code: def example_splits(url_file, all_files):
      """Generate splits of the data."""
  
      def generate_hash(inp):
          """Generate a sha1 hash to match the raw url to the filename extracted."""
          h = hashlib.sha1()
          h.update(inp)
          return h.hexdigest()
  
      all_files_map = {f.split("/")[-1]: f for f in all_files}
  
      urls = [
          line.strip().encode("utf-8")
          for line in tf.gfile.Open(url_file)
      ]
  
      filelist = []
      for url in urls:
          url_hash = generate_hash(url)
          filename = url_hash + ".story"
          if filename not in all_files_map:
              tf.logging.info("Missing file: %s" % url)
              continue
          filelist.append(all_files_map[filename])
  
      tf.logging.info("Found %d examples" % len(filelist))
  
      return filelist
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import hashlib
  import io
  import os
  import random
  import tarfile
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import text_problems
  from tensor2tensor.data_generators import wiki_lm
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: example_splits(url_file, all_files) and returns: filelist, h