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schola.scripts.ray.settings.RLlibScriptArgs

class schola.scripts.ray.settings.RLlibScriptArgs(enable_checkpoints=False, checkpoint_dir=’./ckpt’, save_freq=100000, name_prefix_override=None, export_onnx=False, save_final_policy=False, launch_unreal=False, port=None, executable_path=None, headless=False, map=None, fps=None, disable_script=False, training_settings=, algorithm_settings=, logging_settings=, resume_settings=, network_architecture_settings=, resource_settings=, plugins=) : Bases: ScriptArgs

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.

Methods

__init__([enable_checkpoints, …])
make_unreal_connection()Create an Unreal Engine connection based on the script arguments.

Attributes

checkpoint_dirEnable saving checkpoints.
disable_scriptFlag indicating if the autolaunch script setting in the Unreal Engine Schola Plugin should be disabled.
enable_checkpointsEnable saving checkpoints
executable_pathPath to the standalone executable, when launching a standalone Environment
export_onnxWhether to export the model to ONNX format instead of just saving a checkpoint.
fpsFixed FPS to use when running standalone, if None no fixed timestep is used
headlessFlag indicating if the standalone Unreal Engine process should run in headless mode
launch_unrealFlag indicating if the script should launch a standalone Unreal Engine process
mapMap to load when launching a standalone Unreal Engine process
name_prefix_overrideOverride the name prefix for the checkpoint files (e.g. SAC, PPO, etc.).
portPort to connect to the Unreal Engine process, if None an open port will be automatically selected when running standalone.
save_final_policyWhether to save the final policy after training is complete.
save_freqFrequency with which to save checkpoints.
training_settings
algorithm_settings
logging_settings
resume_settings
network_architecture_settings
resource_settings
plugins

Parameters: : - enable_checkpoints (bool)

__init__(enable_checkpoints=False, checkpoint_dir=’./ckpt’, save_freq=100000, name_prefix_override=None, export_onnx=False, save_final_policy=False, launch_unreal=False, port=None, executable_path=None, headless=False, map=None, fps=None, disable_script=False, training_settings=, algorithm_settings=, logging_settings=, resume_settings=, network_architecture_settings=, resource_settings=, plugins=) : Parameters: : - enable_checkpoints (bool)

Return type: : None

algorithm_settings*: PPOSettings | APPOSettings | IMPALASettings*

logging_settings*: LoggingSettings*

network_architecture_settings*: NetworkArchitectureSettings*

plugins*: List[RLLibLauncherExtension]*

resource_settings*: ResourceSettings*

resume_settings*: ResumeSettings*

training_settings*: TrainingSettings*