Tiny refactor DefaultModelLoader.Source (#5482)

python/sglang/srt/model_executor/model_runner.py

@@ -515,13 +515,7 @@ class ModelRunner:
 
         def get_weight_iter(config):
             iter = loader._get_weights_iterator(
-                DefaultModelLoader.Source(
-                    config.model_path,
-                    revision=config.revision,
-                    fall_back_to_pt=getattr(
-                        self.model, "fall_back_to_pt_during_load", True
-                    ),
-                )
+                DefaultModelLoader.Source.init_new(config, model)
             )
             return iter
 

python/sglang/srt/model_loader/loader.py

@@ -197,6 +197,15 @@ class DefaultModelLoader(BaseModelLoader):
         fall_back_to_pt: bool = True
         """Whether .pt weights can be used."""
 
+        @classmethod
+        def init_new(cls, model_config: ModelConfig, model):
+            return cls(
+                model_config.model_path,
+                model_config.revision,
+                prefix="",
+                fall_back_to_pt=getattr(model, "fall_back_to_pt_during_load", True),
+            )
+
     def __init__(self, load_config: LoadConfig):
         super().__init__(load_config)
         if load_config.model_loader_extra_config:
@@ -341,12 +350,7 @@ class DefaultModelLoader(BaseModelLoader):
         model: nn.Module,
     ) -> Generator[Tuple[str, torch.Tensor], None, None]:
 
-        primary_weights = DefaultModelLoader.Source(
-            model_config.model_path,
-            model_config.revision,
-            prefix="",
-            fall_back_to_pt=getattr(model, "fall_back_to_pt_during_load", True),
-        )
+        primary_weights = DefaultModelLoader.Source.init_new(model_config, model)
         yield from self._get_weights_iterator(primary_weights)
 
         secondary_weights = cast(