code: def get_normalized_item_freq(item2cnt):
      keys = list(item2cnt.keys())
      values = []
      total_value = sum(item2cnt.values())
      for key in keys:
          values.append(item2cnt[key] * 1.0 / total_value)
      values = np.asarray(values, dtype=np.float32)
      return keys, values
  
imports: import codecs
  import pickle
  import time
  import os
  from datetime import datetime
  import random
  import numpy
  import math
  from multiprocessing import Process
  from utils.general import *
  from utils.data_helper import *
label_desc: Use image node_id 10 for calling a global function with example usage: get_normalized_item_freq(item2cnt) and returns: keys,  values