code: def read_labels(data_file):
      labels = []
      lines = []
      with open(data_file, "r") as f:
          for line in f:
              labels_line = []
              words_line = []
              try:
                  line = unicode(line, "UTF-8").split()
              except NameError:
                  line = line.split()
              for word in line:
                  if word.startswith("__label__"):
                      labels_line.append(word)
                  else:
                      words_line.append(word)
              labels.append(labels_line)
              lines.append(" ".join(words_line))
      return lines, labels
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from fasttext import train_supervised
  from fasttext import train_unsupervised
  from fasttext import util
  import fasttext
  import os
  import subprocess
  import unittest
  import tempfile
  import random
  import sys
  import copy
  import numpy
  from fasttext.tests.test_configurations import get_supervised_models
label_desc: Use image node_id 8 for calling a global function with example usage: read_labels(data_file) and returns: lines,  labels