code: def normalize_moments(counts, mean_ss, variance_ss, shift, name=None):
      """Calculate the mean and variance of based on the sufficient statistics.
  
      Args:
        counts: A `Tensor` containing 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`.
      """
      with ops.name_scope(
          name, "normalize", [counts, mean_ss, variance_ss, shift]
      ):
          divisor = math_ops.reciprocal(counts, name="divisor")
          if shift is not None:
              shifted_mean = math_ops.multiply(
                  mean_ss, divisor, name="shifted_mean"
              )
              mean = math_ops.add(shifted_mean, shift, name="mean")
          else:  # no shift.
              shifted_mean = math_ops.multiply(
                  mean_ss, divisor, name="mean"
              )
              mean = shifted_mean
          variance = math_ops.subtract(
              math_ops.multiply(variance_ss, divisor),
              math_ops.square(shifted_mean),
              name="variance",
          )
      return (mean, variance)
  
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 18 for calling a global function with example usage: normalize_moments(counts, mean_ss, variance_ss, shift, name) and returns: mean,  variance