Base class for PreprocessingLayers.
tf.keras.layers.experimental.preprocessing.PreprocessingLayer( trainable=True, name=None, dtype=None, dynamic=False, **kwargs )
adapt
adapt( data, reset_state=True )
Fits the state of the preprocessing layer to the data being passed.
Arguments | |
---|---|
data | The data to train on. It can be passed either as a tf.data Dataset, or as a numpy array. |
reset_state | Optional argument specifying whether to clear the state of the layer at the start of the call to adapt , or whether to start from the existing state. This argument may not be relevant to all preprocessing layers: a subclass of PreprocessingLayer may choose to throw if 'reset_state' is set to False. |
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Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/layers/experimental/preprocessing/PreprocessingLayer