code: def get_label_reader():
      """
      define the label reader
      :return: label reader
      """
      reader = ImageReader(["label"])
      reader.initialise(MOD_LABEL_DATA, MOD_LABEl_TASK, mod_label_list)
      label_normaliser = DiscreteLabelNormalisationLayer(
          image_name="label",
          modalities=vars(SINGLE_25D_TASK).get("label"),
          model_filename=os.path.join("testing_data", "agg_test.txt"),
      )
      reader.add_preprocessing_layers(label_normaliser)
      pad_layer = PadLayer(image_name=("label",), border=(5, 6, 7))
      reader.add_preprocessing_layers([pad_layer])
      return reader
  
imports: from __future__ import absolute_import, division, print_function
  import os
  import nibabel
  import numpy
  import pandas
  import tensorflow
  from niftynet.engine.sampler_resize_v2 import ResizeSampler
  from niftynet.engine.windows_aggregator_resize import ResizeSamplesAggregator
  from niftynet.io.image_reader import ImageReader
  from niftynet.io.image_sets_partitioner import ImageSetsPartitioner
  from niftynet.layer.discrete_label_normalisation import DiscreteLabelNormalisationLayer
  from niftynet.layer.pad import PadLayer
  from niftynet.utilities.util_common import ParserNamespace
  from tests.niftynet_testcase import NiftyNetTestCase
label_desc: Use image node_id 3 for calling a global function with example usage: get_label_reader() and returns: reader