# Ray 2.36.0 — Ray-2.36.0
- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2024-09-17
- Version: 2.36.0
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-2.36.0
- Permalink: https://whatsnew.fyi/product/ray/releases/2.36.0
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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- **changed** — Remove limit on number of tasks launched per scheduling step in Ray Data
- **added** — Allow user-defined Exception to be caught in Ray Data
- **fixed** — Display pending actors separately in the progress bar and not count them towards running resources
- **fixed** — Fix bug where arrow_parquet_args aren't used
- **fixed** — Skip empty JSON files in read_json()
- **fixed** — Remove remote call for initializing Datasource in read_datasource()
- **added** — Decouple device-related modules and add Huawei NPU support to Ray Train
- **fixed** — Update TORCH_NCCL_ASYNC_ERROR_HANDLING env var
- **changed** — Mark proxy as unready when its routers are aware of zero replicas in Ray Serve
- **added** — Setup default serve logger
- **fixed** — Allow get_serve_logs_dir to run outside of Ray's context
- **removed** — Remove support for nested DeploymentResponses
- **added** — Add CQL algorithm to new API stack in RLlib
- **added** — Enable GPU and multi-GPU support for DQN/SAC/CQL in new API stack
- **changed** — Enhance offline RL in new API stack
- **fixed** — Fix large batch size for synchronous algos after EnvRunner failures
- **added** — Add torch.compile config options to old API stack
- **added** — Add kwargs to torch.nn.parallel.DistributedDataParallel
- **added** — Add PREPARED state for placement groups in GCS for better fault tolerance
- **fixed** — Fix ray_unintentional_worker_failures_total to only count unintentional worker failures
#### Ray Libraries
##### Ray Data
💫 Enhancements:
- Remove limit on number of tasks launched per scheduling step (#47393)
- Allow user-defined Exception to be caught. (#47339)
🔨 Fixes:
- Display pending actors separately in the progress bar and not count them towards running resources (#46384)
- Fix bug where `arrow_parquet_args` aren't used (#47161)
- Skip empty JSON files in `read_json()` (#47378)
- Remove remote call for initializing `Datasource` in `read_datasource()` (#47467)
- Remove dead `from_*_operator` modules (#47457)
- Release test fixes
- Add `AWS ACCESS_DENIED` as retryable exception for multi-node Data+Train benchmarks (#47232)
- Get AWS credentials with boto (#47352)
- Use worker node instead of head node for `read_images_comparison_microbenchmark_single_node` release test (#47228)
📖 Documentation:
- Add docstring to explain `Dataset.deserialize_lineage` (#47203)
- Add a comment explaining the bundling behavior for `map_batches` with default batch_size (#47433)
##### Ray Train
💫 Enhancements:
- Decouple device-related modules and add Huawei NPU support to Ray Train (#44086)
🔨 Fixes:
- Update TORCH_NCCL_ASYNC_ERROR_HANDLING env var (#47292)
📖 Documentation:
- Add missing Train public API reference (#47134)
##### Ray Tune
📖 Documentation:
- Add missing Tune public API references (#47138)
##### Ray Serve
💫 Enhancements:
- Mark proxy as unready when its routers are aware of zero replicas (#47002)
- Setup default serve logger (#47229)
🔨 Fixes:
- Allow get_serve_logs_dir to run outside of Ray's context (#47224)
- Use serve logger name for logs in serve (#47205)
📖 Documentation:
- [HPU] [Serve] [experimental] Add vllm HPU support in vllm example (#45893)
🏗 Architecture refactoring:
- Remove support for nested DeploymentResponses (#47209)
##### RLlib
🎉 New Features:
- New API stack: Add CQL algorithm. ([#47000](https://github.com/ray-project/ray/pull/47000), [#47402](https://github.com/ray-project/ray/pull/47402))
- New API stack: Enable GPU and multi-GPU support for DQN/SAC/CQL. ([#47179](https://github.com/ray-project/ray/pull/47179))
💫 Enhancements:
- New API stack: Offline RL enhancements: [#47195](https://github.com/ray-project/ray/pull/47195), [#47359](https://github.com/ray-project/ray/pull/47359)
- Enhance new API stack stability: [#46324](https://github.com/ray-project/ray/pull/46324), [#47196](https://github.com/ray-project/ray/pull/47196), [#47245](https://github.com/ray-project/ray/pull/47245), [#47279](https://github.com/ray-project/ray/pull/47279)
- Fix large batch size for synchronous algos (e.g. PPO) after EnvRunner failures. ([#47356](https://github.com/ray-project/ray/pull/47356))
- Add torch.compile config options to old API stack. ([#47340](https://github.com/ray-project/ray/pull/47340)[)](https://github.com/ray-project/ray/commit/78402bc1fde669cb4015f9393106acb144ac45bf)
- Add kwargs to torch.nn.parallel.DistributedDataParallel ([#47276](https://github.com/ray-project/ray/pull/47276))
- Enhanced CI stability: [#47197](https://github.com/ray-project/ray/pull/47197), [#47249](https://github.com/ray-project/ray/pull/47249)
📖 Documentation:
- New API stack example scripts:
- Float16 training example script. ([#47362](https://github.com/ray-project/ray/pull/47362))
- Mixed precision training example script ([#47116](https://github.com/ray-project/ray/pull/47116))
- ModelV2 -> RLModule wrapper for migrating to new API stack. ([#47425](https://github.com/ray-project/ray/pull/47425))
- Remove "new API stack experimental" hint from docs. ([#47301](https://github.com/ray-project/ray/pull/47301))
🏗 Architecture refactoring:
- Remove 2nd Learner ConnectorV2 pass from PPO ([#47401](https://github.com/ray-project/ray/pull/47401))
- Add separate learning rates for policy a
_[Truncated at 4000 characters — full notes: https://github.com/ray-project/ray/releases/tag/ray-2.36.0]_