[chat-template] Unify tests and clean up 🧼 (#37275)

* fix tests and some clean up

* make one general test for each modality

* remove redundant merging of kwargs

* edge cases

* dont enforce slow when reloading

* fix gemma3 tests

* has to adapt llama 4 after rebase

* remove also from overriden tests

* should be green now

tests/models/aria/test_processor_aria.py

@@ -236,55 +236,6 @@ And who is that?<|im_end|>
 """
         self.assertEqual(rendered, expected_rendered)
 
-    # Override as AriaImageProcessor doesn't accept `do_rescale`
-    def test_image_chat_template_accepts_processing_kwargs(self):
-        processor = self.get_processor()
-        if processor.chat_template is None:
-            self.skipTest("Processor has no chat template")
-
-        messages = [
-            [
-                {
-                    "role": "user",
-                    "content": [
-                        {"type": "text", "text": "What is shown in this image?"},
-                    ],
-                },
-            ]
-        ]
-
-        formatted_prompt_tokenized = processor.apply_chat_template(
-            messages,
-            add_generation_prompt=True,
-            tokenize=True,
-            padding="max_length",
-            max_length=50,
-        )
-        self.assertEqual(len(formatted_prompt_tokenized[0]), 50)
-
-        formatted_prompt_tokenized = processor.apply_chat_template(
-            messages,
-            add_generation_prompt=True,
-            tokenize=True,
-            truncation=True,
-            max_length=5,
-        )
-        self.assertEqual(len(formatted_prompt_tokenized[0]), 5)
-
-        # Now test the ability to return dict
-        messages[0][0]["content"].append(
-            {"type": "image", "url": "https://www.ilankelman.org/stopsigns/australia.jpg"}
-        )
-        out_dict = processor.apply_chat_template(
-            messages,
-            add_generation_prompt=True,
-            tokenize=True,
-            return_dict=True,
-            max_image_size=980,
-            return_tensors="np",
-        )
-        self.assertListEqual(list(out_dict[self.images_input_name].shape), [1, 3, 980, 980])
-
     # Override as AriaProcessor needs image tokens in prompts
     def prepare_text_inputs(self, batch_size: Optional[int] = None):
         if batch_size is None: