rename all test_processing_*.py to test_processor_*.py (#33878)

* rename all test_processing_*.py to test_processor_*.py ans fix duplicate test processor paligemma

* fix copies

* fix broken tests

* fix-copies

* fix test processor bridgetower

tests/models/donut/test_processor_donut.py

@@ -18,10 +18,6 @@ import tempfile
 import unittest
 
 from transformers import DonutImageProcessor, DonutProcessor, XLMRobertaTokenizerFast
-from transformers.testing_utils import (
-    require_torch,
-    require_vision,
-)
 
 from ...test_processing_common import ProcessorTesterMixin
 
@@ -65,30 +61,3 @@ class DonutProcessorTest(ProcessorTesterMixin, unittest.TestCase):
         actual_json = self.processor.token2json(sequence)
 
         self.assertDictEqual(actual_json, expected_json)
-
-    @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")
-        if not tokenizer.pad_token:
-            tokenizer.pad_token = "[TEST_PAD]"
-        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(
-            text=input_str,
-            images=image_input,
-            return_tensors="pt",
-            crop_size={"height": 214, "width": 214},
-            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]), 7)