def _decode_multi_level_predictions(
        self,
        anchors: List[Boxes],
        pred_scores: List[Tensor],
        pred_deltas: List[Tensor],
        score_thresh: float,
        topk_candidates: int,
        image_size: Tuple[int, int],
    ) -> Instances:
        """
        Run `_decode_per_level_predictions` for all feature levels and concat the results.
        """
        predictions = [
            self._decode_per_level_predictions(
                anchors_i,
                box_cls_i,
                box_reg_i,
                self.test_score_thresh,
                self.test_topk_candidates,
                image_size,
            )
            # Iterate over every feature level
            for box_cls_i, box_reg_i, anchors_i in zip(pred_scores, pred_deltas, anchors)
        ]
        return predictions[0].cat(predictions)  # 'Instances.cat' is not scriptale but this is

        Run `_decode_per_level_predictions` for all feature levels and concat the results.
        
video_chat_with_StableLM/models/grit_src/third_party/CenterNet2/detectron2/modeling/meta_arch/dense_detector.py