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API References

Ray API References

• Ray Datasets API
  • Creating Datasets
  • Dataset API
  • Block API
  • DatasetContext API
  • DatasetPipeline API
  • GroupedDataset API
  • Aggregate API
  • RandomAccessDataset API
  • Tensor Column Extension API
  • Custom Datasource API
  • Datasource Partitioning API
  • Built-in Datasources
  • Table Row API
  • Utility
• Ray Train API
  • Trainer
  • Backend Configurations
  • Callbacks
  • Checkpointing
  • Training Function Utilities
  • PyTorch Training Function Utilities
  • TensorFlow Training Function Utilities
• Ray Tune API
  • Execution (tune.run, tune.Experiment)
  • Training (tune.Trainable, tune.report)
  • Search Space API
  • Search Algorithms (tune.suggest)
  • Trial Schedulers (tune.schedulers)
  • Stopping mechanisms (tune.stopper)
  • Analysis (tune.analysis)
  • Console Output (Reporters)
  • Loggers (tune.logger)
  • Environment variables
  • Scikit-Learn API (tune.sklearn)
  • External library integrations (tune.integration)
  • Tune Internals
  • Tune Client API
  • Tune CLI (Experimental)
• Ray Serve API
  • Core APIs
  • Deployment API
  • ServeHandle API
  • Batching Requests
• Ray RLlib API
  • Environments
  • Trainer API
  • Policies
  • Model APIs
  • Evaluation and Environment Rollout
  • Offline RL
  • Distributed Execution API
  • RLlib Utilities
• AIR API
  • Components
• Ray Workflows API
  • Core API
  • Virtual Actors
  • Management API
• Ray Core API
  • Python API
  • Placement Group APIs
  • Custom Metrics APIs
  • Runtime Context APIs
  • Runtime Env APIs
  • Debugging APIs
  • The Ray Command Line API
• Ray Cluster Config YAML and CLI
  • Cluster YAML Configuration Options
  • Cluster Launcher Commands
  • Autoscaler SDK
• Ray Job Submission API
  • Job Submission CLI
  • Job Submission SDK
• Usage Stats Data API
  • UsageStatsToReport

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Usage Stats Collection

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Usage Stats Data API