def test_iadd(self, evt):
        rval = event.ReturnValue(append_events=[evt])
        rval2 = event.ReturnValue(eat=True, append_events=[evt])
        rset = event.ResultSet()

        rset += rval
        rset += rval2
        rset += None
        assert rset.eat
        assert rset.append_events == [evt, evt]
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