old_contents: from keras.preprocessing import sequence
  from keras.datasets import imdb
  from deepcpg.utils import get_from_module
  
  
  def data(max_features=5000, maxlen=400):
      print('Loading data...')
      (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features)
  
      # subset the data
      x_train = x_train[:1000]
      y_train = y_train[:1000]
      x_test = x_test[:100]
      y_test = y_test[:100]
  
      print(len(x_train), 'train sequences')
      print(len(x_test), 'test sequences')
  
      print('Pad sequences (samples x time)')
      x_train = sequence.pad_sequences(x_train, maxlen=maxlen)
      x_test = sequence.pad_sequences(x_test, maxlen=maxlen)
      print('x_train shape:', x_train.shape)
      print('x_test shape:', x_test.shape)
      return (x_train, y_train, [1, 2, 3, "dummy_data"]), (x_test, y_test)
  
  
  def get(name):
      return get_from_module(name, globals())
  
new_contents: from keras.preprocessing import sequence
  from keras.datasets import imdb
  
  
  def data(max_features=5000, maxlen=400):
      print('Loading data...')
      (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=max_features)
  
      # subset the data
      x_train = x_train[:1000]
      y_train = y_train[:1000]
      x_test = x_test[:100]
      y_test = y_test[:100]
  
      print(len(x_train), 'train sequences')
      print(len(x_test), 'test sequences')
  
      print('Pad sequences (samples x time)')
      x_train = sequence.pad_sequences(x_train, maxlen=maxlen)
      x_test = sequence.pad_sequences(x_test, maxlen=maxlen)
      print('x_train shape:', x_train.shape)
      print('x_test shape:', x_test.shape)
      return (x_train, y_train, [1, 2, 3, "dummy_data"]), (x_test, y_test)
subject: Update data.py