diff --git a/federatedscope/contrib/trainer/local_entropy.py b/federatedscope/contrib/trainer/local_entropy.py
index eec78d438..8eaa911c0 100644
--- a/federatedscope/contrib/trainer/local_entropy.py
+++ b/federatedscope/contrib/trainer/local_entropy.py
@@ -83,7 +83,7 @@ def run_epoch(self, optimizer, criterion, current_global_model, mu):
             outputs = self.model(inputs)
             ce_loss = criterion(outputs, targets)
             loss = ce_loss + self._thermal * prox_term(self.model.state_dict(),
-                                                 current_global_model)
+                                                       current_global_model)
             loss.backward()
             optimizer.step()
 
diff --git a/federatedscope/core/aggregators/fedopt_aggregator.py b/federatedscope/core/aggregators/fedopt_aggregator.py
index ae09d87be..29a9b3e99 100644
--- a/federatedscope/core/aggregators/fedopt_aggregator.py
+++ b/federatedscope/core/aggregators/fedopt_aggregator.py
@@ -16,7 +16,9 @@ def __init__(self, config, model, device='cpu'):
         if config.fedopt.annealing:
             self._annealing = True
             # TODO: generic scheduler construction
-            self.scheduler = torch.optim.lr_scheduler.StepLR(self.optimizer, step_size=4000, gamma=0.2)
+            self.scheduler = torch.optim.lr_scheduler.StepLR(self.optimizer,
+                                                             step_size=4000,
+                                                             gamma=0.2)
         else:
             self._annealing = False