diff --git a/examples/getting_started/tf/src/cifar10_tf_fl_alpha_split_scaffold.py b/examples/getting_started/tf/src/cifar10_tf_fl_alpha_split_scaffold.py
index 24fba56990..f1eb461373 100644
--- a/examples/getting_started/tf/src/cifar10_tf_fl_alpha_split_scaffold.py
+++ b/examples/getting_started/tf/src/cifar10_tf_fl_alpha_split_scaffold.py
@@ -24,9 +24,9 @@
 # (1) import nvflare client API
 import nvflare.client as flare
 from nvflare.app_common.app_constant import AlgorithmConstants
+from nvflare.app_opt.tf.fedprox_loss import TFFedProxLoss
 from nvflare.app_opt.tf.scaffold import ScaffoldCallback, TFScaffoldHelper, get_lr_values
 from nvflare.client.tracking import SummaryWriter
-from nvflare.app_opt.tf.fedprox_loss import TFFedProxLoss
 
 PATH = "./tf_model.weights.h5"
 
@@ -199,14 +199,13 @@ def main():
             model.get_layer(k).set_weights(v)
 
         if args.fedprox_mu > 0:
-    
+
             local_model_weights = model.trainable_variables
             global_model_weights = copy.deepcopy(model.trainable_variables)
             model.loss = TFFedProxLoss(local_model_weights, global_model_weights, args.fedprox_mu, loss)
         elif args.fedprox_mu < 0.0:
 
             raise ValueError("mu should be no less than 0.0")
-    
 
         # (step 4) load regularization parameters from scaffold
         global_ctrl_weights = input_model.meta.get(AlgorithmConstants.SCAFFOLD_CTRL_GLOBAL)
diff --git a/examples/getting_started/tf/tf_fl_script_executor_cifar10.py b/examples/getting_started/tf/tf_fl_script_executor_cifar10.py
index 6037bf0d69..4f2d294f03 100644
--- a/examples/getting_started/tf/tf_fl_script_executor_cifar10.py
+++ b/examples/getting_started/tf/tf_fl_script_executor_cifar10.py
@@ -34,8 +34,6 @@
 FEDPROX_ALGO = "fedprox"
 
 
-
-
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument(
diff --git a/nvflare/app_opt/tf/fedopt_ctl.py b/nvflare/app_opt/tf/fedopt_ctl.py
index 42814cf55a..0ec0d2420b 100644
--- a/nvflare/app_opt/tf/fedopt_ctl.py
+++ b/nvflare/app_opt/tf/fedopt_ctl.py
@@ -72,10 +72,6 @@ def run(self):
         try:
             if "args" not in self.optimizer_args:
                 self.optimizer_args["args"] = {}
-<<<<<<< HEAD
-            # self.optimizer_args["args"]["params"] = self.keras_model.parameters()
-=======
->>>>>>> upstream/main
             self.optimizer = self.build_component(self.optimizer_args)
         except Exception as e:
             error_msg = f"Exception while constructing optimizer: {secure_format_exception(e)}"