def simple_test(self, feats, img_shapes, scale_factors, rescale=False):
        """Test det bboxes without test-time augmentation.

        Args:
            feats (tuple[Tensor]): Multi-level features from the
                upstream network, each is a 4D-tensor.
            img_shapes (Tensor): Image shapes.
            rescale (bool, optional): Whether to rescale the results.
                Defaults to False.

        Returns:
            list[tuple[Tensor, Tensor]]: Each item in result_list is 2-tuple.
                The first item is ``bboxes`` with shape (n, 5),
                where 5 represent (tl_x, tl_y, br_x, br_y, score).
                The shape of the second tensor in the tuple is ``labels``
                with shape (n,)
        """
        # forward of this head requires img_metas
        with_nms = True if self.nms is not None else False
        outs = self.forward(feats)
        return self.get_bboxes(
            outs[0], outs[1], img_shapes, scale_factors, rescale=rescale, with_nms=with_nms
        )
Test det bboxes without test-time augmentation.

        Args:
            feats (tuple[Tensor]): Multi-level features from the
                upstream network, each is a 4D-tensor.
            img_shapes (Tensor): Image shapes.
            rescale (bool, optional): Whether to rescale the results.
                Defaults to False.

        Returns:
            list[tuple[Tensor, Tensor]]: Each item in result_list is 2-tuple.
                The first item is ``bboxes`` with shape (n, 5),
                where 5 represent (tl_x, tl_y, br_x, br_y, score).
                The shape of the second tensor in the tuple is ``labels``
                with shape (n,)
        
ppdet/modeling/heads/co_deformable_detr_head.py