fix auxiliary loss training in DetrSegmentation (#28354)

* fix auxiliary loss training in detrSegmentation

* add auxiliary_loss testing

src/transformers/models/detr/modeling_detr.py

@@ -1826,9 +1826,9 @@ class DetrForSegmentation(DetrPreTrainedModel):
             outputs_loss["pred_masks"] = pred_masks
             if self.config.auxiliary_loss:
                 intermediate = decoder_outputs.intermediate_hidden_states if return_dict else decoder_outputs[-1]
-                outputs_class = self.class_labels_classifier(intermediate)
-                outputs_coord = self.bbox_predictor(intermediate).sigmoid()
-                auxiliary_outputs = self._set_aux_loss(outputs_class, outputs_coord)
+                outputs_class = self.detr.class_labels_classifier(intermediate)
+                outputs_coord = self.detr.bbox_predictor(intermediate).sigmoid()
+                auxiliary_outputs = self.detr._set_aux_loss(outputs_class, outputs_coord)
                 outputs_loss["auxiliary_outputs"] = auxiliary_outputs
 
             loss_dict = criterion(outputs_loss, labels)

tests/models/detr/test_modeling_detr.py

@@ -399,6 +399,22 @@ class DetrModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
         self.assertIsNotNone(decoder_attentions.grad)
         self.assertIsNotNone(cross_attentions.grad)
 
+    def test_forward_auxiliary_loss(self):
+        config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
+        config.auxiliary_loss = True
+
+        # only test for object detection and segmentation model
+        for model_class in self.all_model_classes[1:]:
+            model = model_class(config)
+            model.to(torch_device)
+
+            inputs = self._prepare_for_class(inputs_dict, model_class, return_labels=True)
+
+            outputs = model(**inputs)
+
+            self.assertIsNotNone(outputs.auxiliary_outputs)
+            self.assertEqual(len(outputs.auxiliary_outputs), self.model_tester.num_hidden_layers - 1)
+
     def test_forward_signature(self):
         config, _ = self.model_tester.prepare_config_and_inputs_for_common()