# Ray 0.8.4 — Ray 0.8.4

- Product: Ray (https://whatsnew.fyi/product/ray)
- Vendor: Anyscale
- Date: 2020-04-02
- Version: 0.8.4
- Original notes: https://github.com/ray-project/ray/releases/tag/ray-0.8.4
- Permalink: https://whatsnew.fyi/product/ray/releases/0.8.4

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** — Add Python 3.8 support
- **fixed** — Fix asyncio actor deserialization
- **fixed** — Fix importing Pyarrow lead to symbol collision segfault
- **changed** — ray memory will collect statistics from all nodes
- **changed** — Pin lineage of plasma objects that are still in scope
- **added** — Add contextual bandit algorithms
- **added** — Add parameter noise exploration API
- **changed** — Enable restore keras model from h5 file
- **changed** — Store tf-graph by default when doing Policy.export_model()
- **fixed** — Fix default policy overrides torch policy
- **changed** — Add new API for tuning TorchTrainer using Tune
- **changed** — Convert the head worker to a local model
- **added** — Add new API for save/restore
- **added** — Add tqdm support to TorchTrainer
- **added** — Add sorted columns and TensorBoard to Tune tab
- **added** — Tune experiments can now be cancelled via the REST client
- **added** — Add fail_fast to enable experiments to fail quickly
- **changed** — Override the IP retrieval process if needed
- **added** — Add async methods support for serve actors
- **added** — Add multiple method support for serve actors with HTTP methods specification and method execution through X-SERVE-CALL-METHOD header or RayServeHandle options

Highlight
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- Add Python 3.8 support. (#7754)

Core
----
- Fix asycnio actor deserialization. (#7806)
- Fix importing Pyarrow lead to symbol collison segfault. (#7568)
- `ray memory` will collect statistics from all nodes. (#7721)
- Pin lineage of plasma objects that are still in scope. (#7690)

RLlib
-----
- Add contextual bandit algorithms. (#7642)
- Add parameter noise exploration API. (#7772)
- Add [scaling guide](https://ray.readthedocs.io/en/latest/rllib-training.html#scaling-guide). (#7780)
- Enable restore keras model from h5 file. (#7482)
- Store tf-graph by default when doing `Policy.export_model()`. (#7759)
- Fix default policy overrides torch policy. (#7756, #7769)

RaySGD
----
- BREAKING: Add new API for tuning TorchTrainer using Tune. (#7547)
- BREAKING: Convert the head worker to a local model. (#7746)
- Added a new API for save/restore.  (#7547)
- Add tqdm support to TorchTrainer. (#7588)

Tune
------
- Add sorted columns and TensorBoard to Tune tab. (#7140)
- Tune experiments can now be cancelled via the REST client. (#7719)
- `fail_fast` enables experiments to fail quickly. (#7528)
- override the IP retrieval process if needed. (#7705) 
- TensorBoardX nested dictionary support. (#7705) 

Serve
-----
- Performance improvements:
	- Push route table updates to HTTP proxy. (#7774)
	- Improve serialization. (#7688)
- Add async methods support for serve actors. (#7682)
- Add multiple method support for serve actors. (#7709)
	- You can specify HTTP methods in `serve.create_backend(..., methods=["GET", "POST"])`.
	- The ability to specify which actor method to execute in HTTP through `X-SERVE-CALL-METHOD` header or in `RayServeHandle` through `handle.options("method").remote(...)`.

Others
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- Progress towards highly available control plane. (#7822, #7742)
- Progress towards Windows compatibility. (#7740, #7739, #7657)
- Progress towards Ray Streaming library. (#7813)
- Progress towards metrics export service. (#7809)
- Basic C++ worker implementation. (#6125)


Thanks
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We thank the following contributors for their work on this release:

@carlbalmer, @BalaBalaYi, @saurabh3949, @maximsmol, @SongGuyang, @istoica, @pcmoritz, @aannadi, @kfstorm, @ijrsvt, @richardliaw, @mehrdadn, @wumuzi520, @cloudhan, @edoakes, @mitchellstern, @robertnishihara, @hhoke, @simon-mo, @ConeyLiu, @stephanie-wang, @rkooo567, @ffbin, @ericl, @hubcity, @sven1977