code: def _regularize_20m_dataset(temp_dir):
      """
      ratings.csv
        Each line of this file after the header row represents one rating of one
        movie by one user, and has the following format:
        userId,movieId,rating,timestamp
        - The lines within this file are ordered first by userId, then, within user,
          by movieId.
        - Ratings are made on a 5-star scale, with half-star increments
          (0.5 stars - 5.0 stars).
        - Timestamps represent seconds since midnight Coordinated Universal Time
          (UTC) of January 1, 1970.
        - All the users had rated at least 20 movies.
  
      movies.csv
        Each line has the following format:
        MovieID,Title,Genres
          - MovieIDs range from 1 and 3952
      """
      working_dir = os.path.join(temp_dir, ML_20M)
  
      _transform_csv(
          input_path=os.path.join(working_dir, "ratings.csv"),
          output_path=os.path.join(temp_dir, RATINGS_FILE),
          names=RATING_COLUMNS,
          skip_first=True,
          separator=",",
      )
  
      _transform_csv(
          input_path=os.path.join(working_dir, "movies.csv"),
          output_path=os.path.join(temp_dir, MOVIES_FILE),
          names=MOVIE_COLUMNS,
          skip_first=True,
          separator=",",
      )
  
      tf.io.gfile.rmtree(working_dir)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import tempfile
  import zipfile
  import numpy
  import pandas
  import six
  from six.moves import urllib
  from absl import app
  from absl import flags
  from absl import logging
  import tensorflow
  from utils.flags import core
label_desc: Use image node_id 4 for calling a global function with example usage: _regularize_20m_dataset(temp_dir) without return types