code: def sufficient_statistics_v2(
      x, axes, shift=None, keepdims=False, name=None
  ):
      """Calculate the sufficient statistics for the mean and variance of `x`.
  
      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.
        keepdims: produce statistics with the same dimensionality as the input.
        name: Name used to scope the operations that compute the sufficient stats.
  
      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.
      """
      return sufficient_statistics(
          x=x, axes=axes, shift=shift, keep_dims=keepdims, name=name
      )
  
imports: import math
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import candidate_sampling_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import ctc_ops
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import embedding_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gen_sparse_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_fused_batch_norm_grad
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import device_context
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.deprecation import deprecated_args
  from tensorflow.python.util.deprecation import deprecated_argument_lookup
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 17 for calling a global function with example usage: sufficient_statistics_v2(x, axes, shift, keepdims, name) and returns: sufficient_statistics