UnitNormalization layer
UnitNormalization class
keras.layers.UnitNormalization(axis=-1, **kwargs)
Unit normalization layer.
Normalize a batch of inputs so that each input in the batch has a L2 norm
equal to 1 (across the axes specified in axis).
Example
>>> data = np.arange(6).reshape(2, 3)
>>> normalized_data = keras.layers.UnitNormalization()(data)
>>> print(np.sum(normalized_data[0, :] ** 2)
1.0
Arguments
- axis: Integer or list/tuple. The axis or axes to normalize across.
Typically, this is the features axis or axes. The left-out axes are
typically the batch axis or axes.
-1is the last dimension in the input. Defaults to-1.