def search(self, regex):
        try:
            spec = {'$or': [{'data.content'    : {'$regex': regex, '$options': 'im'}},
                            {'data.description': {'$regex': regex, '$options': 'im'}}]}
            fields = {'_id': 0}
            cur = self.db.docs.find(spec, fields)
        except Exception as e:
            raise DatabaseException(e)
        return [Document(**row) for row in cur]
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