Parameters
        ----------
        states : list
            the stack outputs from RNN, which consists of output from each time step (TNC).

        Returns
        --------
        loss : NDArray
            loss tensor with shape (batch_size,). Dimensions other than batch_axis are averaged out.

def hybrid_forward(self, F, *states): # pylint: disable=arguments-differ
        """
        Parameters
        ----------
        states : list
            the stack outputs from RNN, which consists of output from each time step (TNC).

        Returns
        --------
        loss : NDArray
            loss tensor with shape (batch_size,). Dimensions other than batch_axis are averaged out.
        """
        # pylint: disable=unused-argument
        if self._beta != 0:
            if states:
                means = [self._beta * (state[1:] - state[:-1]).__pow__(2).mean()
                         for state in states[-1:]]
                return F.add_n(*means)
            else:
                return F.zeros(1)
        return F.zeros(1)