layer_rescaling
Multiply inputs by scale and adds offset
Description
Multiply inputs by scale and adds offset
Usage
layer_rescaling(object, scale, offset = 0, ...) Arguments
| Arguments | Description |
|---|---|
| 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:
To rescale an input in the
[0, 255]range to be in the[0, 1]range, you would passscale=1./255.To rescale an input in the
[0, 255]range to be in the[-1, 1]range, you would passscale = 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()