def METHOD_NAME(self, params):
    """
    get cuda model data used by params
    """
    data_volume = self._grad_stats.unreleased_grad_volume
    for p in params:
        cur_model_data_volume = p.data.numel() * p.data.element_size()
        data_volume += cur_model_data_volume
        if self._training_phase == TrainingPhase.BACKWARD and p.requires_grad:
            # add param.grad, actually param.grad is None in this time
            data_volume += cur_model_data_volume
            if not self._grad_stats.unreleased_grad_flag[p]:
                self._grad_stats.unreleased_grad_volume += cur_model_data_volume
                self._grad_stats.unreleased_grad_flag[p] = True
    # record max non model data used for this Op
    self._memstats.record_max_cuda_model_data(data_volume)