commonpower.data_forecasting.nn_forecasting.eval_metrics.MeanAbsoluteError

class MeanAbsoluteError(*, name: str = 'mae')[source]

Mean Absolute Error (MAE) evaluation metric.

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.

Methods

`construct`
`copy`	Returns a copy of the model.
`dict`
`from_orm`
`json`
`model_construct`	Creates a new instance of the Model class with validated data.
`model_copy`	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#model_copy
`model_dump`	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump
`model_dump_json`	Usage docs: https://docs.pydantic.dev/2.10/concepts/serialization/#modelmodel_dump_json
`model_json_schema`	Generates a JSON schema for a model class.
`model_parametrized_name`	Compute the class name for parametrizations of generic classes.
`model_post_init`	Override this method to perform additional initialization after __init__ and model_construct.
`model_rebuild`	Try to rebuild the pydantic-core schema for the model.
`model_validate`	Validate a pydantic model instance.
`model_validate_json`	Usage docs: https://docs.pydantic.dev/2.10/concepts/json/#json-parsing
`model_validate_strings`	Validate the given object with string data against the Pydantic model.
`parse_file`
`parse_obj`
`parse_raw`
`schema`
`schema_json`
`update_forward_refs`
`validate`

Attributes

`model_computed_fields`
`model_config`	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
`model_extra`	Get extra fields set during validation.
`model_fields`
`model_fields_set`	Returns the set of fields that have been explicitly set on this model instance.
`name`

__call__(y_true: Tensor, y_pred: Tensor) → float[source]

Calculate the Mean Absolute Error (MAE).

Parameters:

Returns:

float – The MAE value.

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].