Working with preprocessing layers - Keras
keras.io › guides › preprocessing_layersJul 25, 2020 · tf.keras.layers.IntegerLookup: turns integer categorical values into an encoded representation that can be read by an Embedding layer or Dense layer. Image preprocessing. These layers are for standardizing the inputs of an image model. tf.keras.layers.Resizing: resizes a batch of images to a target size. tf.keras.layers.Rescaling: rescales and ...
tf.keras.layers.Rescaling | TensorFlow Core v2.7.0
www.tensorflow.org › tf › kerasDec 23, 2021 · 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. For an overview and full list of preprocessing layers, see ...
Rescaling layer - Keras
keras.io › api › layersA 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.