Model output test (#6155)

* Use return_dict=True in all tests

* Formatting

tests/test_modeling_xlm_roberta.py

@@ -28,7 +28,7 @@ if is_torch_available():
 class XLMRobertaModelIntegrationTest(unittest.TestCase):
     @slow
     def test_xlm_roberta_base(self):
-        model = XLMRobertaModel.from_pretrained("xlm-roberta-base")
+        model = XLMRobertaModel.from_pretrained("xlm-roberta-base", return_dict=True)
         input_ids = torch.tensor([[0, 581, 10269, 83, 99942, 136, 60742, 23, 70, 80583, 18276, 2]])
         # The dog is cute and lives in the garden house
 
@@ -40,14 +40,14 @@ class XLMRobertaModelIntegrationTest(unittest.TestCase):
         #  xlmr.eval()
         #  expected_output_values_last_dim = xlmr.extract_features(input_ids[0])[:, :, -1]
 
-        output = model(input_ids)[0].detach()
+        output = model(input_ids)["last_hidden_state"].detach()
         self.assertEqual(output.shape, expected_output_shape)
         # compare the actual values for a slice of last dim
         self.assertTrue(torch.allclose(output[:, :, -1], expected_output_values_last_dim, atol=1e-3))
 
     @slow
     def test_xlm_roberta_large(self):
-        model = XLMRobertaModel.from_pretrained("xlm-roberta-large")
+        model = XLMRobertaModel.from_pretrained("xlm-roberta-large", return_dict=True)
         input_ids = torch.tensor([[0, 581, 10269, 83, 99942, 136, 60742, 23, 70, 80583, 18276, 2]])
         # The dog is cute and lives in the garden house
 
@@ -59,7 +59,7 @@ class XLMRobertaModelIntegrationTest(unittest.TestCase):
         #  xlmr.eval()
         #  expected_output_values_last_dim = xlmr.extract_features(input_ids[0])[:, :, -1]
 
-        output = model(input_ids)[0].detach()
+        output = model(input_ids)["last_hidden_state"].detach()
         self.assertEqual(output.shape, expected_output_shape)
         # compare the actual values for a slice of last dim
         self.assertTrue(torch.allclose(output[:, :, -1], expected_output_values_last_dim, atol=1e-3))