code: def print_top_n(probs, n=5):
      top_classes, class_probs = top_n(probs, n)
  
      print("-----------------------")
      print("Top-{} predicted classes".format(n))
      print("-----------------------")
  
      for top_class, class_prob in zip(top_classes, class_probs):
          print("{:<80s}: {:.2%}".format(top_class, class_prob))
  
      print("-----------------------")
  
file_path: neupy/examples/cnn/imagenet_tools.py
imports: from __future__ import division
  import os
  import requests
  from tqdm import tqdm
  import numpy
  from imageio import imread
  from skimage import transform
  from neupy.utils import asfloat
label_desc: Use image node_id 7 for calling a global function with example usage: print_top_n(probs, n) without return types