code: def main(_):
      with tf.Session() as session:
          num_actions = get_num_actions()
          graph_ops = build_graph(num_actions)
          saver = tf.train.Saver(max_to_keep=5)
  
          if testing:
              evaluation(session, graph_ops, saver)
          else:
              train(session, graph_ops, num_actions, saver)
  
imports: from __future__ import division, print_function, absolute_import
  import threading
  import random
  import numpy
  import time
  from skimage.transform import resize
  from skimage.color import rgb2gray
  from collections import deque
  import gym
  import tensorflow.compat.v1
  import tflearn
label_desc: Use image node_id 9 for calling a global function with example usage: main(_) without return types