[Misc] Automatically resolve HF processor init kwargs (#22005)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/model_executor/models/skyworkr1v.py

@@ -7,9 +7,8 @@
 # Copyright (c) 2025 Skywork
 # Licensed under The MIT License [see LICENSE for details]
 # --------------------------------------------------------
-from abc import ABC, abstractmethod
 from collections.abc import Iterable, Mapping, Sequence
-from typing import Literal, Optional, TypedDict, TypeVar, Union
+from typing import Literal, Optional, TypedDict, Union
 
 import torch
 import torch.nn as nn
@@ -232,7 +231,7 @@ def image_to_pixel_values_skyworkr1v(
     return pixel_values
 
 
-class BaseSkyworkR1VProcessor(ABC):
+class SkyworkR1VProcessor:
     """
     This model doesn't define its own HF processor,
     so we implement our own one here.
@@ -279,17 +278,18 @@ class BaseSkyworkR1VProcessor(ABC):
         self.use_thumbnail: bool = config.use_thumbnail
 
     @property
-    @abstractmethod
     def image_token_id(self) -> int:
-        raise NotImplementedError
+        return self.tokenizer.get_vocab()[IMG_CONTEXT]
 
-    @abstractmethod
     def get_image_repl(
         self,
         feature_size: int,
         num_patches: Optional[int],
     ) -> PromptUpdateDetails[str]:
-        raise NotImplementedError
+        repl_features = IMG_CONTEXT * feature_size
+        repl_full = IMG_START + repl_features + IMG_END
+
+        return PromptUpdateDetails.select_text(repl_full, IMG_CONTEXT)
 
     def resolve_min_max_num(
         self,
@@ -426,35 +426,15 @@ class BaseSkyworkR1VProcessor(ABC):
         }
 
 
-class SkyworkR1VProcessor(BaseSkyworkR1VProcessor):
+class SkyworkR1VProcessingInfo(BaseProcessingInfo):
 
-    @property
-    def image_token_id(self) -> int:
-        return self.tokenizer.get_vocab()[IMG_CONTEXT]
-
-    def get_image_repl(
-        self,
-        feature_size: int,
-        num_patches: Optional[int],
-    ) -> PromptUpdateDetails[str]:
-        repl_features = IMG_CONTEXT * feature_size
-        repl_full = IMG_START + repl_features + IMG_END
-
-        return PromptUpdateDetails.select_text(repl_full, IMG_CONTEXT)
-
-
-class BaseSkyworkR1VProcessingInfo(BaseProcessingInfo):
-
-    @abstractmethod
-    def get_hf_processor(
-        self,
-        *,
-        min_dynamic_patch: Optional[int] = None,
-        max_dynamic_patch: Optional[int] = None,
-        dynamic_image_size: Optional[bool] = None,
-        **kwargs: object,
-    ) -> BaseSkyworkR1VProcessor:
-        raise NotImplementedError
+    def get_hf_processor(self, **kwargs: object) -> SkyworkR1VProcessor:
+        return self.ctx.init_processor(
+            SkyworkR1VProcessor,
+            config=self.get_hf_config(),
+            tokenizer=self.get_tokenizer(),
+            **kwargs,
+        )
 
     def get_supported_mm_limits(self) -> Mapping[str, Optional[int]]:
         return {"image": None}
@@ -464,7 +444,7 @@ class BaseSkyworkR1VProcessingInfo(BaseProcessingInfo):
         *,
         image_width: int,
         image_height: int,
-        processor: Optional[BaseSkyworkR1VProcessor],
+        processor: Optional[SkyworkR1VProcessor],
     ) -> int:
         if processor is None:
             processor = self.get_hf_processor()
@@ -500,10 +480,8 @@ class BaseSkyworkR1VProcessingInfo(BaseProcessingInfo):
         return largest_feature_pinpoint
 
 
-_I = TypeVar("_I", bound=BaseSkyworkR1VProcessingInfo)
-
-
-class SkyworkR1VDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
+class SkyworkR1VDummyInputsBuilder(
+        BaseDummyInputsBuilder[SkyworkR1VProcessingInfo]):
 
     def get_dummy_text(self, mm_counts: Mapping[str, int]) -> str:
         num_images = mm_counts.get("image", 0)
@@ -527,7 +505,8 @@ class SkyworkR1VDummyInputsBuilder(BaseDummyInputsBuilder[_I]):
         }
 
 
-class SkyworkR1VMultiModalProcessor(BaseMultiModalProcessor[_I]):
+class SkyworkR1VMultiModalProcessor(
+        BaseMultiModalProcessor[SkyworkR1VProcessingInfo]):
 
     def _call_hf_processor(
         self,
@@ -617,31 +596,6 @@ class SkyworkR1VMultiModalProcessor(BaseMultiModalProcessor[_I]):
         ]
 
 
-class SkyworkR1VProcessingInfo(BaseSkyworkR1VProcessingInfo):
-
-    def get_hf_processor(
-        self,
-        *,
-        min_dynamic_patch: Optional[int] = None,
-        max_dynamic_patch: Optional[int] = None,
-        dynamic_image_size: Optional[bool] = None,
-        **kwargs: object,
-    ) -> SkyworkR1VProcessor:
-        if min_dynamic_patch is not None:
-            kwargs["min_dynamic_patch"] = min_dynamic_patch
-        if max_dynamic_patch is not None:
-            kwargs["max_dynamic_patch"] = max_dynamic_patch
-        if dynamic_image_size is not None:
-            kwargs["dynamic_image_size"] = dynamic_image_size
-
-        return self.ctx.init_processor(
-            SkyworkR1VProcessor,
-            config=self.get_hf_config(),
-            tokenizer=self.get_tokenizer(),
-            **kwargs,
-        )
-
-
 @MULTIMODAL_REGISTRY.register_processor(
     SkyworkR1VMultiModalProcessor,
     info=SkyworkR1VProcessingInfo,