tf.compat.v1.linalg.l2_normalize

Normalizes along dimension axis using an L2 norm. (deprecated arguments)

View aliases

Compat aliases for migration

tf.compat.v1.math.l2_normalize, tf.compat.v1.nn.l2_normalize

tf.compat.v1.linalg.l2_normalize(
    x, axis=None, epsilon=1e-12, name=None, dim=None
)

Warning: SOME ARGUMENTS ARE DEPRECATED: (dim). They will be removed in a future version. Instructions for updating: dim is deprecated, use axis instead

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.

Args:

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).
dim: Deprecated alias for axis.

Returns:

A Tensor with the same shape as x.