[diffusion] chore: clean excessive document (#16986)

python/sglang/multimodal_gen/runtime/loader/component_loader.py

@@ -254,9 +254,6 @@ class ComponentLoader(ABC):
         Args:
             module_type: Type of module (e.g., "vae", "text_encoder", "transformer", "scheduler")
             transformers_or_diffusers: Whether the module is from transformers or diffusers
-
-        Returns:
-            A component loader for the specified module type
         """
         # Map of module types to their loader classes and expected library
         module_type = _normalize_module_type(module_type)
@@ -803,8 +800,6 @@ class PipelineComponentLoader:
             component_model_path: Path to the component model
             transformers_or_diffusers: Whether the module is from transformers or diffusers
 
-        Returns:
-            The loaded module
         """
 
         # Get the appropriate loader for this module type

python/sglang/multimodal_gen/runtime/loader/fsdp_load.py

@@ -181,8 +181,6 @@ def shard_model(
             which modules to shard with FSDP.
         pin_cpu_memory (bool): If set to True, FSDP will pin the CPU memory of the offloaded parameters.
 
-    Raises:
-        ValueError: If no layer modules were sharded, indicating that no shard_condition was triggered.
     """
     if fsdp_shard_conditions is None or len(fsdp_shard_conditions) == 0:
         logger.warning(
@@ -244,8 +242,6 @@ def load_model_from_full_model_state_dict(
             * **missing_keys** is a list of str containing the missing keys
             * **unexpected_keys** is a list of str containing the unexpected keys
 
-    Raises:
-        NotImplementedError: If got FSDP with more than 1D.
     """
     meta_sd = model.state_dict()
     param_dict = dict(model.named_parameters())