code: def _running_mean(self, old_mean, new_val, factor):
      if factor == 1.0:
          return new_val
      else:
          return (1.0 - factor) * old_mean + factor * new_val
  
imports: import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_fused_batch_norm_grad
  from tensorflow.python.ops import nn_impl
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the BatchNormalizationTest obj's underlying member method code with example usage: obj._running_mean(old_mean, new_val, factor) and returns: new_val, unknown