# tf.nn.normalize_moments(counts, mean_ss, variance_ss, shift, name=None)

### tf.nn.normalize_moments(counts, mean_ss, variance_ss, shift, name=None)

See the guide: Neural Network > Normalization

Calculate the mean and variance of based on the sufficient statistics.

#### Args:

• counts: A Tensor containing a the total count of the data (one value).
• mean_ss: A Tensor containing the mean sufficient statistics: the (possibly shifted) sum of the elements to average over.
• variance_ss: A Tensor containing the variance sufficient statistics: the (possibly shifted) squared sum of the data to compute the variance over.
• shift: A Tensor containing the value by which the data is shifted for numerical stability, or None if no shift was performed.
• name: Name used to scope the operations that compute the moments.

#### Returns:

Two Tensor objects: mean and variance.

Defined in tensorflow/python/ops/nn_impl.py.