code: def _test01(self, dtype):
      with test_util.device(True):
          x = constant_op.constant(
              [5, 5, 7, 7, 9, 9, 11, 11, 13, 13, 15, 15],
              dtype=dtype,
              shape=[1, 1, 6, 2],
          )
          scale = constant_op.constant([4, 5], dtype=float)
          offset = constant_op.constant([2, 3], dtype=float)
  
          batch_norm, batch_mean, batch_var = nn_impl.fused_batch_norm(
              x, scale, offset, is_training=True
          )
          relu = nn_ops.relu(batch_norm)
  
          y1 = array_ops.identity(relu)
          y2 = array_ops.identity(batch_mean)
          y3 = array_ops.identity(batch_var)
  
          return (y1, y2, y3)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import time
  import collections
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import nn_impl
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  import tensorflow.python.ops.nn_grad
  from tensorflow.python.platform import test
  from tensorflow.python.framework import test_util
  from tensorflow.python.client import session
  import numpy
label_desc: Use image node_id 1 for calling the BnAForwardTestSuite obj's underlying member method code with example usage: obj._test01(dtype) and returns: y1,  y2,  y3