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Calculates the mean and variance of x.
tf.compat.v2.nn.moments(
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], passaxes=[0, 1, 2]. - for simple batch normalization pass
axes=[0](batch only).
Args | |
|---|---|
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. |
Returns | |
|---|---|
Two Tensor objects: mean and variance.
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