tf.math.l2_normalize

Normalizes along dimension axis using an L2 norm.

Main aliases

tf.linalg.l2_normalize, tf.nn.l2_normalize

Compat aliases for migration

See Migration guide for more details.

tf.compat.v2.linalg.l2_normalize, tf.compat.v2.math.l2_normalize, tf.compat.v2.nn.l2_normalize

tf.math.l2_normalize(
    x, axis=None, epsilon=1e-12, name=None
)

For a 1-D tensor with axis = 0, computes

output = x / sqrt(max(sum(x**2), epsilon))

For x with more dimensions, independently normalizes each 1-D slice along dimension axis.

x: A Tensor.
axis: Dimension along which to normalize. A scalar or a vector of integers.
epsilon: A lower bound value for the norm. Will use sqrt(epsilon) as the divisor if norm < sqrt(epsilon).
name: A name for this operation (optional).

A Tensor with the same shape as x.