tf.keras.layers.Rescaling
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A preprocessing layer which rescales input values to a new range.
Inherits From: Layer, Module
tf.keras.layers.Rescaling(
scale, offset=0.0, **kwargs
)
This layer rescales every value of an input (often an image) by multiplying
by scale and adding offset.
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. Inputs can be
of integer or floating point dtype, and by default the layer will output
floats.
For an overview and full list of preprocessing layers, see the preprocessing
guide.
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 2023-10-06 UTC.
[null,null,["Last updated 2023-10-06 UTC."],[],[],null,["# tf.keras.layers.Rescaling\n\n\u003cbr /\u003e\n\n|---------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v2.10.0/keras/layers/preprocessing/image_preprocessing.py#L623-L680) |\n\nA preprocessing layer which rescales input values to a new range.\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\\`, \\`tf.compat.v1.keras.layers.experimental.preprocessing.Rescaling\\`\n\n\u003cbr /\u003e\n\n tf.keras.layers.Rescaling(\n scale, offset=0.0, **kwargs\n )\n\nThis layer rescales every value of an input (often an image) by multiplying\nby `scale` and adding `offset`.\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]`\n range, you would pass `scale=1./127.5, offset=-1`.\n\nThe rescaling is applied both during training and inference. Inputs can be\nof integer or floating point dtype, and by default the layer will output\nfloats.\n\nFor an overview and full list of preprocessing layers, see the preprocessing\n[guide](https://www.tensorflow.org/guide/keras/preprocessing_layers).\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Input shape ----------- ||\n|---|---|\n| Arbitrary. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Output shape ------------ ||\n|---|---|\n| Same as input. ||\n\n\u003cbr /\u003e\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"]]
View source on GitHub