From 2100f4cac29d90808ae7e6344e8587d9e9774984 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Wed, 23 Jul 2025 14:37:30 +0800
Subject: [PATCH] linting

---
 comfy/weight_adapter/loha.py |  4 ++--
 comfy/weight_adapter/lokr.py | 10 ++++------
 comfy/weight_adapter/oft.py  |  3 +--
 3 files changed, 7 insertions(+), 10 deletions(-)

diff --git a/comfy/weight_adapter/loha.py b/comfy/weight_adapter/loha.py
index 2a09a63d9..55c97a3af 100644
--- a/comfy/weight_adapter/loha.py
+++ b/comfy/weight_adapter/loha.py
@@ -78,7 +78,7 @@ class LohaDiff(WeightAdapterTrainBase):
     def __init__(self, weights):
         super().__init__()
         # Unpack weights tuple from LoHaAdapter
-        w1a, w1b, alpha, w2a, w2b, t1, t2, dora_scale = weights
+        w1a, w1b, alpha, w2a, w2b, t1, t2, _ = weights
 
         # Create trainable parameters
         self.hada_w1_a = torch.nn.Parameter(w1a)
@@ -98,7 +98,7 @@ class LohaDiff(WeightAdapterTrainBase):
 
         # Store rank and non-trainable alpha
         self.rank = w1b.shape[0]
-        self.register_buffer("alpha", torch.tensor(alpha))
+        self.alpha = torch.nn.Parameter(torch.tensor(alpha), requires_grad=False)
 
     def __call__(self, w):
         org_dtype = w.dtype
diff --git a/comfy/weight_adapter/lokr.py b/comfy/weight_adapter/lokr.py
index d33077f27..49b0be55f 100644
--- a/comfy/weight_adapter/lokr.py
+++ b/comfy/weight_adapter/lokr.py
@@ -17,16 +17,16 @@ class LokrDiff(WeightAdapterTrainBase):
         (lokr_w1, lokr_w2, alpha, lokr_w1_a, lokr_w1_b, lokr_w2_a, lokr_w2_b, lokr_t2, dora_scale) = weights
         self.use_tucker = False
         if lokr_w1_a is not None:
-            out_dim_a, rank_a = lokr_w1_a.shape[0], lokr_w1_a.shape[1]
-            rank_a, in_dim_a = lokr_w1_b.shape[0], lokr_w1_b.shape[1]
+            _, rank_a = lokr_w1_a.shape[0], lokr_w1_a.shape[1]
+            rank_a, _ = lokr_w1_b.shape[0], lokr_w1_b.shape[1]
             self.lokr_w1_a = torch.nn.Parameter(lokr_w1_a)
             self.lokr_w1_b = torch.nn.Parameter(lokr_w1_b)
             self.w1_rebuild = True
             self.ranka = rank_a
 
         if lokr_w2_a is not None:
-            out_dim_b, rank_b = lokr_w2_a.shape[0], lokr_w2_a.shape[1]
-            rank_b, in_dim_b = lokr_w2_b.shape[0], lokr_w2_b.shape[1]
+            _, rank_b = lokr_w2_a.shape[0], lokr_w2_a.shape[1]
+            rank_b, _ = lokr_w2_b.shape[0], lokr_w2_b.shape[1]
             self.lokr_w2_a = torch.nn.Parameter(lokr_w2_a)
             self.lokr_w2_b = torch.nn.Parameter(lokr_w2_b)
             if lokr_t2 is not None:
@@ -36,12 +36,10 @@ class LokrDiff(WeightAdapterTrainBase):
             self.rankb = rank_b
 
         if lokr_w1 is not None:
-            out_dim_a, in_dim_a = lokr_w1.shape[0], lokr_w1.shape[1]
             self.lokr_w1 = torch.nn.Parameter(lokr_w1)
             self.w1_rebuild = False
 
         if lokr_w2 is not None:
-            out_dim_b, in_dim_b = lokr_w2.shape[0], lokr_w2.shape[1]
             self.lokr_w2 = torch.nn.Parameter(lokr_w2)
             self.w2_rebuild = False
 
diff --git a/comfy/weight_adapter/oft.py b/comfy/weight_adapter/oft.py
index 1a59727d2..9d4982083 100644
--- a/comfy/weight_adapter/oft.py
+++ b/comfy/weight_adapter/oft.py
@@ -10,7 +10,7 @@ class OFTDiff(WeightAdapterTrainBase):
     def __init__(self, weights):
         super().__init__()
         # Unpack weights tuple from LoHaAdapter
-        blocks, rescale, alpha, dora_scale = weights
+        blocks, rescale, alpha, _ = weights
 
         # Create trainable parameters
         self.oft_blocks = torch.nn.Parameter(blocks)
@@ -124,7 +124,6 @@ class OFTAdapter(WeightAdapterBase):
         rescale = v[1]
         alpha = v[2]
         if alpha is None:
-            print("Alpha is None")
             alpha = 0
         dora_scale = v[3]