has_attentions - consistent test skipping logic and tf tests (#17495)

tests/models/convnext/test_modeling_convnext.py

@@ -158,6 +158,10 @@ class ConvNextModelTest(ModelTesterMixin, unittest.TestCase):
     def create_and_test_config_common_properties(self):
         return
 
+    @unittest.skip(reason="ConvNext does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     @unittest.skip(reason="ConvNext does not use inputs_embeds")
     def test_inputs_embeds(self):
         pass

tests/models/cvt/test_modeling_cvt.py

@@ -173,6 +173,10 @@ class CvtModelTest(ModelTesterMixin, unittest.TestCase):
     def create_and_test_config_common_properties(self):
         return
 
+    @unittest.skip(reason="Cvt does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     @unittest.skip(reason="Cvt does not use inputs_embeds")
     def test_inputs_embeds(self):
         pass

tests/models/flava/test_modeling_flava.py

@@ -695,6 +695,10 @@ class FlavaImageCodebookTest(ModelTesterMixin, unittest.TestCase):
             expected_arg_names = ["pixel_values"]
             self.assertListEqual(arg_names[:1], expected_arg_names)
 
+    @unittest.skip(reason="Flava does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     def test_model_common_attributes(self):
         # No embedding in multimodal model
         pass

tests/models/poolformer/test_modeling_poolformer.py

@@ -142,6 +142,10 @@ class PoolFormerModelTest(ModelTesterMixin, unittest.TestCase):
         config_and_inputs = self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*config_and_inputs)
 
+    @unittest.skip(reason="PoolFormer does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     @unittest.skip("PoolFormer does not use inputs_embeds")
     def test_inputs_embeds(self):
         pass

tests/models/regnet/test_modeling_regnet.py

@@ -147,6 +147,10 @@ class RegNetModelTest(ModelTesterMixin, unittest.TestCase):
     def create_and_test_config_common_properties(self):
         return
 
+    @unittest.skip(reason="RegNet does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     @unittest.skip(reason="RegNet does not use inputs_embeds")
     def test_inputs_embeds(self):
         pass

tests/models/resnet/test_modeling_resnet.py

@@ -147,6 +147,10 @@ class ResNetModelTest(ModelTesterMixin, unittest.TestCase):
     def create_and_test_config_common_properties(self):
         return
 
+    @unittest.skip(reason="ResNet does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     @unittest.skip(reason="ResNet does not use inputs_embeds")
     def test_inputs_embeds(self):
         pass

tests/models/van/test_modeling_van.py

@@ -144,6 +144,10 @@ class VanModelTest(ModelTesterMixin, unittest.TestCase):
     def create_and_test_config_common_properties(self):
         return
 
+    @unittest.skip(reason="Van does not output attentions")
+    def test_attention_outputs(self):
+        pass
+
     @unittest.skip(reason="Van does not use inputs_embeds")
     def test_inputs_embeds(self):
         pass

tests/test_modeling_common.py

@@ -485,10 +485,6 @@ class ModelTesterMixin:
             loss.backward()
 
     def test_attention_outputs(self):
-        if not self.has_attentions:
-            pass
-
-        else:
         config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
         config.return_dict = True
 

tests/test_modeling_tf_common.py

@@ -978,6 +978,7 @@ class TFModelTesterMixin:
             dict_inputs = self._prepare_for_class(inputs_dict, model_class)
             check_equivalence(model, tuple_inputs, dict_inputs, {"output_hidden_states": True})
 
+            if self.has_attentions:
                 tuple_inputs = self._prepare_for_class(inputs_dict, model_class)
                 dict_inputs = self._prepare_for_class(inputs_dict, model_class)
                 check_equivalence(model, tuple_inputs, dict_inputs, {"output_attentions": True})
@@ -992,6 +993,7 @@ class TFModelTesterMixin:
                 dict_inputs = self._prepare_for_class(inputs_dict, model_class, return_labels=True)
                 check_equivalence(model, tuple_inputs, dict_inputs, {"output_hidden_states": True})
 
+                if self.has_attentions:
                     tuple_inputs = self._prepare_for_class(inputs_dict, model_class, return_labels=True)
                     dict_inputs = self._prepare_for_class(inputs_dict, model_class, return_labels=True)
                     check_equivalence(model, tuple_inputs, dict_inputs, {"output_attentions": True})