[Bugfix] Fix qwen2.5-vl image processor (#13286)

Author: Isotr0py

vllm/model_executor/models/qwen2_5_vl.py

@@ -33,10 +33,11 @@
 import torch.nn.functional as F
 from einops import rearrange
 from transformers import BatchFeature
-from transformers.models.qwen2_5_vl import (Qwen2_5_VLImageProcessor,
-                                            Qwen2_5_VLProcessor)
+from transformers.models.qwen2_5_vl import Qwen2_5_VLProcessor
 from transformers.models.qwen2_5_vl.configuration_qwen2_5_vl import (
     Qwen2_5_VLConfig, Qwen2_5_VLVisionConfig)
+from transformers.models.qwen2_vl import (Qwen2VLImageProcessor,
+                                          Qwen2VLImageProcessorFast)
 
 from vllm.attention import AttentionMetadata
 from vllm.config import VllmConfig
@@ -693,7 +694,8 @@ def get_hf_processor(
     ) -> Qwen2_5_VLProcessor:
         hf_processor = self.ctx.get_hf_processor(Qwen2_5_VLProcessor)
         image_processor = hf_processor.image_processor  # type: ignore
-        assert isinstance(image_processor, Qwen2_5_VLImageProcessor)
+        assert isinstance(image_processor,
+                          (Qwen2VLImageProcessor, Qwen2VLImageProcessorFast))
 
         if min_pixels:
             image_processor.min_pixels = min_pixels
@@ -713,14 +715,15 @@ def get_image_processor(
         min_pixels: Optional[int] = None,
         max_pixels: Optional[int] = None,
         fps: Optional[float] = 2.0,
-    ) -> Qwen2_5_VLImageProcessor:
+    ) -> Union[Qwen2VLImageProcessor, Qwen2VLImageProcessorFast]:
         hf_processor = self.get_hf_processor(
             min_pixels=min_pixels,
             max_pixels=max_pixels,
             fps=fps,
         )
         image_processor = hf_processor.image_processor  # type: ignore
-        assert isinstance(image_processor, Qwen2_5_VLImageProcessor)
+        assert isinstance(image_processor,
+                          (Qwen2VLImageProcessor, Qwen2VLImageProcessorFast))
         return image_processor
 
 

vllm/model_executor/models/qwen2_vl.py

@@ -31,7 +31,9 @@
 import torch.nn as nn
 import torch.nn.functional as F
 from einops import rearrange, repeat
+from packaging.version import Version
 from transformers import BatchFeature
+from transformers import __version__ as TRANSFORMERS_VERSION
 from transformers.models.qwen2_vl import (Qwen2VLImageProcessor,
                                           Qwen2VLProcessor)
 from transformers.models.qwen2_vl.configuration_qwen2_vl import (
@@ -746,7 +748,13 @@ def get_image_processor(
         hf_processor = self.get_hf_processor(min_pixels=min_pixels,
                                              max_pixels=max_pixels)
         image_processor = hf_processor.image_processor  # type: ignore
-        assert isinstance(image_processor, Qwen2VLImageProcessor)
+        if Version(TRANSFORMERS_VERSION) >= Version("4.49"):
+            from transformers.models.qwen2_vl import Qwen2VLImageProcessorFast
+            assert isinstance(
+                image_processor,
+                (Qwen2VLImageProcessor, Qwen2VLImageProcessorFast))
+        else:
+            assert isinstance(image_processor, Qwen2VLImageProcessor)
         return image_processor
 
     def get_supported_mm_limits(self) -> Mapping[str, Optional[int]]: