def METHOD_NAME(self, sample_dict, net_out_dict):
    mask_cls = net_out_dict['logits']
    mask_pred = net_out_dict['masks']
    mask_cls = mask_cls[0]
    mask_pred = mask_pred[0]
    sem_prob, sem_pred = self._semantic_inference(mask_cls, mask_pred)
    _, pan_pred = self._panoptic_inference(mask_cls, mask_pred)
    sem_pred = sem_pred.unsqueeze_([0, 1])
    pan_pred = pan_pred.unsqueeze_([0, 1])
    sem_prob = sem_prob.unsqueeze_(0)
    pp_out = build_info_dict(
        _type_='pp_out',
        pan_pred=pan_pred,
        sem_prob=sem_prob,
        sem_pred=sem_pred)
    return pp_out