code: def get_class_label_dict(labels_dir):
      label = []
      labels_path = os.path.join(labels_dir, "labels.txt")
      proto_as_ascii_lines = tf.gfile.GFile(labels_path).readlines()
      for temp in proto_as_ascii_lines:
          label.append(temp.rstrip())
      return label
  
file_path: MachineLearningNotebooks/tutorials/machine-learning-pipelines-advanced/scripts/batch_scoring.py
imports: import os
  import argparse
  import datetime
  import time
  import tensorflow.compat.v1
  from math import ceil
  import numpy
  import sys
  import shutil
  import subprocess
  import tf_slim
  from azureml.core import Run
  from azureml.core.model import Model
  from azureml.core.dataset import Dataset
  from tf_slim import nets
label_desc: Use image node_id 1 for calling a global function with example usage: get_class_label_dict(labels_dir) and returns: label