Function l2_normalize

tensorflow/python/ops/nn_impl.py:596–619

Normalizes along dimension `axis` using an L2 norm. 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

(x, axis=None, epsilon=1e-12, name=None, dim=None)

@tf_export(v1=["math.l2_normalize", "linalg.l2_normalize", "nn.l2_normalize"])
@deprecated_args(None, "dim is deprecated, use axis instead", "dim")
def l2_normalize(x, axis=None, epsilon=1e-12, name=None, dim=None):
  """Normalizes along dimension `axis` using an L2 norm.

  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`.
  """
  axis = deprecated_argument_lookup("axis", axis, "dim", dim)
  return l2_normalize_v2(x, axis, epsilon, name, False)


@tf_export("math.l2_normalize", "linalg.l2_normalize", "nn.l2_normalize", v1=[])