def get_last_tid(self):
        try:
            spec = {'tid': {'$gt': 0}}
            sort = [('tid', -1)]
            row = self.db.docs.find_one(spec, sort=sort)
        except Exception as e:
            raise DatabaseException(e)
        if row:
            return row['tid']
        return 0
def _apply_mask(y_true, sample_weight, masked_tokens, dtype):
  if sample_weight is None:
    sample_weight = tf.ones_like(y_true, dtype)
  else:
    sample_weight = tf.cast(sample_weight, dtype)
  for token in masked_tokens:
    mask = tf.cast(tf.not_equal(y_true, token), dtype)
    sample_weight = sample_weight * mask
  return sample_weight