tf.nn.moments

Calculates the mean and variance of x.

tf.nn.moments(
    x, axes, shift=None, keepdims=False, name=None
)

Used in the notebooks

Used in the tutorials

The mean and variance are calculated by aggregating the contents of x across axes. If x is 1-D and axes = [0] this is just the mean and variance of a vector.

When using these moments for batch normalization (see tf.nn.batch_normalization):

  • for so-called "global normalization", used with convolutional filters with shape [batch, height, width, depth], pass axes=[0, 1, 2].
  • for simple batch normalization pass axes=[0] (batch only).

x A Tensor.
axes Array of ints. Axes along which to compute mean and variance.
shift Not used in the current implementation.
keepdims produce moments with the same dimensionality as the input.
name Name used to scope the operations that compute the moments.

Two Tensor objects: mean and variance.