Missed TensorFlow Dev Summit? Check out the video playlist. Watch recordings

tf.compat.v1.linalg.l2_normalize

View source on GitHub

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

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

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.