code: def imdb(limit=None, shuffle=True):
      
  
      movie_review_url = 'http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz'
  
      # download and extract, thus remove the suffix '.tar.gz'
      path = keras.utils.get_file(
          'aclImdb.tar.gz', movie_review_url, extract=True)[:-7]
  
      X_train, y_train = read_pos_neg_data(path, 'train', limit)
      X_test, y_test = read_pos_neg_data(path, 'test', limit)
  
      if shuffle:
          X_train, y_train = sklearn.utils.shuffle(X_train, y_train)
          X_test, y_test = sklearn.utils.shuffle(X_test, y_test)
  
      return X_train, X_test, y_train, y_test
docs: Downloads (and caches) IMDB Moview Reviews. 25k training data, 25k test data
  
      Args:
          limit: get only first N items for each class
  
      Returns:
          [X_train, y_train, X_test, y_test]