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NumericalFeature

NumericalFeature with dynamic kwargs passing and embedding support.

Constructor

__init__(self, name: str, feature_type: kdp.features.FeatureType = <FeatureType.FLOAT_NORMALIZED: 2>, preferred_distribution: kdp.layers.distribution_aware_encoder_layer.DistributionType | None = None, use_embedding: bool = False, embedding_dim: int | kdp.features._Unset = <unset>, num_bins: int | kdp.features._Unset = <unset>, **kwargs) -> None

Initializes a NumericalFeature instance.

Parameters- name (str): The name of the feature.

feature_type (FeatureType): The type of the feature.
preferred_distribution (DistributionType | None): The preferred distribution type.
use_embedding (bool): Whether to use advanced numerical embedding.
embedding_dim (int): Dimension of the embedding space.
num_bins (int): Number of bins for discretization.
**kwargs: Additional keyword arguments for the feature.

add_preprocessor

add_preprocessor(self, preprocessor: kdp.layers_factory.PreprocessorLayerFactory | typing.Any) -> None

Adds a preprocessor to the feature.

Parameters- preprocessor (Union[PreprocessorLayerFactory, Any]): The preprocessor to add.

from_string

from_string(type_str: str) -> 'FeatureType'

Converts a string to a FeatureType.

Parameters- type_str (str): The string representation of the feature type.

get_embedding_layer

get_embedding_layer(self, input_shape: tuple | None = None, defaults: dict | None = None) -> keras.src.layers.layer.Layer

Creates and returns a NumericalEmbedding layer configured for this feature.

Parameters- input_shape: Unused. NumericalEmbedding derives the feature count

    in its own `build`, so nothing here depends on the shape. The
    parameter is kept, and optional, so existing callers that pass
    it keep working.
  • defaults: Model-level embedding settings, used for every option this feature did not set itself. PreprocessingModel passes its embedding_dim, mlp_hidden_units, num_bins, init_min, init_max, dropout_rate and use_batch_norm here; without them those arguments had no effect at all.

Returns

A `NumericalEmbedding` layer built from this feature's settings.

update_kwargs

update_kwargs(self, **kwargs) -> None

Updates the kwargs with new or modified parameters.

Parameters

**kwargs: The new or modified parameters.