Calculate the sufficient statistics for the mean and variance of x
.
tf.compat.v1.nn.sufficient_statistics( x, axes, shift=None, keep_dims=None, name=None, keepdims=None )
These sufficient statistics are computed using the one pass algorithm on an input that's optionally shifted. See: https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Computing_shifted_data
Args  

x  A Tensor . 
axes  Array of ints. Axes along which to compute mean and variance. 
shift  A Tensor containing the value by which to shift the data for numerical stability, or None if no shift is to be performed. A shift close to the true mean provides the most numerically stable results. 
keep_dims  produce statistics with the same dimensionality as the input. 
name  Name used to scope the operations that compute the sufficient stats. 
keepdims  Alias for keep_dims. 
Returns  

Four Tensor objects of the same type as x :

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Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/nn/sufficient_statistics