code: def lm1b_preprocess(dataset, training,
                      max_target_length=-1, max_eval_target_length=-1):
    
  
    def target_right_length(_, target):
      return tf.less(tf.shape(target)[0], max_target_length + 1)
  
    def eval_target_right_length(_, target):
      return tf.less(tf.shape(target)[0], max_eval_target_length + 1)
  
    if max_target_length > 0 and training:
      dataset = dataset.filter(target_right_length)
  
    if max_eval_target_length > 0 and not training:
      dataset = dataset.filter(eval_target_right_length)
  
    return dataset
docs: Preprocessing for LM1B: filter out targets exceeding maximum length.