9f0b230e1f59cb399e36210483bc075760b02eaf,gluonvision/model_zoo/ssd/ssd.py,SSD,hybrid_forward,#SSD#Any#Any#,154

Before Change

        if autograd.is_recording():
            return [cls_preds, box_preds, anchors]
        bboxes = self.bbox_decoder(box_preds, anchors)
        cls_ids, scores = self.cls_decoder(F.softmax(cls_preds))
        result = F.concat(
            cls_ids.expand_dims(axis=-1), scores.expand_dims(axis=-1), bboxes, dim=-1)
        conf_mask = F.tile(scores.expand_dims(axis=-1) > 0.01, reps=(1, 1, 6))

After Change

        bboxes = self.bbox_decoder(box_preds, anchors)
        cls_ids, scores = self.cls_decoder(F.softmax(cls_preds, axis=-1))
        results = []
        for i in range(self.num_classes - 1):
            cls_id = cls_ids.slice_axis(axis=-1, begin=i, end=i+1)
            score = scores.slice_axis(axis=-1, begin=i, end=i+1)
            // per class results
            per_result = F.concat(*[cls_id, score, bboxes], dim=-1)
            if self.nms_thresh > 0 and self.nms_thresh < 1:
                per_result = F.contrib.box_nms(
                    per_result, overlap_thresh=self.nms_thresh, topk=self.nms_topk,
                    id_index=0, score_index=1, coord_start=2)
            results.append(per_result)
        result = F.concat(*results, dim=1)
        //
        // cls_ids, scores = self.cls_decoder(F.softmax(cls_preds))
        // result = F.concat(

Instances