def METHOD_NAME(config):
  """Initializes data normalizer."""
  normalizer = data_normalizer.registry[config['data_normalizer']](config)
  if normalizer.exists():
    return
  if config['task'] == 0:
    tf.reset_default_graph()
    data_helper = data_helpers.registry[config['data_type']](config)
    real_images, _ = data_helper.provide_data(batch_size=10)
    # Save normalizer.
    # Note if normalizer has been saved, save() is no-op. To regenerate the
    # normalizer, delete the normalizer file in train_root_dir/assets
    normalizer.save(real_images)
  else:
    while not normalizer.exists():
      time.sleep(5)