Minor changes to NMS Op implementation

TrainingExtensions/torch/src/python/aimet_torch/elementwise_ops.py

@@ -361,16 +361,27 @@ def forward(self, *args) -> torch.Tensor:
         res = []
         for index, (boxes, scores) in enumerate(zip(batches_boxes, batch_scores)):
             for class_index, classes_score in enumerate(scores):
-                filtered_score_ind = (classes_score > self.score_threshold).nonzero()[:, 0]
-                boxes = boxes[filtered_score_ind, :]
-                classes_score = classes_score[filtered_score_ind]
-                temp_res = torchvision.ops.nms(boxes, classes_score, self.iou_threshold)
-                res_ = filtered_score_ind[temp_res]
-                for val in res_:
-                    res.append([index, class_index, val.detach()])
-                res = res[:(self.max_output_boxes_per_class *(index+1))]
+                nms_output = self.perform_nms_per_class(boxes, classes_score)
+                res_per_class = []
+                for val in nms_output:
+                    res_per_class.append([index, class_index, val.detach()])
+                res_per_class = res_per_class[:self.max_output_boxes_per_class]
+                res.extend(res_per_class)
         return torch.Tensor(res).type(torch.int64)
 
+    def perform_nms_per_class(self, boxes: torch.Tensor, classes_score: torch.Tensor) -> torch.Tensor:
+        """
+        Performs NMS per class
+        :param boxes: boxes on which NMS should be performed
+        :param classes_score: corresponding class scores for the boxes
+        :return: returns box indices filtered out by NMS
+        """
+        filtered_score_ind = (classes_score > self.score_threshold).nonzero()[:, 0]
+        filtered_boxes = boxes[filtered_score_ind]
+        filtered_classes_score = classes_score[filtered_score_ind]
+        res_ = torchvision.ops.nms(filtered_boxes, filtered_classes_score, self.iou_threshold)
+        return filtered_score_ind[res_]
+
 
 class GatherNd(torch.nn.Module):
     """ GatherNd op implementation"""