mirror of
https://github.com/vale981/ray
synced 2025-03-12 14:16:39 -04:00
3293317c40
This PR Adds notes and example on logging for Ray/K8s. Implements an API Reference paging pointing to the configuration guide and the RayCluster CR definition. Takes managed K8s services out of the tabbed structure, to make that page look less sad. Adds a comparison of the KubeRay operator and legacy K8s operator Adds an architecture diagram for the autoscaling sections Fixes some other minor items Adds some info about networking to the configuration guide, removes the previously planned networking page Signed-off-by: Dmitri Gekhtman <dmitri.m.gekhtman@gmail.com>
360 lines
17 KiB
YAML
360 lines
17 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 AI Runtime
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chapters:
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- file: ray-air/getting-started
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title: "What is Ray AI Runtime (AIR)?"
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- file: ray-air/key-concepts
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- file: ray-air/user-guides
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sections:
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- file: ray-air/preprocessors
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- file: ray-air/trainer
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- file: ray-air/check-ingest
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- file: ray-air/tuner
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- file: ray-air/predictors
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- file: ray-air/examples/serving_guide
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- file: ray-air/deployment
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- file: ray-air/examples/index
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sections:
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- file: ray-air/examples/torch_image_example
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- file: ray-air/examples/convert_existing_pytorch_code_to_ray_air
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- file: ray-air/examples/tfx_tabular_train_to_serve
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- file: ray-air/examples/huggingface_text_classification
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- file: ray-air/examples/sklearn_example
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- file: ray-air/examples/xgboost_example
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- file: ray-air/examples/analyze_tuning_results
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- file: ray-air/examples/lightgbm_example
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- file: ray-air/examples/torch_incremental_learning
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- file: ray-air/examples/rl_serving_example
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- file: ray-air/examples/rl_online_example
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- file: ray-air/examples/rl_offline_example
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- file: ray-air/examples/upload_to_comet_ml
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- file: ray-air/examples/upload_to_wandb
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- file: ray-air/examples/feast_example
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- file: ray-air/package-ref
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- file: ray-air/benchmarks
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- caption: Ray Libraries
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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/getting-started
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- file: data/key-concepts
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- file: data/user-guide
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- file: data/examples/index
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sections:
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- file: data/examples/nyc_taxi_basic_processing
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title: Processing the NYC taxi dataset
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- file: data/examples/big_data_ingestion
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title: Large-scale ML Ingest
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- file: data/examples/ocr_example
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title: Scaling OCR with Ray Datasets
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- file: data/advanced-pipelines
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- file: data/random-access
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- file: data/faq
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- file: data/package-ref
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- file: data/integrations
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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/getting-started
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- file: train/key-concepts
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- file: train/user-guides
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sections:
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- file: train/config_guide
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- file: train/dl_guide
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- file: train/gbdt
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- file: train/architecture
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- file: train/faq
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- file: train/examples
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- file: train/api
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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/getting-started
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- file: tune/key-concepts
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- file: tune/tutorials/overview
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sections:
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- file: tune/tutorials/tune-lifecycle
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title: "How Tune Works"
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- file: tune/tutorials/tune-stopping
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title: "How to Stop and Resume"
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- file: tune/tutorials/tune-metrics
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title: "Using Callbacks and Metrics"
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- file: tune/tutorials/tune-distributed
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title: "Distributed Tuning"
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- file: tune/tutorials/tune-output
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title: "Logging Tune Runs"
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- file: tune/tutorials/tune-resources
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title: "Managing Resources"
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- file: tune/tutorials/tune-checkpoints
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title: "Working with Checkpoints"
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- file: tune/tutorials/tune-search-spaces
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title: "Using Search Spaces"
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- file: tune/tutorials/tune-advanced-tutorial
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title: "Understanding PBT"
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- file: tune/tutorials/tune-scalability
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title: "Scalability Benchmarks"
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- file: tune/examples/index
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sections:
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- file: tune/examples/tune-sklearn
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title: "Scikit-Learn Example"
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- file: tune/examples/tune_mnist_keras
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title: "Keras Example"
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- file: tune/examples/tune-pytorch-cifar
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title: "PyTorch Example"
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- file: tune/examples/tune-pytorch-lightning
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title: "PyTorch Lightning Example"
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- file: tune/examples/mxnet_example
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title: "MXNet Example"
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- file: tune/examples/tune-serve-integration-mnist
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title: "Ray Serve Example"
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- file: tune/examples/pbt_ppo_example
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title: "Ray RLlib Example"
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- file: tune/examples/tune-xgboost
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title: "XGBoost Example"
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- file: tune/examples/lightgbm_example
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title: "LightGBM Example"
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- file: tune/examples/horovod_simple
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title: "Horovod Example"
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- file: tune/examples/pbt_transformers
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title: "Huggingface Example"
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- file: tune/examples/tune-comet
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title: "Comet Example"
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- file: tune/examples/tune-wandb
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title: "Weights & Biases Example"
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- file: tune/examples/ax_example
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title: "Ax Example"
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- file: tune/examples/dragonfly_example
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title: "Dragonfly Example"
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- file: tune/examples/skopt_example
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title: "Skopt Example"
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- file: tune/examples/hyperopt_example
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title: "HyperOpt Example"
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- file: tune/examples/bayesopt_example
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title: "Bayesopt Example"
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- file: tune/examples/flaml_example
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title: "FLAML Example"
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- file: tune/examples/bohb_example
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title: "BOHB Example"
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- file: tune/examples/nevergrad_example
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title: "Nevergrad Example"
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- file: tune/examples/optuna_example
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title: "Optuna Example"
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- file: tune/examples/zoopt_example
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title: "ZOOpt Example"
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- file: tune/examples/sigopt_example
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title: "SigOpt Example"
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- file: tune/examples/hebo_example
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title: "HEBO Example"
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- file: tune/faq
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- file: tune/api_docs/overview.rst
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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/getting_started
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- file: serve/key-concepts
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- file: serve/user-guide
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sections:
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- file: serve/managing-deployments
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- file: serve/handling-dependencies
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- file: serve/http-guide
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- file: serve/http-adapters
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- file: serve/handle-guide
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- file: serve/ml-models
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- file: serve/deploying-serve
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- file: serve/monitoring
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- file: serve/performance
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- file: serve/autoscaling
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- file: serve/deployment-graph
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sections:
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- file: serve/deployment-graph/deployment-graph-e2e-tutorial
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- file: serve/deployment-graph/chain_nodes_same_class_different_args
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- file: serve/deployment-graph/combine_two_nodes_with_passing_input_parallel
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- file: serve/deployment-graph/control_flow_based_on_user_inputs
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- file: serve/deployment-graph/visualize_dag_during_development
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- file: serve/deployment-graph/http_endpoint_for_dag_graph
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- file: serve/production
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- file: serve/migration
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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: serve/package-ref
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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/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-algorithms
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- file: rllib/user-guides
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sections:
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- file: rllib/rllib-models
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- file: rllib/rllib-concepts
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- file: rllib/rllib-sample-collection
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- file: rllib/rllib-replay-buffers
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- file: rllib/rllib-offline
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- file: rllib/rllib-dev
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- file: rllib/rllib-examples
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- file: rllib/package_ref/index
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- file: ray-more-libs/index
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title: More Libraries
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sections:
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- file: ray-more-libs/joblib
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- file: ray-more-libs/lightgbm-ray
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- file: ray-more-libs/multiprocessing
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- file: ray-more-libs/ray-collective
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- file: ray-more-libs/ray-lightning
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- file: ray-core/examples/using-ray-with-pytorch-lightning
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- file: ray-more-libs/xgboost-ray
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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: 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/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: workflows/package-ref
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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/key-concepts
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title: "Key Concepts"
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- file: ray-core/user-guide
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title: "User Guides"
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- file: ray-core/examples/overview
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title: "Examples"
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sections:
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- file: ray-core/examples/plot_example-a3c
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- file: ray-core/examples/plot_example-lm
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- file: ray-core/examples/plot_hyperparameter
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- file: ray-core/examples/plot_parameter_server
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- file: ray-core/examples/plot_pong_example
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- file: ray-core/examples/highly_parallel
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- file: ray-core/package-ref
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- caption: Ray Clusters
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chapters:
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- file: cluster/index
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- file: cluster/quickstart
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- file: cluster/key-concepts
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- file: cluster/user-guide
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- file: cluster/cloud
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- file: cluster/deploy
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- file: cluster/api
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- file: cluster/usage-stats
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- file: cluster/cluster_under_construction
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title: Ray Clusters (under construction)
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sections:
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- file: cluster/cluster_under_construction/getting-started
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title: Getting Started
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- file: cluster/cluster_under_construction/key-concepts
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title: Key Concepts
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/index
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title: Ray Clusters on Kubernetes
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/getting-started
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides/k8s-cluster-setup.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides/config.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides/autoscaling.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides/logging.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides/gpu.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/user-guides/kuberay-vs-legacy.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/examples
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/examples/ml-example.md
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- file: cluster/cluster_under_construction/ray-clusters-on-kubernetes/references
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/index
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title: Ray Clusters on VMs
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/getting-started
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/index
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title: User Guides
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/installing-ray
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/launching-clusters/index
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title: Launching Clusters
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/launching-clusters/aws
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/launching-clusters/azure
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/launching-clusters/gcp
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/launching-clusters/add-your-own-cloud-provider
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/running-ray-cluster-on-prem
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/monitoring-and-observing-ray-cluster
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/large-cluster-best-practices
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/multi-tenancy-best-practices
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/configuring-autoscaling
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/community-supported-cluster-manager/index
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title: Community-supported Cluster Managers
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/community-supported-cluster-manager/yarn
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/community-supported-cluster-manager/slurm
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/community-supported-cluster-manager/lsf
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/running-jobs/index
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title: Running Jobs
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/running-jobs/job-submission-cli
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/running-jobs/job-submission-sdk
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/running-jobs/job-submission-rest
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/user-guides/running-jobs/ray-client
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/index
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title: Examples
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/learn-ray-cluster-basics/index
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/learn-ray-cluster-basics/launching-ray-cluster
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/learn-ray-cluster-basics/running-job-via-job-submission
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/learn-ray-cluster-basics/scale-your-job-with-autoscaling
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/learn-ray-cluster-basics/observe-your-app
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/learn-ray-cluster-basics/shutting-down-your-ray-cluster
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/setting-up-ray-cluster-for-development/index
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/setting-up-ray-cluster-for-development/todo
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/setting-up-ray-cluster-for-production/index
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/examples/setting-up-ray-cluster-for-production/todo
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/references/index
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sections:
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/references/job-submission-apis
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/references/ray-cluster-cli
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/references/ray-cluster-configuration
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- file: cluster/cluster_under_construction/ray-clusters-on-vms/references/autoscaler-sdk-api
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- caption: References
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chapters:
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- file: ray-references/api
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- caption: Developer Guides
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chapters:
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- file: ray-contribute/stability
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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/docs
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- file: ray-contribute/fake-autoscaler
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- file: ray-core/examples/testing-tips
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- file: ray-core/configure
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- file: ray-observability/index
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- file: ray-contribute/whitepaper
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