training_config

Config classes for the graphnet.training module.

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

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.

__init__ uses __pydantic_self__ instead of the more common self for the first arg 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].

model_fields: ClassVar[dict[str, FieldInfo]] = {'dataloader': FieldInfo(annotation=Dict[str, Any], required=True), 'early_stopping_patience': FieldInfo(annotation=int, required=True), 'fit': FieldInfo(annotation=Dict[str, Any], required=True), 'target': FieldInfo(annotation=Union[str, List[str]], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.