tf.keras.layers.UnitNormalization

Unit normalization layer.

Inherits From: Layer, Module

tf.keras.layers.UnitNormalization(
    axis=-1, **kwargs
)

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

Args
`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. `-1` is the last dimension in the input. Defaults to `-1`.

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Last updated 2023-10-06 UTC.

tf.keras.layers.UnitNormalization

Example:

Args