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tf.compat.v1.nn.sufficient_statistics

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:
  • the count (number of elements to average over).
  • the (possibly shifted) sum of the elements in the array.
  • the (possibly shifted) sum of squares of the elements in the array.
  • the shift by which the mean must be corrected or None if shift is None.

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Licensed under the Creative Commons Attribution License 3.0.
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