diff --git a/demo/distillation/train.py b/demo/distillation/train.py
index 7f389168440a59f0872d44ab6e62f262e373f6f0..e17678a70c73cfd1af746118ae7d0685317e96aa 100644
--- a/demo/distillation/train.py
+++ b/demo/distillation/train.py
@@ -140,41 +140,38 @@ def compress(args):
     # define teacher program
     teacher_program = fluid.Program()
     t_startup = fluid.Program()
-    teacher_scope = fluid.Scope()
-    with fluid.scope_guard(teacher_scope):
-        with fluid.program_guard(teacher_program, t_startup):
-            with fluid.unique_name.guard():
-                image = fluid.layers.data(
-                    name='image', shape=image_shape, dtype='float32')
-                predict = teacher_model.net(image, class_dim=class_dim)
-
-            #print("="*50+"teacher_model_params"+"="*50)
-            #for v in teacher_program.list_vars():
-            #    print(v.name, v.shape)
-
-        exe.run(t_startup)
-        assert args.teacher_pretrained_model and os.path.exists(
-            args.teacher_pretrained_model
-        ), "teacher_pretrained_model should be set when teacher_model is not None."
-
-        def if_exist(var):
-            return os.path.exists(
-                os.path.join(args.teacher_pretrained_model, var.name)
-            ) and var.name != 'conv1_weights' and var.name != 'fc_0.w_0' and var.name != 'fc_0.b_0'
-
-        fluid.io.load_vars(
-            exe,
-            args.teacher_pretrained_model,
-            main_program=teacher_program,
-            predicate=if_exist)
+    with fluid.program_guard(teacher_program, t_startup):
+        with fluid.unique_name.guard():
+            image = fluid.layers.data(
+                name='image', shape=image_shape, dtype='float32')
+            predict = teacher_model.net(image, class_dim=class_dim)
+
+        #print("="*50+"teacher_model_params"+"="*50)
+        #for v in teacher_program.list_vars():
+        #    print(v.name, v.shape)
+
+    exe.run(t_startup)
+    assert args.teacher_pretrained_model and os.path.exists(
+        args.teacher_pretrained_model
+    ), "teacher_pretrained_model should be set when teacher_model is not None."
+
+    def if_exist(var):
+        return os.path.exists(
+            os.path.join(args.teacher_pretrained_model, var.name)
+        ) and var.name != 'conv1_weights' and var.name != 'fc_0.w_0' and var.name != 'fc_0.b_0'
+
+    fluid.io.load_vars(
+        exe,
+        args.teacher_pretrained_model,
+        main_program=teacher_program,
+        predicate=if_exist)
 
     data_name_map = {'image': 'image'}
     main = merge(
         teacher_program,
         student_program,
         data_name_map,
-        place,
-        teacher_scope=teacher_scope)
+        place)
 
     #print("="*50+"teacher_vars"+"="*50)
     #for v in teacher_program.list_vars():
diff --git a/paddleslim/dist/single_distiller.py b/paddleslim/dist/single_distiller.py
index 70b843c90fec6bdf906045dbac3097f8dfba3ff1..8f5dcaeb14a0f6a7aadd5c99de7bc3c144f21414 100644
--- a/paddleslim/dist/single_distiller.py
+++ b/paddleslim/dist/single_distiller.py
@@ -20,8 +20,7 @@ def merge(teacher_program,
           student_program,
           data_name_map,
           place,
-          teacher_scope=fluid.global_scope(),
-          student_scope=fluid.global_scope(),
+          scope=fluid.global_scope(),
           name_prefix='teacher_'):
     """
     Merge teacher program into student program and add a uniform prefix to the
@@ -33,8 +32,7 @@ def merge(teacher_program,
                             and the student var name
         place(fluid.CPUPlace()|fluid.CUDAPlace(N)): This parameter represents
                                                     paddle run on which device.
-        student_scope(Scope): The input student scope 
-        teacher_scope(Scope): The input teacher scope
+        scope(Scope): The input scope
         name_prefix(str): Name prefix added for all vars of the teacher program.
     Return(Program): Merged program.
     """
@@ -50,9 +48,9 @@ def merge(teacher_program,
                 new_name = name_prefix + teacher_var.name
             if not skip_rename:
                 # scope var rename
-                scope_var = teacher_scope.var(teacher_var.name).get_tensor()
-                renamed_scope_var = teacher_scope.var(new_name).get_tensor()
-                renamed_scope_var.set(np.array(scope_var), place)
+                old_var = scope.var(teacher_var.name).get_tensor()
+                renamed_var = scope.var(new_name).get_tensor()
+                renamed_var.set(np.array(old_var), place)
     
                 # program var rename
                 renamed_var = teacher_program.global_block()._rename_var(
@@ -60,11 +58,6 @@ def merge(teacher_program,
 
     for teacher_var in teacher_program.list_vars():
         if teacher_var.name != 'fetch' and teacher_var.name != 'feed':
-            # student scope add var
-            student_scope_var = student_scope.var(teacher_var.name).get_tensor()
-            teacher_scope_var = teacher_scope.var(teacher_var.name).get_tensor()
-            student_scope_var.set(np.array(teacher_scope_var), place)
-
             # student program add var
             new_var = student_program.global_block()._clone_variable(
                 teacher_var, force_persistable=False)