A preprocessing layer which rescales input values to a new range.
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.
A preprocessing layer which rescales input values to a new range.
This layer rescales every value of an input (often an image) by multiplying by
scaleand addingoffset.For instance:
[0, 255]range to be in the[0, 1]range, you would passscale=1/255.[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. Inputs can be of integer or floating point dtype, and by default the layer will output floats.Arguments:
scale: Float, the scale to apply to the inputs.offset: Float, the offset to apply to the inputs.Input shape: Arbitrary.
Output shape: Same as input.