code: def get_num_actions():
      """
      Returns the number of possible actions for the given atari game
      """
      # Figure out number of actions from gym env
      env = gym.make(game)
      num_actions = env.action_space.n
      return num_actions
  
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 6 for calling a global function with example usage: get_num_actions() and returns: num_actions