code: def batch_normalization(input, name, **kwargs):
      mean = tf.Variable(
          __weights_dict[name]["mean"],
          name=name + "_mean",
          trainable=is_train,
      )
      variance = tf.Variable(
          __weights_dict[name]["var"],
          name=name + "_var",
          trainable=is_train,
      )
      offset = (
          tf.Variable(
              __weights_dict[name]["bias"],
              name=name + "_bias",
              trainable=is_train,
          )
          if "bias" in __weights_dict[name]
          else None
      )
      scale = (
          tf.Variable(
              __weights_dict[name]["scale"],
              name=name + "_scale",
              trainable=is_train,
          )
          if "scale" in __weights_dict[name]
          else None
      )
      return tf.nn.batch_normalization(
          input, mean, variance, offset, scale, name=name, **kwargs
      )
  
imports: import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: batch_normalization(input, name) and returns: tf