change text pair handling when positional arg

src/transformers/models/udop/processing_udop.py

@@ -37,10 +37,7 @@
 
 
 class UdopTextKwargs(TextKwargs, total=False):
-    text_pair: Optional[Union[PreTokenizedInput, List[PreTokenizedInput]]]
     word_labels: Optional[Union[List[int], List[List[int]]]]
-    text_target: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]]
-    text_pair_target: Optional[Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]]]
     boxes: Union[List[List[int]], List[List[List[int]]]]
 
 
@@ -87,6 +84,8 @@ class UdopProcessor(ProcessorMixin):
     attributes = ["image_processor", "tokenizer"]
     image_processor_class = "LayoutLMv3ImageProcessor"
     tokenizer_class = ("UdopTokenizer", "UdopTokenizerFast")
+    # For backward compatibility. See transformers.processing_utils.ProcessorMixin.prepare_and_validate_optional_call_args for more details.
+    optional_call_args = ["text_pair"]
 
     def __init__(self, image_processor, tokenizer):
         super().__init__(image_processor, tokenizer)
@@ -95,6 +94,10 @@ def __call__(
         self,
         images: Optional[ImageInput] = None,
         text: Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None,
+        # The following is to capture `text_pair` argument that may be passed as a positional argument.
+        # See transformers.processing_utils.ProcessorMixin.prepare_and_validate_optional_call_args for more details.
+        # This behavior is only needed for backward compatibility and will be removed in future versions.
+        *args,
         audio=None,
         videos=None,
         **kwargs: Unpack[UdopProcessorKwargs],
@@ -117,13 +120,8 @@ def __call__(
             UdopProcessorKwargs,
             tokenizer_init_kwargs=self.tokenizer.init_kwargs,
             **kwargs,
+            **self.prepare_and_validate_optional_call_args(*args),
         )
-        # for BC
-        if "text_pair " not in output_kwargs["text_kwargs"] and audio is not None:
-            logger.warning_once(
-                "The use of `text_pair` as an argument without specifying it explicitely as `text_pair=` will be deprecated in future versions."
-            )
-            output_kwargs["text_kwargs"]["text_pair"] = audio
 
         boxes = output_kwargs["text_kwargs"].pop("boxes", None)
         word_labels = output_kwargs["text_kwargs"].pop("word_labels", None)
@@ -230,4 +228,4 @@ def post_process_image_text_to_text(self, generated_outputs):
 
     @property
     def model_input_names(self):
-        return ["pixel_values", "input_ids", "attention_mask", "bbox"]
+        return ["pixel_values", "input_ids", "bbox", "attention_mask"]

tests/models/udop/test_processor_udop.py

@@ -54,7 +54,6 @@
 class UdopProcessorTest(ProcessorTesterMixin, unittest.TestCase):
     tokenizer_class = UdopTokenizer
     rust_tokenizer_class = UdopTokenizerFast
-    image_processor_class = LayoutLMv3ImageProcessor
     processor_class = UdopProcessor
     maxDiff = None
 
@@ -80,7 +79,7 @@ def get_tokenizer(self, **kwargs) -> PreTrainedTokenizer:
         return self.tokenizer_class.from_pretrained(self.tokenizer_pretrained_name, **kwargs)
 
     def get_image_processor(self, **kwargs):
-        return self.image_processor_class.from_pretrained(self.tmpdirname, **kwargs).image_processor
+        return LayoutLMv3ImageProcessor.from_pretrained(self.tmpdirname, **kwargs)
 
     def get_rust_tokenizer(self, **kwargs) -> PreTrainedTokenizerFast:
         return self.rust_tokenizer_class.from_pretrained(self.tokenizer_pretrained_name, **kwargs)
@@ -152,7 +151,7 @@ def test_model_input_names(self):
         input_str = "lower newer"
         image_input = self.prepare_image_inputs()
 
-        inputs = processor(text=input_str, images=image_input)
+        inputs = processor(images=image_input, text=input_str)
 
         self.assertListEqual(list(inputs.keys()), processor.model_input_names)
 
@@ -221,8 +220,8 @@ def test_unstructured_kwargs_batched(self):
         input_str = ["lower newer", "upper older longer string"]
         image_input = self.prepare_image_inputs() * 2
         inputs = processor(
-            text=input_str,
             images=image_input,
+            text=input_str,
             return_tensors="pt",
             size={"height": 214, "width": 214},
             padding="longest",