tf.keras.layers.Rescaling
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Multiply inputs by scale
and adds offset
.
Inherits From: Layer
, Module
tf.keras.layers.Rescaling(
scale, offset=0.0, **kwargs
)
For instance:
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.
Output shape:
Same as input.
Args |
scale
|
Float, the scale to apply to the inputs.
|
offset
|
Float, the offset to apply to the inputs.
|
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Last updated 2021-08-16 UTC.
[null,null,["Last updated 2021-08-16 UTC."],[],[],null,["# tf.keras.layers.Rescaling\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/master/keras/layers/preprocessing/image_preprocessing.py#L316-L361) |\n\nMultiply inputs by `scale` and adds `offset`.\n\nInherits From: [`Layer`](../../../tf/keras/layers/Layer), [`Module`](../../../tf/Module)\n\n#### View aliases\n\n\n**Main aliases**\n\n[`tf.keras.layers.experimental.preprocessing.Rescaling`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Rescaling)\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.keras.layers.Rescaling`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Rescaling), [`tf.compat.v1.keras.layers.experimental.preprocessing.Rescaling`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/Rescaling)\n\n\u003cbr /\u003e\n\n tf.keras.layers.Rescaling(\n scale, offset=0.0, **kwargs\n )\n\n#### For instance:\n\n1. To rescale an input in the `[0, 255]` range\n to be in the `[0, 1]` range, you would pass `scale=1./255`.\n\n2. To rescale an input in the `[0, 255]` range to be in the `[-1, 1]` range,\n you would pass `scale=1./127.5, offset=-1`.\n\nThe rescaling is applied both during training and inference.\n\n#### Input shape:\n\nArbitrary.\n\n#### Output shape:\n\nSame as input.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|----------|-------------------------------------------|\n| `scale` | Float, the scale to apply to the inputs. |\n| `offset` | Float, the offset to apply to the inputs. |\n\n\u003cbr /\u003e"]]