[Core] More fixes to MultiModalEmbeddings type handling (vllm-project#19715)

russellb · wwl2755-google · commit 8160aa9dec5e · 2025-07-01T00:22:46.000Z
Signed-off-by: Russell Bryant &lt;rbryant@redhat.com&gt;
diff --git a/vllm/model_executor/models/aria.py b/vllm/model_executor/models/aria.py
@@ -620,7 +620,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.config.image_token_index)
diff --git a/vllm/model_executor/models/aya_vision.py b/vllm/model_executor/models/aya_vision.py
@@ -430,7 +430,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids=input_ids,
                 inputs_embeds=inputs_embeds,
diff --git a/vllm/model_executor/models/blip2.py b/vllm/model_executor/models/blip2.py
@@ -641,7 +641,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 _IMAGE_TOKEN_ID)
diff --git a/vllm/model_executor/models/chameleon.py b/vllm/model_executor/models/chameleon.py
@@ -1005,7 +1005,8 @@ def get_input_embeddings(
     ) -> torch.Tensor:
 
         inputs_embeds = self.model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.model.vocabulary_mapping.image_token_id)
diff --git a/vllm/model_executor/models/deepseek_vl2.py b/vllm/model_executor/models/deepseek_vl2.py
@@ -600,7 +600,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.image_token_id)
diff --git a/vllm/model_executor/models/florence2.py b/vllm/model_executor/models/florence2.py
@@ -1046,7 +1046,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.pad_token_id)
diff --git a/vllm/model_executor/models/fuyu.py b/vllm/model_executor/models/fuyu.py
@@ -345,7 +345,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/gemma3_mm.py b/vllm/model_executor/models/gemma3_mm.py
@@ -592,7 +592,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/glm4v.py b/vllm/model_executor/models/glm4v.py
@@ -609,7 +609,8 @@ def get_input_embeddings(
     ) -> torch.Tensor:
         inputs_embeds = self.transformer.get_input_embeddings(input_ids)
 
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids=input_ids,
                 inputs_embeds=inputs_embeds,
diff --git a/vllm/model_executor/models/granite_speech.py b/vllm/model_executor/models/granite_speech.py
@@ -721,7 +721,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         """Compute the merged LLM / audio embeddings."""
-        if multimodal_embeddings is None:
+        if multimodal_embeddings is None \
+            or len(multimodal_embeddings) == 0:
             return self.language_model.get_input_embeddings(input_ids)
 
         inputs_embeds = embed_multimodal(
diff --git a/vllm/model_executor/models/idefics3.py b/vllm/model_executor/models/idefics3.py
@@ -720,7 +720,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/internvl.py b/vllm/model_executor/models/internvl.py
@@ -1336,7 +1336,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             context_token_ids = [
                 token_id for token_id in (self.img_context_token_id,
                                           self.video_context_token_id)
diff --git a/vllm/model_executor/models/kimi_vl.py b/vllm/model_executor/models/kimi_vl.py
@@ -393,7 +393,8 @@ def get_input_embeddings(
         # model as one of the requirements of basic vLLM model implementation.
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
 
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None and len(
+                multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids=input_ids,
                 inputs_embeds=inputs_embeds,
diff --git a/vllm/model_executor/models/llava.py b/vllm/model_executor/models/llava.py
@@ -683,7 +683,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/llava_next.py b/vllm/model_executor/models/llava_next.py
@@ -502,7 +502,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
 
-        if not multimodal_embeddings:
+        if multimodal_embeddings is None \
+            or len(multimodal_embeddings) == 0:
             return self.language_model.get_input_embeddings(input_ids)
 
         inputs_embeds = embed_multimodal(
diff --git a/vllm/model_executor/models/llava_next_video.py b/vllm/model_executor/models/llava_next_video.py
@@ -426,7 +426,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.config.video_token_index)
diff --git a/vllm/model_executor/models/llava_onevision.py b/vllm/model_executor/models/llava_onevision.py
@@ -881,7 +881,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 [self.config.image_token_index, self.config.video_token_index])
diff --git a/vllm/model_executor/models/minicpmv.py b/vllm/model_executor/models/minicpmv.py
@@ -892,7 +892,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.llm.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             assert len(self.mm_token_ids) > 0
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
diff --git a/vllm/model_executor/models/minimax_vl_01.py b/vllm/model_executor/models/minimax_vl_01.py
@@ -201,7 +201,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/mistral3.py b/vllm/model_executor/models/mistral3.py
@@ -521,7 +521,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/mllama4.py b/vllm/model_executor/models/mllama4.py
@@ -808,7 +808,8 @@ def get_input_embeddings(
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
 
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None and len(
+                multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/molmo.py b/vllm/model_executor/models/molmo.py
@@ -1487,7 +1487,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             assert self.img_patch_id is not None
 
             inputs_embeds = merge_multimodal_embeddings(
diff --git a/vllm/model_executor/models/ovis.py b/vllm/model_executor/models/ovis.py
@@ -515,7 +515,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.llm.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.image_pad_token_id)
diff --git a/vllm/model_executor/models/paligemma.py b/vllm/model_executor/models/paligemma.py
@@ -364,7 +364,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.config.image_token_index)
diff --git a/vllm/model_executor/models/phi3v.py b/vllm/model_executor/models/phi3v.py
@@ -669,7 +669,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.embed_tokens(input_ids)
-        if multimodal_embeddings:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.image_token_id)
diff --git a/vllm/model_executor/models/phi4mm.py b/vllm/model_executor/models/phi4mm.py
@@ -1148,7 +1148,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.model.embed_tokens(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None and len(
+                multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 [_IMAGE_PLACEHOLDER_TOKEN_ID, _AUDIO_PLACEHOLDER_TOKEN_ID])
diff --git a/vllm/model_executor/models/pixtral.py b/vllm/model_executor/models/pixtral.py
@@ -423,7 +423,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/qwen2_5_omni_thinker.py b/vllm/model_executor/models/qwen2_5_omni_thinker.py
@@ -805,7 +805,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
 
             # TODO (ywang96): support overlapping modalitiy embeddings so that
             # `use_audio_in_video` will work on V1.
@@ -845,7 +846,7 @@ def get_input_embeddings_v0(
         multimodal_embeddings: Optional[NestedTensors] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is None:
+        if multimodal_embeddings is None or len(multimodal_embeddings) == 0:
             return inputs_embeds
 
         for embeddings, modality in multimodal_embeddings:
diff --git a/vllm/model_executor/models/qwen2_5_vl.py b/vllm/model_executor/models/qwen2_5_vl.py
@@ -1046,7 +1046,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 [self.config.image_token_id, self.config.video_token_id])
diff --git a/vllm/model_executor/models/qwen2_audio.py b/vllm/model_executor/models/qwen2_audio.py
@@ -364,7 +364,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.config.audio_token_index)
diff --git a/vllm/model_executor/models/qwen2_vl.py b/vllm/model_executor/models/qwen2_vl.py
@@ -1289,7 +1289,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 [self.config.image_token_id, self.config.video_token_id])
diff --git a/vllm/model_executor/models/qwen_vl.py b/vllm/model_executor/models/qwen_vl.py
@@ -754,7 +754,8 @@ def get_input_embeddings(
     ) -> torch.Tensor:
         inputs_embeds = self.transformer.get_input_embeddings(input_ids)
 
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids, inputs_embeds, multimodal_embeddings,
                 self.transformer.visual.image_pad_id)
diff --git a/vllm/model_executor/models/skyworkr1v.py b/vllm/model_executor/models/skyworkr1v.py
@@ -883,7 +883,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             assert self.img_context_token_id is not None
             self._set_visual_token_mask(input_ids)
             inputs_embeds = merge_multimodal_embeddings(
diff --git a/vllm/model_executor/models/tarsier.py b/vllm/model_executor/models/tarsier.py
@@ -598,7 +598,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
             inputs_embeds = merge_multimodal_embeddings(
                 input_ids,
                 inputs_embeds,
diff --git a/vllm/model_executor/models/ultravox.py b/vllm/model_executor/models/ultravox.py
@@ -560,7 +560,8 @@ def get_input_embeddings(
         multimodal_embeddings: Optional[MultiModalEmbeddings] = None,
     ) -> torch.Tensor:
         inputs_embeds = self.language_model.get_input_embeddings(input_ids)
-        if multimodal_embeddings is not None:
+        if multimodal_embeddings is not None \
+            and len(multimodal_embeddings) != 0:
 
             # TODO(ywang96): remove this block after v0 is deprecated.
             if not envs.VLLM_USE_V1:
