Preprocessor

Base class for preprocessing layers.
A Preprocessor layer provides a complete preprocessing setup for a given task. It handles tokenization, audio/image conversion, and any other necessary preprocessing steps.
This class can be subclassed similar to any keras.layers.Layer, by defining build(), call() and get_config() methods. All subclasses should set the tokenizer or audio_converter or image_converter properties during construction as needed.
Instantiate a keras_hub.models.Preprocessor from a model preset.
A preset is a directory of configs, weights and other file assets used to save and load a pre-trained model. The preset can be passed as one of:
For any Preprocessor subclass, you can run cls.presets.keys() to list all built-in presets available on the class.
As there are usually multiple preprocessing classes for a given model, this method should be called on a specific subclass like keras_hub.models.BertTextClassifierPreprocessor.from_preset().
Save preprocessor to a preset directory.
The tokenizer used to tokenize strings.