layer_rescaling: Multiply inputs by 'scale' and adds 'offset'

In keras: R Interface to 'Keras'

Multiply inputs by scale and adds offset

Description

Multiply inputs by scale and adds offset

Usage

layer_rescaling(object, scale, offset = 0, ...)

Arguments

object	What to compose the new Layer instance with. Typically a Sequential model or a Tensor (e.g., as returned by layer_input()). The return value depends on object. If object is: missing or NULL, the Layer instance is returned. a Sequential model, the model with an additional layer is returned. a Tensor, the output tensor from layer_instance(object) is returned.
scale	Float, the scale to apply to the inputs.
offset	Float, the offset to apply to the inputs.
...	standard layer arguments.

Details

For instance:

1. To rescale an input in the ⁠[0, 255]⁠ range to be in the ⁠[0, 1]⁠ range, you would pass scale=1./255.

2. 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.

Input shape: Arbitrary.

Output shape: Same as input.

See Also

• https://www.tensorflow.org/api_docs/python/tf/keras/layers/Rescaling

• https://keras.io/api/layers/preprocessing_layers/image_preprocessing/rescaling

Other image preprocessing layers: layer_center_crop(), layer_resizing()

Other preprocessing layers: layer_category_encoding(), layer_center_crop(), layer_discretization(), layer_hashing(), layer_integer_lookup(), layer_normalization(), layer_random_brightness(), layer_random_contrast(), layer_random_crop(), layer_random_flip(), layer_random_height(), layer_random_rotation(), layer_random_translation(), layer_random_width(), layer_random_zoom(), layer_resizing(), layer_string_lookup(), layer_text_vectorization()

keras documentation built on May 29, 2024, 3:20 a.m.