fix common processor

src/transformers/processing_utils.py

@@ -736,12 +736,12 @@ def _merge_kwargs(
         The order of operations is as follows:
             1) kwargs passed as before have highest priority to preserve BC.
                 ```python
-                high_priority_kwargs = {"crop_size" = (224, 224), "padding" = "max_length"}
+                high_priority_kwargs = {"crop_size" = {"height": 222, "width": 222}, "padding" = "max_length"}
                 processor(..., **high_priority_kwargs)
                 ```
             2) kwargs passed as modality-specific kwargs have second priority. This is the recommended API.
                 ```python
-                processor(..., text_kwargs={"padding": "max_length"}, images_kwargs={"crop_size": (224, 224)}})
+                processor(..., text_kwargs={"padding": "max_length"}, images_kwargs={"crop_size": {"height": 222, "width": 222}}})
                 ```
             3) kwargs passed during instantiation of a modality processor have fourth priority.
                 ```python
@@ -799,14 +799,20 @@ class MyProcessingKwargs(ProcessingKwargs, CommonKwargs, TextKwargs, ImagesKwarg
         output_kwargs.update(default_kwargs)
 
         # gather common kwargs and remove them from individual kwargs if present
-        common_kwargs = {
-            key: value
-            for key, value in kwargs.items()
-            if key not in ModelProcessorKwargs.__annotations__["text_kwargs"].__annotations__
-            and key not in ModelProcessorKwargs.__annotations__["images_kwargs"].__annotations__
-            and key not in ModelProcessorKwargs.__annotations__["audio_kwargs"].__annotations__
-            and key not in ModelProcessorKwargs.__annotations__["videos_kwargs"].__annotations__
-        }
+        common_kwargs = {}
+        for key, value in kwargs.items():
+            if key == "common_kwargs":
+                for common_key, common_value in value.items():
+                    common_kwargs[common_key] = common_value
+            elif key in ["text_kwargs", "images_kwargs", "audio_kwargs", "videos_kwargs"]:
+                pass
+            elif (
+                key not in ModelProcessorKwargs.__annotations__["text_kwargs"].__annotations__
+                and key not in ModelProcessorKwargs.__annotations__["images_kwargs"].__annotations__
+                and key not in ModelProcessorKwargs.__annotations__["audio_kwargs"].__annotations__
+                and key not in ModelProcessorKwargs.__annotations__["videos_kwargs"].__annotations__
+            ):
+                common_kwargs[key] = value
 
         # ensure common kwargs are propagated to all relevant modalities
         for key, value in common_kwargs.items():
@@ -820,10 +826,10 @@ class MyProcessingKwargs(ProcessingKwargs, CommonKwargs, TextKwargs, ImagesKwarg
         # update modality kwargs with passed kwargs
         for modality in output_kwargs:
             for modality_key in ModelProcessorKwargs.__annotations__[modality].__annotations__.keys():
-                if modality in kwargs and modality_key in kwargs[modality]:
-                    output_kwargs[modality][modality_key] = kwargs[modality][modality_key]
-                elif modality_key in kwargs:
+                if modality_key in kwargs:
                     output_kwargs[modality][modality_key] = kwargs[modality_key]
+                elif modality in kwargs and modality_key in kwargs[modality]:
+                    output_kwargs[modality][modality_key] = kwargs[modality][modality_key]
         return output_kwargs
 
     @classmethod
@@ -988,5 +994,4 @@ def apply_chat_template(
 ProcessorMixin.push_to_hub = copy_func(ProcessorMixin.push_to_hub)
 if ProcessorMixin.push_to_hub.__doc__ is not None:
     ProcessorMixin.push_to_hub.__doc__ = ProcessorMixin.push_to_hub.__doc__.format(
-        object="processor", object_class="AutoProcessor", object_files="processor files"
-    )
+        object="processor", object_class="AutoProcessor", object_

tests/models/grounding_dino/test_processor_grounding_dino.py

@@ -43,6 +43,7 @@
 @require_torch
 @require_vision
 class GroundingDinoProcessorTest(ProcessorTesterMixin, unittest.TestCase):
+    from_pretrained_id = "IDEA-Research/grounding-dino-base"
     processor_class = GroundingDinoProcessor
 
     def setUp(self):
@@ -67,6 +68,13 @@ def setUp(self):
         with open(self.image_processor_file, "w", encoding="utf-8") as fp:
             json.dump(image_processor_map, fp)
 
+        image_processor = GroundingDinoImageProcessor()
+        tokenizer = BertTokenizer.from_pretrained(self.from_pretrained_id)
+
+        processor = GroundingDinoProcessor(image_processor, tokenizer)
+
+        processor.save_pretrained(self.tmpdirname)
+
         self.batch_size = 7
         self.num_queries = 5
         self.embed_dim = 5
@@ -281,4 +289,4 @@ def test_unstructured_kwargs_batched(self):
         )
         self.assertEqual(inputs["pixel_values"].shape[2], 214)
 
-        self.assertEqual(len(inputs["input_ids"][0]), 11)
+        self.assertEqual(len(inputs["input_ids"][0]), 6)

tests/test_processing_common.py

@@ -277,13 +277,13 @@ def test_doubly_passed_kwargs(self):
 
         input_str = ["lower newer"]
         image_input = self.prepare_image_inputs()
-        with self.assertRaises(ValueError):
-            _ = processor(
-                text=input_str,
-                images=image_input,
-                images_kwargs={"crop_size": {"height": 222, "width": 222}},
-                crop_size={"height": 214, "width": 214},
-            )
+        inputs = processor(
+            text=input_str,
+            images=image_input,
+            images_kwargs={"size": {"height": 222, "width": 222}},
+            size={"height": 35, "width": 35},
+        )
+        self.assertEqual(inputs["pixel_values"][0].shape[2], 35)
 
     @require_torch
     @require_vision