Update ray requirement from <2.0.0,>=0.8.7 to >=0.8.7,<3.0.0

[dependabot]

Updates the requirements on ray to permit the latest version.

Release notes

Sourced from ray's releases.

Ray-2.0.0

Release Highlights

Ray 2.0 is an exciting release with enhancements to all libraries in the Ray ecosystem. With this major release, we take strides towards our goal of making distributed computing scalable, unified, and open.

Towards these goals, Ray 2.0 features new capabilities for unifying the machine learning (ML) ecosystem, improving Ray's production support, and making it easier than ever for ML practitioners to use Ray's libraries.

Highlights:

• Ray AIR, a scalable and unified toolkit for ML applications, is now in Beta.
• ​​Ray now supports natively shuffling 100TB or more of data with the Ray Datasets library.
• KubeRay, a toolkit for running Ray on Kubernetes, is now in Beta. This replaces the legacy Python-based Ray operator.
• Ray Serve’s Deployment Graph API is a new and easier way to build, test, and deploy an inference graph of deployments. This is released as Beta in 2.0.

A migration guide for all the different libraries can be found here: Ray 2.0 Migration Guide.

Ray Libraries

Ray AIR

Ray AIR is now in beta. Ray AIR builds upon Ray’s libraries to enable end-to-end machine learning workflows and applications on Ray. You can install all dependencies needed for Ray AIR via pip install -u "ray[air]".

🎉 New Features:

• Predictors:
  • BatchPredictors now have support for scalable inference on GPUs.
  • All Predictors can now be constructed from pre-trained models, allowing you to easily scale batch inference with trained models from common ML frameworks.
  • ray.ml.predictors has been moved to the Ray Train namespace (ray.train).
• Preprocessing: New preprocessors and API changes on Ray Datasets now make feature processing easier to do on AIR. See the Ray Data release notes for more details.
• New features for Datasets/Train/Tune/Serve can be found in the corresponding library release notes for more details.

💫 Enhancements:

• Major package refactoring is included in this release.
  • ray.ml is renamed to ray.air.
  • ray.ml.preprocessors have been moved to ray.data.
    • train_test_split is now a new method of ray.data.Dataset (#27065)
  • ray.ml.trainers have been moved to ray.train (#25570)
  • ray.ml.predictors has been moved to ray.train.
  • ray.ml.config has been moved to ray.air.config (#25712).
  • Checkpoints are now framework-specific -- meaning that each Trainer generates its own Framework-specific Checkpoint class. See Ray Train for more details.
  • ModelWrappers have been renamed to PredictorDeployments.
• API stability annotations have been added (#25485)
• Train/Tune now have the same reporting and checkpointing API -- see the Train notes for more details (#26303)

... (truncated)

Commits

• cba26cc [Serve][Doc] Fix user guide tables (#27991) (#27994)
• d0f4cae Add RayService link (#27992)
• 19c30ee Fix linkcheck introduced by Ray Clusters doc changes (#27804)
• e6067ef fix placement group tests
• 0c02ff9 Cherry-pick all Serve doc changes for Ray 2.0 (#27960)
• aec51c3 [Serve][Java][Pick] Add Serve to Jar Building Process (#27977)
• c1e2abf [2.0.0] update version to 2.0.0 (#27972)
• 79ae3af [hotfix] Fix pytest dependency in test_utils (#27956)
• d3c231d [AIR][Docs] Set logging_strategy="epoch" for HF (#27917) (#27955)
• 5e4aad9 [requirements/docker] Update xgboost-ray and lightgbm-ray versions (#27943)
• Additional commits viewable in compare view

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[codecov]

Codecov Report

Merging #740 (4b29765) into master (402b8e6) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #740   +/-   ##
=======================================
  Coverage   82.45%   82.45%           
=======================================
  Files         107      107           
  Lines       12658    12658           
=======================================
  Hits        10437    10437           
  Misses       2221     2221           

Impacted Files	Coverage Δ
...i/explainers/anchors/anchor_tabular_distributed.py	27.18% <ø> (ø)

[ascillitoe]

Do not merge! CI tests involving ray have not been running due to an issue with the github action's yaml syntax (see #756 and SeldonIO/alibi-detect#615). We should rebase and run CI once #756 is merged.

[ascillitoe]

@dependabot rebase

[ascillitoe]

Fixes to types needed...

[ascillitoe]

LGTM!