[Model] Move vision_feature_select_strategy into resolve_visual_encoder_outputs (#25938)

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

vllm/model_executor/models/llava_next.py

@@ -235,12 +235,12 @@ class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal,
         # Determine the layer up to which we will initialize the vision tower
         if isinstance(vision_feature_layer, int):
             vision_hidden_size = config.vision_config.hidden_size
-            self.feature_sample_layers = None
+            self.select_layers = None
         # Used for multimodal granite models to control encoder outputs
         elif isinstance(vision_feature_layer, (list, tuple)):
             vision_hidden_size = config.vision_config.hidden_size * len(
                 vision_feature_layer)
-            self.feature_sample_layers = vision_feature_layer
+            self.select_layers = vision_feature_layer
         else:
             raise TypeError(
                 f"vision_layer_feature type: {type(vision_feature_layer)}"
@@ -312,30 +312,17 @@ class LlavaNextForConditionalGeneration(nn.Module, SupportsMultiModal,
 
         raise AssertionError("This line should be unreachable.")
 
-    def _select_image_features(self, image_features: torch.Tensor, *,
-                               strategy: str) -> torch.Tensor:
-        # Copied from https://github.com/huggingface/transformers/blob/39c3c0a72af6fbda5614dde02ff236069bb79827/src/transformers/models/llava/modeling_llava.py#L421  # noqa
-        if strategy == "default":
-            return image_features[:, 1:]
-        elif strategy == "full":
-            return image_features
-
-        raise ValueError(f"Unexpected select feature strategy: {strategy}")
-
     def _image_pixels_to_features(
         self,
         vision_tower: Union[CLIPVisionModel, SiglipVisionModel],
         pixel_values: torch.Tensor,
     ) -> torch.Tensor:
-
         # NOTE: we skip the step to select the vision feature layer since
         # this is already done inside the vision tower
-        image_features = vision_tower(
-            pixel_values, feature_sample_layers=self.feature_sample_layers)
-
-        return self._select_image_features(
-            image_features,
-            strategy=self.config.vision_feature_select_strategy,
+        return vision_tower(
+            pixel_values,
+            select_layers=self.select_layers,
+            feature_select_strategy=self.config.vision_feature_select_strategy,
         )
 
     # Based on: https://github.com/haotian-liu/LLaVA/blob/main/llava/model/llava_arch.py