Add support for args to ProcessorMixin for backward compatibility (#33479)

* add check and prepare args for BC to ProcessorMixin, improve ProcessorTesterMixin

* change size and crop_size in processor kwargs tests to do_rescale and rescale_factor

* remove unnecessary llava processor kwargs test overwrite

* nit

* change data_arg_name to input_name

* Remove unnecessary test override

* Remove unnecessary tests Paligemma

* Move test_prepare_and_validate_optional_call_args to TesterMixin, add docstring

tests/models/llava/test_processor_llava.py

@@ -17,7 +17,7 @@ import tempfile
 import unittest
 
 from transformers import AutoProcessor, AutoTokenizer, LlamaTokenizerFast, LlavaProcessor
-from transformers.testing_utils import require_torch, require_vision
+from transformers.testing_utils import require_vision
 from transformers.utils import is_vision_available
 
 from ...test_processing_common import ProcessorTesterMixin
@@ -93,29 +93,3 @@ class LlavaProcessorTest(ProcessorTesterMixin, unittest.TestCase):
 
         formatted_prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
         self.assertEqual(expected_prompt, formatted_prompt)
-
-    @require_torch
-    @require_vision
-    def test_unstructured_kwargs_batched(self):
-        if "image_processor" not in self.processor_class.attributes:
-            self.skipTest(f"image_processor attribute not present in {self.processor_class}")
-        image_processor = self.get_component("image_processor")
-        tokenizer = self.get_component("tokenizer")
-
-        processor = self.processor_class(tokenizer=tokenizer, image_processor=image_processor)
-        self.skip_processor_without_typed_kwargs(processor)
-
-        input_str = ["lower newer", "upper older longer string"]
-        image_input = self.prepare_image_inputs() * 2
-        inputs = processor(
-            images=image_input,
-            text=input_str,
-            return_tensors="pt",
-            size={"height": 214, "width": 214},
-            padding="longest",
-            max_length=76,
-        )
-
-        self.assertEqual(inputs["pixel_values"].shape[2], 214)
-
-        self.assertEqual(len(inputs["input_ids"][0]), 5)