code: def might_create_training_set():
      if not tf.gfile.Exists(TRAIN_FILE):
          labels = might_create_dataset(
              "train", TRAIN_FILE, shuffle=True
          )
          with tf.gfile.Open(CLASSES_FILE, "w") as f:
              for l in labels:
                  f.write("{}\n".format(l))
  
imports: import argparse
  import logging
  import multiprocessing
  import os
  import random
  import sys
  import time
  from xml.etree import ElementTree
  import numpy
  import tensorflow
  from tensorflow.contrib import slim
  from tensorflow.contrib.slim.python.slim.nets.inception_v3 import inception_v3, inception_v3_arg_scope
  from tensorflow.python.framework.errors_impl import OutOfRangeError
  from tensorflow.python.training import session_run_hook
  from tensorflow.python.training.basic_session_run_hooks import StopAtStepHook
  from tensorflow.python.training.monitored_session import SingularMonitoredSession
  import tensorlayer
label_desc: Use image node_id 3 for calling a global function with example usage: might_create_training_set() without return types