Skip to content

RllibScriptSettings

Full path: schola.scripts.rllib.train.settings.RllibScriptSettings

Top level dataclass for RLlib script arguments. This class aggregates all the settings required for configuring the RLlib training process. It includes settings for training, algorithms, logging, resuming from checkpoints, network architecture, and resource allocation. This allows for a comprehensive configuration of the RLlib training job in a structured manner.

RllibScriptSettings(training_settings = <factory>,
                    algorithm_settings = <factory>,
                    logging_settings = <factory>, resume_settings = <factory>,
                    network_architecture_settings = <factory>,
                    resource_settings = <factory>,
                    checkpoint_settings = <factory>,
                    environment_settings = <factory>)

Parameters

  • training_settings (Annotated)

  • algorithm_settings (Annotated)

  • logging_settings (Annotated)

  • resume_settings (Annotated)

  • network_architecture_settings (Annotated)

  • resource_settings (Annotated)

  • checkpoint_settings (Annotated)

  • environment_settings (Annotated)

Methods

init

__init__(training_settings = <factory>, algorithm_settings = <factory>,
         logging_settings = <factory>, resume_settings = <factory>,
         network_architecture_settings = <factory>,
         resource_settings = <factory>, checkpoint_settings = <factory>,
         environment_settings = <factory>)

Parameters

  • training_settings (Annotated)

  • algorithm_settings (Annotated)

  • logging_settings (Annotated)

  • resume_settings (Annotated)

  • network_architecture_settings (Annotated)

  • resource_settings (Annotated)

  • checkpoint_settings (Annotated)

  • environment_settings (Annotated)

Attributes

algorithm_settings

algorithm_settings

Settings for configuring the training algorithm to use.

checkpoint_settings

checkpoint_settings

Settings for checkpoints

environment_settings

environment_settings

Settings for the environment to use during training

logging_settings

logging_settings

Settings for enabling logging and configuring the logging directory.

network_architecture_settings

network_architecture_settings

Settings for configuring the neural network architecture used for training.

resource_settings

resource_settings

Settings for configuring the resource allocation for the training process.

resume_settings

resume_settings

Settings for resuming training from a checkpoint.

training_settings

training_settings

Settings for configuring the training process.