diff --git a/qlib/contrib/model/pytorch_gru.py b/qlib/contrib/model/pytorch_gru.py
index 282ce72dd..02664b6ac 100755
--- a/qlib/contrib/model/pytorch_gru.py
+++ b/qlib/contrib/model/pytorch_gru.py
@@ -146,7 +146,6 @@ class GRU(Model):
 
         raise ValueError("unknown metric `%s`" % self.metric)
 
-
     def train_epoch(self, x_train, y_train):
 
         x_train_values = x_train.values
diff --git a/qlib/contrib/model/pytorch_lstm.py b/qlib/contrib/model/pytorch_lstm.py
index 844a08a83..f8951509a 100755
--- a/qlib/contrib/model/pytorch_lstm.py
+++ b/qlib/contrib/model/pytorch_lstm.py
@@ -146,7 +146,6 @@ class LSTM(Model):
 
         raise ValueError("unknown metric `%s`" % self.metric)
 
-
     def train_epoch(self, x_train, y_train):
 
         x_train_values = x_train.values
diff --git a/qlib/contrib/model/pytorch_sfm.py b/qlib/contrib/model/pytorch_sfm.py
index f8a96bc84..1d27f3927 100644
--- a/qlib/contrib/model/pytorch_sfm.py
+++ b/qlib/contrib/model/pytorch_sfm.py
@@ -100,9 +100,7 @@ class SFM_Model(nn.Module):
             x_c = torch.matmul(x * B_W[0], self.W_c) + self.b_c
             x_o = torch.matmul(x * B_W[0], self.W_o) + self.b_o
 
-            i = self.inner_activation(
-                x_i + torch.matmul(h_tm1 * B_U[0], self.U_i)
-            )  
+            i = self.inner_activation(x_i + torch.matmul(h_tm1 * B_U[0], self.U_i))
             ste = self.inner_activation(x_ste + torch.matmul(h_tm1 * B_U[0], self.U_ste))
             fre = self.inner_activation(x_fre + torch.matmul(h_tm1 * B_U[0], self.U_fre))