training_config

Config classes for the graphnet.training module.

class graphnet.utilities.config.training_config.TrainingConfig(*, target, early_stopping_patience, fit, dataloader)[source]

Bases: BaseConfig

Configuration for all trainings.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

  • target (str | List[str])

  • early_stopping_patience (int)

  • fit (Dict[str, Any])

  • dataloader (Dict[str, Any])

target: Union[str, List[str]]
early_stopping_patience: int
fit: Dict[str, Any]
dataloader: Dict[str, Any]
model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].