no nans

transformers/tests/modeling_common_test.py

@@ -88,7 +88,13 @@ class CommonTestCases:
                     model = model_class.from_pretrained(tmpdirname)
                     with torch.no_grad():
                         after_outputs = model(**inputs_dict)
-                    max_diff = np.amax(np.abs(after_outputs[0].numpy() - outputs[0].numpy()))
+
+                    # Make sure we don't have nans
+                    out_1 = after_outputs[0].numpy()
+                    out_2 = outputs[0].numpy()
+                    out_1 = out_1[~np.isnan(out_1)]
+                    out_2 = out_2[~np.isnan(out_2)]
+                    max_diff = np.amax(np.abs(out_1 - out_2))
                     self.assertLessEqual(max_diff, 1e-5)
 
         def test_initialization(self):

transformers/tests/modeling_tf_common_test.py

@@ -92,7 +92,13 @@ class TFCommonTestCases:
                     model.save_pretrained(tmpdirname)
                     model = model_class.from_pretrained(tmpdirname)
                     after_outputs = model(inputs_dict)
-                    max_diff = np.amax(np.abs(after_outputs[0].numpy() - outputs[0].numpy()))
+
+                    # Make sure we don't have nans
+                    out_1 = after_outputs[0].numpy()
+                    out_2 = outputs[0].numpy()
+                    out_1 = out_1[~np.isnan(out_1)]
+                    out_2 = out_2[~np.isnan(out_2)]
+                    max_diff = np.amax(np.abs(out_1 - out_2))
                     self.assertLessEqual(max_diff, 1e-5)
 
         def test_pt_tf_model_equivalence(self):