Multiply inputs by scale and adds offset

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.