refactor: unify names of the feature field of MultimodalDataItem (#8075)

python/sglang/srt/models/vila.py

@@ -237,7 +237,7 @@ class VILAForConditionalGeneration(nn.Module):
         return cast(LogitsProcessorOutput, output)
 
     def get_image_feature(self, mm_input: List[MultimodalDataItem]) -> Tensor:
-        pixel_values = cast(Tensor, mm_input[0].pixel_values)
+        pixel_values = cast(Tensor, mm_input[0].feature)
 
         ##### BEGIN COPY modeling_vila.py #####
 

python/sglang/srt/multimodal/processors/base_processor.py

@@ -5,7 +5,6 @@ import multiprocessing as mp
 import os
 import re
 from abc import ABC, abstractmethod
-from functools import lru_cache
 from typing import Any, Dict, List, Optional, Tuple, Union
 
 import numpy as np
@@ -156,6 +155,10 @@ class BaseMultimodalProcessor(ABC):
             # "precomputed_features" - handled specially as it can be any modality
         }
 
+        # name of the feature filed
+        # TODO: pass from processors
+        self.FEATURE_NAMES = ["pixel_values", "pixel_values_videos", "audio_features"]
+
     def process_mm_data(
         self, input_text, images=None, videos=None, audios=None, **kwargs
     ):
@@ -524,6 +527,9 @@ class BaseMultimodalProcessor(ABC):
                 if modality not in items:
                     items[modality] = MultimodalDataItem(modality=modality)
 
+                if attr_name in self.FEATURE_NAMES:
+                    attr_name = "feature"
+
                 # Set attribute
                 setattr(items[modality], attr_name, value)
 

python/sglang/srt/multimodal/processors/clip.py

@@ -26,7 +26,7 @@ class ClipImageProcessor(BaseMultimodalProcessor):
         image_inputs["input_ids"] = image_inputs["input_ids"].tolist()[0]
         image_inputs["mm_items"] = [
             MultimodalDataItem(
-                pixel_values=image_inputs["pixel_values"], modality=Modality.IMAGE
+                feature=image_inputs["pixel_values"], modality=Modality.IMAGE
             )
         ]
 

python/sglang/srt/multimodal/processors/deepseek_vl_v2.py

@@ -68,7 +68,7 @@ class DeepseekVL2ImageProcessor(BaseMultimodalProcessor):
             input_ids=input_ids, mm_token_id=self._processor.image_token_id
         )
         item = MultimodalDataItem(
-            pixel_values=res["images"],
+            feature=res["images"],
             offsets=image_offsets,
             modality=Modality.IMAGE,
             image_emb_mask=images_seq_mask,

python/sglang/srt/multimodal/processors/internvl.py

@@ -223,7 +223,7 @@ class InternVLImageProcessor(BaseMultimodalProcessor):
         )
         items = [
             MultimodalDataItem(
-                pixel_values=pixel_values,
+                feature=pixel_values,
                 modality=Modality.IMAGE,
                 offsets=image_offsets,
             )

python/sglang/srt/multimodal/processors/janus_pro.py

@@ -47,7 +47,7 @@ class JanusProImageProcessor(BaseMultimodalProcessor):
         return {
             "mm_items": [
                 MultimodalDataItem(
-                    pixel_values=res["pixel_values"],
+                    feature=res["pixel_values"],
                     image_emb_mask=res["images_emb_mask"],
                     offsets=image_offsets,
                     modality=Modality.IMAGE,

python/sglang/srt/multimodal/processors/llava.py

@@ -158,7 +158,7 @@ class LlavaImageProcessor(BaseMultimodalProcessor):
         return {
             "mm_items": [
                 MultimodalDataItem(
-                    pixel_values=pixel_values,
+                    feature=pixel_values,
                     image_sizes=image_sizes,
                     modality=modality,
                 )

python/sglang/srt/multimodal/processors/minicpm.py

@@ -114,7 +114,7 @@ class MiniCPMMultimodalProcessor(BaseMultimodalProcessor):
 
         if len(pixel_values) != 0:
             item = MultimodalDataItem(
-                pixel_values=pixel_values,
+                feature=pixel_values,
                 offsets=image_offsets,
                 tgt_size=tgt_sizes_flat,
                 modality=Modality.IMAGE,
@@ -135,7 +135,7 @@ class MiniCPMMultimodalProcessor(BaseMultimodalProcessor):
             else:
                 audio_offsets = None
             item = MultimodalDataItem(
-                audio_features=[res["audio_features"]],
+                feature=[res["audio_features"]],
                 audio_feature_lens=res["audio_feature_lens"],
                 offsets=audio_offsets,
                 modality=Modality.AUDIO,

python/sglang/srt/multimodal/processors/mlama.py

@@ -24,7 +24,7 @@ class MllamaImageProcessor(BaseMultimodalProcessor):
         image_inputs["input_ids"] = image_inputs["input_ids"].tolist()[0]
         image_inputs["mm_items"] = [
             MultimodalDataItem(
-                pixel_values=image_inputs["pixel_values"],
+                feature=image_inputs["pixel_values"],
                 aspect_ratio_id=image_inputs["aspect_ratio_ids"],
                 aspect_ratio_mask=image_inputs["aspect_ratio_mask"],
                 modality=Modality.IMAGE,

python/sglang/srt/multimodal/processors/mllama4.py

@@ -142,7 +142,7 @@ class Mllama4ImageProcessor(BaseMultimodalProcessor):
         # Add metadata for image processing
         processor_output["mm_items"] = [
             MultimodalDataItem(
-                pixel_values=processor_output["pixel_values"],
+                feature=processor_output["pixel_values"],
                 modality=Modality.IMAGE,
                 offsets=image_offsets,
             )

python/sglang/srt/multimodal/processors/phi4mm.py

@@ -62,7 +62,7 @@ class Phi4MMImageProcessor(BaseMultimodalProcessor):
 
         items = [
             MultimodalDataItem(
-                pixel_values=res["input_image_embeds"],
+                feature=res["input_image_embeds"],
                 image_sizes=res["image_sizes"],
                 image_emb_mask=res["image_attention_mask"],
                 offsets=image_offsets,

python/sglang/srt/multimodal/processors/pixtral.py

@@ -103,7 +103,7 @@ class PixtralProcessor(BaseMultimodalProcessor):
             )
             mm_items = [
                 MultimodalDataItem(
-                    pixel_values=processor_output["pixel_values"],
+                    feature=processor_output["pixel_values"],
                     image_sizes=processor_output["image_sizes"],
                     modality=Modality.IMAGE,
                     offsets=image_offsets,

test/srt/test_vlm_accuracy.py

@@ -245,7 +245,7 @@ class TestMiniCPMVLogits(VisionLLMLogitsBase):
                     MultimodalInputs(
                         mm_items=[
                             MultimodalDataItem(
-                                pixel_values=pixel_values_flat,
+                                feature=pixel_values_flat,
                                 offsets=image_offsets,
                                 tgt_size=tgt_sizes_flat,
                                 modality=Modality.IMAGE,