Check models used for common tests are small (#24824)

* First models

* Conditional DETR

* Treat DETR models, skip others

* Skip LayoutLMv2 as well

* Fix last tests

tests/models/vit_mae/test_modeling_vit_mae.py

@@ -279,6 +279,10 @@ class ViTMAEModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
     def test_model_outputs_equivalence(self):
         pass
 
+    @unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
+    def test_model_is_small(self):
+        pass
+
     @slow
     def test_model_from_pretrained(self):
         for model_name in VIT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:

tests/models/vivit/test_modeling_vivit.py

@@ -310,6 +310,10 @@ class VivitModelTest(ModelTesterMixin, unittest.TestCase):
 
             check_hidden_states_output(inputs_dict, config, model_class)
 
+    @unittest.skip("Will be fixed soon by reducing the size of the model used for common tests.")
+    def test_model_is_small(self):
+        pass
+
 
 # We will verify our results on a video of eating spaghetti
 # Frame indices used: [164 168 172 176 181 185 189 193 198 202 206 210 215 219 223 227]

tests/test_modeling_common.py

@@ -2705,6 +2705,18 @@ class ModelTesterMixin:
                     else:
                         new_model_without_prefix(input_ids)
 
+    def test_model_is_small(self):
+        # Just a consistency check to make sure we are not running tests on 80M parameter models.
+        config, _ = self.model_tester.prepare_config_and_inputs_for_common()
+        # print(config)
+
+        for model_class in self.all_model_classes:
+            model = model_class(config)
+            num_params = model.num_parameters()
+            assert (
+                num_params < 1000000
+            ), f"{model_class} is too big for the common tests ({num_params})! It should have 200k max."
+
 
 global_rng = random.Random()