🏭 Preprocessing Layers Factory

The PreprocessorLayerFactory class provides a convenient way to create and manage preprocessing layers for your machine learning models. It supports both standard Keras preprocessing layers and custom layers defined within the KDP framework.

🎡 Using Keras Preprocessing Layers

All preprocessing layers available in Keras can be used within the PreprocessorLayerFactory. You can access these layers by their class names. Here's an example of how to use a Keras preprocessing layer:

normalization_layer = PreprocessorLayerFactory.create_layer(
    "Normalization",
    axis=-1,
    mean=None,
    variance=None
)

Available layers:

• Normalization
• Discretization
• CategoryEncoding
• Hashing
• HashedCrossing
• StringLookup
• IntegerLookup
• TextVectorization
• ... and more

🏗️ Custom KDP Preprocessing Layers

In addition to Keras layers, the PreprocessorLayerFactory includes several custom layers specific to the KDP framework. Here's a list of available custom layers:

cast_to_float32_layer(name='cast_to_float32', **kwargs) staticmethod

Create a CastToFloat32Layer layer.

Parameters:

Name	Type	Description	Default
name	str	The name of the layer.	'cast_to_float32'
**kwargs	dict	Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the CastToFloat32Layer layer.

create_layer(layer_class, name=None, **kwargs) staticmethod

Create a layer using the layer class name, automatically filtering kwargs based on the layer class.

Parameters:

Name	Type	Description	Default
layer_class	str | Class Object	The name of the layer class to be created (e.g., 'Normalization', 'Rescaling') or the class object itself.	required
name	str	The name of the layer. Optional.	None
**kwargs		Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the specified layer class.

date_encoding_layer(name='date_encoding_layer', **kwargs) staticmethod

Create a DateEncodingLayer layer.

Parameters:

Name	Type	Description	Default
name	str	The name of the layer.	'date_encoding_layer'
**kwargs	dict	Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the DateEncodingLayer layer.

date_parsing_layer(name='date_parsing_layer', **kwargs) staticmethod

Create a DateParsingLayer layer.

Parameters:

Name	Type	Description	Default
name	str	The name of the layer.	'date_parsing_layer'
**kwargs	dict	Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the DateParsingLayer layer.

date_season_layer(name='date_season_layer', **kwargs) staticmethod

Create a SeasonLayer layer.

Parameters:

Name	Type	Description	Default
name	str	The name of the layer.	'date_season_layer'
**kwargs	dict	Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the SeasonLayer layer.

text_preprocessing_layer(name='text_preprocessing', **kwargs) staticmethod

Create a TextPreprocessingLayer layer.

Parameters:

Name	Type	Description	Default
name	str	The name of the layer.	'text_preprocessing'
**kwargs	dict	Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the TextPreprocessingLayer layer.

transformer_block_layer(name='transformer', **kwargs) staticmethod

Create a TransformerBlock layer.

Parameters:

Name	Type	Description	Default
name	str	The name of the layer.	'transformer'
**kwargs	dict	Additional keyword arguments to pass to the layer constructor.	{}

Returns:

Type	Description
Layer	An instance of the TransformerBlock layer.