code: def maybe_download(file_urls, directory):
      """Download a set of files in temporary local folder."""
  
      # Create directory if doesn't exist
      assert create_dir_if_needed(directory)
  
      # This list will include all URLS of the local copy of downloaded files
      result = []
  
      # For each file of the dataset
      for file_url in file_urls:
          # Extract filename
          filename = file_url.split("/")[-1]
  
          # If downloading from GitHub, remove suffix ?raw=True from local filename
          if filename.endswith("?raw=true"):
              filename = filename[:-9]
  
          # Deduce local file url
          # filepath = os.path.join(directory, filename)
          filepath = directory + "/" + filename
  
          # Add to result list
          result.append(filepath)
  
          # Test if file already exists
          if not tf.gfile.Exists(filepath):
  
              def _progress(count, block_size, total_size):
                  sys.stdout.write(
                      "\r>> Downloading %s %.1f%%"
                      % (
                          filename,
                          float(count * block_size)
                          / float(total_size)
                          * 100.0,
                      )
                  )
                  sys.stdout.flush()
  
              filepath, _ = urllib.request.urlretrieve(
                  file_url, filepath, _progress
              )
              print()
              statinfo = os.stat(filepath)
              print(
                  "Successfully downloaded",
                  filename,
                  statinfo.st_size,
                  "bytes.",
              )
  
      return result
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gzip
  import math
  import os
  import sys
  import tarfile
  import numpy
  from scipy.io import loadmat
  from six.moves import cPickle
  from six.moves import urllib
  from six.moves import xrange
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: maybe_download(file_urls, directory) and returns: result