tf.keras.ops.layer_normalization

Layer normalization layer (Ba et al., 2016).

tf.keras.ops.layer_normalization(
    x, gamma=None, beta=None, axis=-1, epsilon=None, **kwargs
)

Normalize the activations of the previous layer for each given example in a batch independently, rather than across a batch like Batch Normalization. i.e. applies a transformation that maintains the mean activation within each example close to 0 and the activation standard deviation close to 1.

x Input tensor.
gamma Optional scaling factor for the normalization.
beta Optional add offset for the normalized tensor.
axis The axis or axes along which to perform normalization. Default to -1.
epsilon A lower bound value for the norm. Defaults to backend.epsilon().

The normalized array.

Example:

x = keras.ops.arange(5, dtype="float32")
keras.ops.layer_normalization(x)
array([-1.4142135, -0.70710677, 0.0, 0.7071067, 1.4142135])