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f9b71a8bf6
This PR consolidates both #21667 and #21759 (look there for features), but improves on them in the following way: - [x] we reverted renaming of existing projects `tune`, `rllib`, `train`, `cluster`, `serve`, `raysgd` and `data` so that links won't break. I think my consolidation efforts with the `ray-` prefix were a little overeager in that regard. It's better like this. Only the creation of `ray-core` was a necessity, and some files moved into the `rllib` folder, so that should be relatively benign. - [x] Additionally, we added Algolia `docsearch`, screenshot below. This is _much_ better than our current search. Caveat: there's a sphinx dependency that needs to be replaced (`sphinx-tabs`) by another, newer one (`sphinx-panels`), as the former prevents loading of the `algolia.js` library. Will follow-up in the next PR (hoping this one doesn't get re-re-re-re-reverted).
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6 KiB
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172 lines
No EOL
6 KiB
YAML
format: jb-book
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root: index
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parts:
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- caption: Overview
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chapters:
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- file: ray-overview/index
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- file: ray-overview/installation
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- file: ray-overview/ray-libraries
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- caption: Ray ML
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chapters:
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- file: data/dataset
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title: Ray Data
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sections:
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- file: data/dataset-pipeline
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- file: data/dataset-ml-preprocessing
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- file: data/dataset-execution-model
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- file: data/dataset-tensor-support
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- file: data/examples/big_data_ingestion
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- file: data/dask-on-ray
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- file: data/mars-on-ray
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- file: data/modin/index
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- file: data/raydp
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- file: train/train
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title: Ray Train
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sections:
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- file: train/user_guide
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- file: train/examples
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- file: train/architecture
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- file: train/migration-guide
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- file: raysgd/raysgd
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title: "RaySGD v1: Distributed Training Wrappers"
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- file: tune/index
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title: Ray Tune
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sections:
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- file: tune/key-concepts
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- file: tune/user-guide
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- file: tune/tutorials/overview
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sections:
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- file: tune/tutorials/tune-tutorial.rst
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- file: tune/tutorials/tune-advanced-tutorial.rst
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- file: tune/tutorials/tune-distributed.rst
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- file: tune/tutorials/tune-lifecycle.rst
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- file: tune/tutorials/tune-mlflow.rst
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- file: tune/tutorials/tune-pytorch-cifar.rst
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- file: tune/tutorials/tune-pytorch-lightning.rst
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- file: tune/tutorials/tune-serve-integration-mnist.rst
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- file: tune/tutorials/tune-sklearn.rst
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- file: tune/tutorials/tune-xgboost.rst
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- file: tune/tutorials/tune-wandb.rst
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- file: tune/examples/index
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- file: tune/contrib
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- file: serve/index
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title: Ray Serve
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sections:
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- file: serve/tutorial
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- file: serve/core-apis
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- file: serve/http-servehandle
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- file: serve/deployment
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- file: serve/ml-models
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- file: serve/pipeline
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- file: serve/performance
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- file: serve/architecture
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- file: serve/tutorials/index
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- file: serve/faq
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- file: rllib/index
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title: Ray RLlib
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sections:
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- file: rllib/rllib-toc
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- file: rllib/core-concepts
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- file: rllib/rllib-training
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- file: rllib/rllib-env
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- file: rllib/rllib-models
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- file: rllib/rllib-algorithms
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- file: rllib/rllib-sample-collection
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- file: rllib/rllib-offline
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- file: rllib/rllib-concepts
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- file: rllib/rllib-examples
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- file: rllib/rllib-dev
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- file: workflows/concepts
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title: Ray Workflows
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sections:
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- file: workflows/basics
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- file: workflows/management
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- file: workflows/actors
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- file: workflows/metadata
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- file: workflows/events
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- file: workflows/comparison
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- file: workflows/advanced
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- file: ray-more-libs/index
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title: More Ray ML Libraries
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- caption: Ray Core
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chapters:
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- file: ray-core/walkthrough
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title: Getting Started
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- file: ray-core/using-ray
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title: "User Guide"
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sections:
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- file: ray-core/starting-ray
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- file: ray-core/actors
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- file: ray-core/namespaces
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- file: ray-core/handling-dependencies
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- file: ray-core/async_api
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- file: ray-core/concurrency_group_api
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- file: ray-core/using-ray-with-gpus
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- file: ray-core/serialization
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- file: ray-core/memory-management
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- file: ray-core/placement-group
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- file: ray-core/troubleshooting
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- file: ray-core/fault-tolerance
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- file: ray-core/advanced
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- file: ray-core/cross-language
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- file: ray-core/using-ray-with-tensorflow
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- file: ray-core/using-ray-with-pytorch
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- file: ray-core/using-ray-with-jupyter
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- file: ray-core/examples/overview
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title: "Tutorials and Examples"
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sections:
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- file: ray-core/examples/tips-for-first-time
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- file: ray-core/examples/testing-tips
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- file: ray-core/examples/progress_bar
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- file: ray-core/examples/plot_streaming
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- file: ray-core/examples/placement-group
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- file: ray-core/examples/plot_parameter_server
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- file: ray-core/examples/plot_hyperparameter
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- file: ray-core/examples/plot_lbfgs
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- file: ray-core/examples/plot_example-lm
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- file: ray-core/examples/plot_newsreader
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- file: ray-core/examples/dask_xgboost/dask_xgboost
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- file: ray-core/examples/modin_xgboost/modin_xgboost
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- file: ray-core/examples/plot_pong_example
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- file: ray-core/examples/plot_example-a3c
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- file: ray-core/examples/using-ray-with-pytorch-lightning
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- caption: Deploying Ray Clusters
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chapters:
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- file: cluster/quickstart
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- file: cluster/user-guide
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sections:
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- file: cluster/index
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- file: cluster/guide
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- file: cluster/job-submission
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title: "Submitting Ray Jobs"
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- file: cluster/ray-client
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- file: cluster/cloud
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sections:
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- file: cluster/aws-tips
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- file: cluster/deploy
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sections:
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- file: cluster/kubernetes
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- file: cluster/yarn
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- file: cluster/slurm
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- file: cluster/lsf
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- caption: References
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chapters:
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- file: ray-references/api
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- file: ray-references/faq
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- caption: Developer Guide
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chapters:
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- file: ray-contribute/getting-involved
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sections:
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- file: ray-contribute/development
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- file: ray-contribute/fake-autoscaler
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- file: ray-core/configure
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- file: ray-observability/index
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- file: ray-design-patterns/index
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- file: ray-contribute/whitepaper
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# TODO: Add examples section |