code: def batch_norm_relu(inputs, is_training, relu=True):
      """Block of batch norm and relu."""
      inputs = mtf.layers.batch_norm(
          inputs,
          is_training,
          BATCH_NORM_DECAY,
          epsilon=BATCH_NORM_EPSILON,
          init_zero=(not relu),
      )
      if relu:
          inputs = mtf.relu(inputs)
      return inputs
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import mesh_tensorflow
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.utils import mtf_model
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 1 for calling a global function with example usage: batch_norm_relu(inputs, is_training, relu) and returns: inputs