# Ray 2.11.0 — Ray-2.11.0
- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2024-04-17
- Version: 2.11.0
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-2.11.0
- Permalink: https://whatsnew.fyi/product/ray/releases/2.11.0
What's New is an index, not a publisher: every entry below links to the vendor's own release notes, which are the authoritative source. Entries are labelled where they are hand-curated sample data, pre-releases, or drawn from a secondary source such as a developer blog.
Reuse: the summaries, labels and curation here are © What's New. Quote freely with attribution and a link back; wholesale republication of the corpus is not permitted — terms: https://whatsnew.fyi/terms. The vendors' own release notes remain their publishers'.
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- **added** — Support reading Avro files with ray.data.read_avro
- **added** — Add experimental support for AWS Trainium (Neuron)
- **added** — Add experimental support for Intel HPU
- **changed** — Pin ipywidgets==7.7.2 to enable Data progress bars in VSCode Web
- **changed** — Change log level for ignored exceptions
- **changed** — Change Parquet encoding ratio lower bound from 2 to 1
- **changed** — Add support for new style lightning import
- **fixed** — Fix throughput time calculations for metrics
- **fixed** — Fix nested ragged numpy.ndarray
- **fixed** — Fix Ray debugger incompatibility caused by trimmed error stack trace
- **fixed** — Fix ScalingConfig(accelerator_type) to request an appropriate resource amount
- **fixed** — Fix maximum recursion issue when serializing exceptions
- **fixed** — Remove base config deepcopy when initializing the trainer actor
- **fixed** — Dynamically-created applications will no longer be deleted when a config is PUT via the REST API
- **fixed** — Fix _to_object_ref memory leak
- **fixed** — Fix multi-GPU and multi-agent support on the new API stack
- **removed** — Remove deprecated BatchPredictor
- **removed** — Remove scikit-optimize search algorithm
- **removed** — Remove batch_queue_cls parameter from the @serve.batch decorator
- **deprecated** — Log a deprecation warning for local_dir and related environment variables
#### Release Highlights
- [data] Support reading Avro files with `ray.data.read_avro`
- [train] Added experimental support for AWS Trainium (Neuron) and Intel HPU.
#### Ray Libraries
##### Ray Data
🎉 New Features:
- Support reading Avro files with `ray.data.read_avro` (#43663)
💫 Enhancements:
- Pin `ipywidgets==7.7.2` to enable Data progress bars in VSCode Web (#44398)
- Change log level for ignored exceptions (#44408)
🔨 Fixes:
- Change Parquet encoding ratio lower bound from 2 to 1 (#44470)
- Fix throughput time calculations for metrics (#44138)
- Fix nested ragged `numpy.ndarray` (#44236)
- Fix Ray debugger incompatibility caused by trimmed error stack trace (#44496)
📖 Documentation:
- Update "Data Loading and Preprocessing" doc (#44165)
- Move imports into `TFPRedictor` in batch inference example (#44434)
##### Ray Train
🎉 New Features:
- Add experimental support for AWS Trainium (Neuron) (#39130)
- Add experimental support for Intel HPU (#43343)
💫 Enhancements:
- Log a deprecation warning for local_dir and related environment variables (#44029)
- Enforce xgboost>=1.7 for XGBoostTrainer usage (#44269)
🔨 Fixes:
- Fix ScalingConfig(accelerator_type) to request an appropriate resource amount (#44225)
- Fix maximum recursion issue when serializing exceptions (#43952)
- Remove base config deepcopy when initializing the trainer actor (#44611)
🏗 Architecture refactoring:
- Remove deprecated `BatchPredictor` (#43934)
##### Ray Tune
💫 Enhancements:
- Add support for new style lightning import (#44339)
- Log a deprecation warning for local_dir and related environment variables (#44029)
🏗 Architecture refactoring:
- Remove scikit-optimize search algorithm (#43969)
##### Ray Serve
🔨 Fixes:
- Dynamically-created applications will no longer be deleted when a config is PUT via the REST API ([#44476](https://github.com/ray-project/ray/pull/44476)).
- Fix `_to_object_ref` memory leak ([#43763](https://github.com/ray-project/ray/pull/43763))
- Log warning to reconfigure `max_ongoing_requests` if `max_batch_size` is less than `max_ongoing_requests` ([#43840](https://github.com/ray-project/ray/pull/43840))
- Deployment fails to start with `ModuleNotFoundError` in Ray 3.10 ([#44329](https://github.com/ray-project/ray/issues/44329))
- This was fixed by reverting the original core changes on the `sys.path` behavior. Revert "[core] If there's working_dir, don't set _py_driver_sys_path." ([#44435](https://github.com/ray-project/ray/pull/44435))
- The `batch_queue_cls` parameter is removed from the `@serve.batch` decorator ([#43935](https://github.com/ray-project/ray/pull/43935))
##### RLlib
🎉 New Features:
- New API stack: **DQN Rainbow** is now available for single-agent ([#43196](https://github.com/ray-project/ray/pull/43196), [#43198](https://github.com/ray-project/ray/pull/43198), [#43199](https://github.com/ray-project/ray/pull/43199))
- **`PrioritizedEpisodeReplayBuffer`** is available for **off-policy learning using the EnvRunner API** (`SingleAgentEnvRunner`) and supports random n-step sampling ([#42832](https://github.com/ray-project/ray/pull/42832), [#43258](https://github.com/ray-project/ray/pull/43258), [#43458](https://github.com/ray-project/ray/pull/43458), [#43496](https://github.com/ray-project/ray/pull/43496), [#44262](https://github.com/ray-project/ray/pull/44262))
💫 Enhancements:
- **Restructured `examples/` folder**; started moving example scripts to the new API stack ([#44559](https://github.com/ray-project/ray/pull/44559), [#44067](https://github.com/ray-project/ray/pull/44067), [#44603](https://github.com/ray-project/ray/pull/44603))
- **Evaluation do-over: Deprecate `enable_async_evaluation` option** (in favor of existing `evaluation_paralle
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