fix (#6946)

tests/test_modeling_lxmert.py

@@ -120,8 +120,8 @@ class LxmertModelTester:
 
         output_attentions = self.output_attentions
         input_ids = ids_tensor([self.batch_size, self.seq_length], vocab_size=self.vocab_size)
-        visual_feats = torch.rand(self.batch_size, self.num_visual_features, self.visual_feat_dim)
-        bounding_boxes = torch.rand(self.batch_size, self.num_visual_features, 4)
+        visual_feats = torch.rand(self.batch_size, self.num_visual_features, self.visual_feat_dim, device=torch_device)
+        bounding_boxes = torch.rand(self.batch_size, self.num_visual_features, 4, device=torch_device)
 
         input_mask = None
         if self.use_lang_mask:
@@ -407,8 +407,8 @@ class LxmertModelTester:
         num_small_labels = int(config.num_qa_labels * 2)
         less_labels_ans = ids_tensor([self.batch_size], num_small_labels)
         more_labels_ans = ids_tensor([self.batch_size], num_large_labels)
-        model_pretrain = LxmertForPreTraining(config=config)
-        model_qa = LxmertForQuestionAnswering(config=config)
+        model_pretrain = LxmertForPreTraining(config=config).to(torch_device)
+        model_qa = LxmertForQuestionAnswering(config=config).to(torch_device)
         config.num_labels = num_small_labels
         end_labels = config.num_labels
 
@@ -560,6 +560,7 @@ class LxmertModelTest(ModelTesterMixin, unittest.TestCase):
     def test_model_from_pretrained(self):
         for model_name in LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
             model = LxmertModel.from_pretrained(model_name)
+            model.to(torch_device)
             self.assertIsNotNone(model)
 
     def test_attention_outputs(self):