def bbox(self):
        """
        return torch.Tensor([N,4]), in xmin, ymin, xmax, ymax form
        """
        assert len(self.instance_list) != 0
        instance_bbox_list = []
        for instance in self.instance_list:
            # bounds is bbox: [xmin, ymin, xmax, ymax]
            instance_bbox_list.append(instance.bounds)
        instance_bbox_array = np.array(instance_bbox_list)
        instance_bbox_tensor = to_tensor(instance_bbox_array)
        instance_bbox_tensor = instance_bbox_tensor.to(
                            dtype=torch.float32)
        instance_bbox_tensor[:,0] = torch.clamp(instance_bbox_tensor[:,0], min=-self.max_x,max=self.max_x)
        instance_bbox_tensor[:,1] = torch.clamp(instance_bbox_tensor[:,1], min=-self.max_y,max=self.max_y)
        instance_bbox_tensor[:,2] = torch.clamp(instance_bbox_tensor[:,2], min=-self.max_x,max=self.max_x)
        instance_bbox_tensor[:,3] = torch.clamp(instance_bbox_tensor[:,3], min=-self.max_y,max=self.max_y)
        return instance_bbox_tensor

        return torch.Tensor([N,4]), in xmin, ymin, xmax, ymax form
        
projects/mmdet3d_plugin/datasets/nuscenes_vad_dataset.py