tf.keras.layers.Normalization

Feature-wise normalization of the data.

Inherits From: PreprocessingLayer, Layer, Module

This layer will coerce its inputs into a distribution centered around 0 with standard deviation 1. It accomplishes this by precomputing the mean and variance of the data, and calling (input - mean) / sqrt(var) at runtime.

What happens in adapt(): Compute mean and variance of the data and store them as the layer's weights. adapt() should be called before fit(), evaluate(), or predict().

axis Integer, tuple of integers, or None. The axis or axes tha