[processor] clean up mulitmodal tests (#37362)

* clkea up mulitmodal processor tests

* fixup

* fix tests

* fix one last test

* forgot

tests/models/llama4/test_processor_llama4.py

@@ -15,7 +15,6 @@
 import shutil
 import tempfile
 import unittest
-from typing import Optional
 
 from transformers import AutoProcessor, Llama4Processor, PreTrainedTokenizerFast
 from transformers.testing_utils import require_vision
@@ -38,9 +37,10 @@ class Llama4ProcessorTest(ProcessorTesterMixin, unittest.TestCase):
 
         image_processor = Llama4ImageProcessorFast(max_patches=1, size={"height": 20, "width": 20})
         tokenizer = PreTrainedTokenizerFast.from_pretrained("unsloth/Llama-3.2-11B-Vision-Instruct-unsloth-bnb-4bit")
-        processor_kwargs = {}
+        processor_kwargs = cls.prepare_processor_dict()
         processor = Llama4Processor(image_processor, tokenizer, **processor_kwargs)
         processor.save_pretrained(cls.tmpdirname)
+        cls.image_token = processor.image_token
 
     def get_tokenizer(self, **kwargs):
         return AutoProcessor.from_pretrained(self.tmpdirname, **kwargs).tokenizer
@@ -51,21 +51,3 @@ class Llama4ProcessorTest(ProcessorTesterMixin, unittest.TestCase):
     @classmethod
     def tearDownClass(cls):
         shutil.rmtree(cls.tmpdirname)
-
-    # Override as Llama4Processor needs image tokens in prompts
-    def prepare_text_inputs(self, batch_size: Optional[int] = None):
-        if batch_size is None:
-            return "lower newer <|image|>"
-
-        if batch_size < 1:
-            raise ValueError("batch_size must be greater than 0")
-
-        if batch_size == 1:
-            return ["lower newer <|image|>"]
-        return ["lower newer <|image|>", "<|image|> upper older longer string"] + ["<|image|> lower newer"] * (
-            batch_size - 2
-        )
-
-    @unittest.skip("This test uses return_tensors='np' which is not supported")
-    def test_image_chat_template_accepts_processing_kwargs(self):
-        pass