def METHOD_NAME(self, tensor, grad):
    """Start backward propagation given the gradient of the output tensor.
    Args:
        tensor (:class:`torch.Tensor`): Output tensor.
        grad (:class:`torch.Tensor`): Gradient passed back to the output.
    """
    ret = self.optimizer.METHOD_NAME(tensor, grad)
    for ophook in self._ophook_list:
        ophook.post_iter()
    return ret