def forward(
        self,
        images,
        image_shapes,
        gt_boxes=None,
        proposals=None,
        scales_yx=None,
        **kwargs,
    ):
        """
        kwargs:
            max_detections (int), return_tensors {"np", "pt", None}, padding {None,
            "max_detections"}, pad_value (int), location = {"cuda", "cpu"}
        """
        if self.training:
            raise NotImplementedError()
        return self.inference(
            images=images,
            image_shapes=image_shapes,
            gt_boxes=gt_boxes,
            proposals=proposals,
            scales_yx=scales_yx,
            **kwargs,
        )

        kwargs:
            max_detections (int), return_tensors {"np", "pt", None}, padding {None,
            "max_detections"}, pad_value (int), location = {"cuda", "cpu"}
        
dpkd/transformers/examples/research_projects/visual_bert/modeling_frcnn.py