[Bugfix] Fix embedding assignment for InternVL-based models (vllm-project#15086)

Signed-off-by: DarkLight1337 <[email protected]>

Author: DarkLight1337

examples/offline_inference/vision_language.py

@@ -169,7 +169,6 @@ def run_gemma3(questions: list[str], modality: str) -> ModelRequestData:
         model=model_name,
         max_model_len=2048,
         max_num_seqs=2,
-        # Default is False; setting it to True is not supported in V1 yet
         mm_processor_kwargs={"do_pan_and_scan": True},
         disable_mm_preprocessor_cache=args.disable_mm_preprocessor_cache,
     )

examples/offline_inference/vision_language_multi_image.py

@@ -91,8 +91,6 @@ def load_gemma3(question: str, image_urls: list[str]) -> ModelRequestData:
         model=model_name,
         max_model_len=8192,
         max_num_seqs=2,
-        # Default is False; setting it to True is not supported in V1 yet
-        mm_processor_kwargs={"do_pan_and_scan": True},
         limit_mm_per_prompt={"image": len(image_urls)},
     )
 

vllm/model_executor/models/gemma3_mm.py

@@ -183,7 +183,7 @@ def get_image_repl(
         image_width: int,
         image_height: int,
         processor: Optional[Gemma3Processor],
-    ) -> PromptUpdateDetails:
+    ) -> PromptUpdateDetails[str]:
         if processor is None:
             processor = self.get_hf_processor()
 

vllm/model_executor/models/h2ovl.py

@@ -249,20 +249,15 @@ def __init__(
     def image_token_id(self) -> int:
         return self.tokenizer.get_vocab()[IMG_CONTEXT]
 
-    def get_image_repl_features(
+    def get_image_repl(
         self,
         feature_size: int,
         num_patches: Optional[int],
-    ) -> str:
-        return IMG_CONTEXT * feature_size
+    ) -> PromptUpdateDetails[str]:
+        repl_features = IMG_CONTEXT * feature_size
+        repl_full = IMG_START + repl_features + IMG_END
 
-    def get_image_repl_full(
-        self,
-        feature_size: int,
-        num_patches: Optional[int],
-    ) -> str:
-        features = self.get_image_repl_features(feature_size, num_patches)
-        return IMG_START + features + IMG_END
+        return PromptUpdateDetails(full=repl_full, features=repl_features)
 
     def resolve_min_max_num(
         self,
@@ -501,12 +496,7 @@ def get_replacement_internvl(item_idx: int):
             if num_patches is not None:
                 assert isinstance(num_patches, int)
 
-            return PromptUpdateDetails(
-                full=hf_processor.get_image_repl_full(feature_size,
-                                                      num_patches),
-                features=hf_processor.get_image_repl_features(
-                    feature_size, num_patches),
-            )
+            return hf_processor.get_image_repl(feature_size, num_patches)
 
         return [
             PromptReplacement(