Multiply inputs by scale
and adds offset
.
Inherits From: PreprocessingLayer
, Layer
, Module
tf.keras.layers.experimental.preprocessing.Rescaling( scale, offset=0.0, name=None, **kwargs )
To rescale an input in the [0, 255]
range to be in the [0, 1]
range, you would pass scale=1./255
.
To rescale an input in the [0, 255]
range to be in the [-1, 1]
range, you would pass scale=1./127.5, offset=-1
.
The rescaling is applied both during training and inference.
Arbitrary.
Same as input.
Arguments | |
---|---|
scale | Float, the scale to apply to the inputs. |
offset | Float, the offset to apply to the inputs. |
name | A string, the name of the layer. |
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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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/keras/layers/experimental/preprocessing/Rescaling