Ray 2.10 release brings important stability improvements and enhancements to Ray Data, with Ray Data becoming generally available (GA).

  • [Data] Ray Data becomes generally available with stability improvements in streaming execution, reading and writing data, better tasks concurrency control, and debuggability improvement with dashboard, logging and metrics visualization.
  • [RLlib] “New API Stack” officially announced as alpha for PPO and SAC.
  • [Serve] Added a default autoscaling policy set via num_replicas=”auto” (#42613).
  • [Serve] Added support for active load shedding via max_queued_requests (#42950).
  • [Serve] Added replica queue length caching to the DeploymentHandle scheduler (#42943).
    • This should improve overhead in the Serve proxy and handles.
    • max_ongoing_requests (max_concurrent_queries) is also now strictly enforced (#42947).
    • If you see any issues, please report them on GitHub and you can disable this behavior by setting: RAY_SERVE_ENABLE_QUEUE_LENGTH_CACHE=0.
  • [Serve] Renamed the following parameters. Each of the old names will be supported for another release before removal.
    • max_concurrent_queries -> max_ongoing_requests
    • target_num_ongoing_requests_per_replica -> target_ongoing_requests
    • downscale_smoothing_factor -> downscaling_factor
    • upscale_smoothing_factor -> upscaling_factor
  • [Serve] WARNING: the following default values will change in Ray 2.11:
    • Default for max_ongoing_requests will change from 100 to 5.
    • Default for target_ongoing_requests will change from 1 to 2.
  • [Core] Autoscaler v2 is in alpha and can be tried out with Kuberay. It has improved observability and stability compared to v1.
  • [Train] Added support for accelerator types via ScalingConfig(accelerator_type).
  • [Train] Revamped the XGBoostTrainer and LightGBMTrainer to no longer depend on xgboost_ray and lightgbm_ray. A new, more flexible API will be released in a future release.
  • [Train/Tune] Refactored local staging directory to remove the need for local_dir and RAY_AIR_LOCAL_CACHE_DIR.

Ray Libraries

Ray Data

🎉 New Features:

  • Streaming execution stability improvement to avoid memory issue, including per-operator resource reservation, streaming generator output buffer management, and better runtime resource estimation (#43026, #43171, #43298, #43299, #42930, #42504)
  • Metadata read stability improvement to avoid AWS transient error, including retry on application-level exception, spread tasks across multiple nodes, and configure retry interval (#42044, #43216, #42922, #42759).
  • Allow tasks concurrency control for read, map, and write APIs (#42849, #43113, #43177, #42637)
  • Data dashboard and statistics improvement with more runtime metrics for each components (#43790, #43628, #43241, #43477, #43110, #43112)
  • Allow to specify application-level error to retry for actor task (#42492)
  • Add num_rows_per_file parameter to file-based writes (#42694)
  • Add DataIterator.materialize (#43210)
  • Skip schema call in DataIterator.to_tf if tf.TypeSpec is provided (#42917)
  • Add option to append for Dataset.write_bigquery (#42584)
  • Deprecate legacy components and classes (#43575, #43178, #43347, #43349, #43342, #43341, #42936, #43144, #43022, #43023)

💫 Enhancements:

  • Restructure stdout logging for better readability (#43360)
  • Add a more performant way to read large TFRecord datasets (#42277)
  • Modify ImageDatasource to use Image.BILINEAR as the default image resampling filter (#43484)
  • Reduce internal stack trace output by default (#43251)
  • Perform incremental writes to Parquet files (#43563)
  • Warn on excessive driver memory usage during shuffle ops (#42574)
  • Distributed reads for ray.data.from_huggingface (#42599)

... (truncated)

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Bumps [ray[default,rllib]](https://github.com/ray-project/ray) from 2.5.0 to 2.10.0.
- [Release notes](https://github.com/ray-project/ray/releases)
- [Commits](ray-project/ray@ray-2.5.0...ray-2.10.0)

---
updated-dependencies:
- dependency-name: ray[default,rllib]
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update Python code labels Apr 1, 2024
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dependabot bot commented on behalf of github May 1, 2024

Superseded by #78.

@dependabot dependabot bot closed this May 1, 2024
@dependabot dependabot bot deleted the dependabot/pip/ray-defaultrllib--2.10.0 branch May 1, 2024 17:25
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