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 gradients(self, d_grads, g_grads):
      if self.d_grads is None:
          self.d_grads = [torch.zeros_like(_g) for _g in d_grads]
          self.g_grads = [torch.zeros_like(_g) for _g in g_grads]