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Calculates the mean and variance of x.

    x, axes, shift=None, keepdims=False, name=None

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.