format

Author: lxd-cumt

flagscale/train/peft/lora.py

@@ -70,12 +70,9 @@ def transform(self, m: nn.Module, name=None, prefix=None):
         if (ans := match_module(m, name, prefix, self.target_modules)) is not None:
             (match, full_name) = ans
 
-            (
-                input_is_parallel,
-                in_features,
-                out_features,
-                base_linear_is_parallel,
-            ) = get_adapter_attributes_from_linear(m)
+            (input_is_parallel, in_features, out_features, base_linear_is_parallel) = (
+                get_adapter_attributes_from_linear(m)
+            )
 
             adapter = ParallelLinearAdapter(
                 in_features=in_features,

flagscale/train/peft/utils.py

@@ -99,12 +99,7 @@ def get_adapter_attributes_from_linear(m: nn.Module):
     else:
         raise NotImplementedError(f"Layer type is unrecognized for LoRA: {type(m)}")
 
-    return (
-        input_is_parallel,
-        in_features,
-        out_features,
-        base_linear_is_parallel,
-    )
+    return (input_is_parallel, in_features, out_features, base_linear_is_parallel)
 
 
 def is_expert_linear(fqn):