UnitNormalization layer
UnitNormalization class
tf_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 = tf.constant(np.arange(6).reshape(2, 3), dtype=tf.float32)
>>> normalized_data = tf.keras.layers.UnitNormalization()(data)
>>> print(tf.reduce_sum(normalized_data[0, :] ** 2).numpy())
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.