diff --git a/dizoo/mujoco/envs/mujoco_wrappers.py b/dizoo/mujoco/envs/mujoco_wrappers.py
index 0a8b41939c01c925f6917d386d6f32fb230785ea..fea4825512040d5863db756c78ee6b19213f0adc 100644
--- a/dizoo/mujoco/envs/mujoco_wrappers.py
+++ b/dizoo/mujoco/envs/mujoco_wrappers.py
@@ -1,10 +1,12 @@
+from typing import Dict
 import gym
 import numpy as np
 
 from ding.envs import ObsNormEnv, RewardNormEnv
 
 
-def wrap_mujoco(env_id, norm_obs=True, norm_reward=True, only_info=False) -> gym.Env:
+def wrap_mujoco(env_id, norm_obs: Dict=dict(use_norm=False, ), 
+                norm_reward: Dict=dict(use_norm=False, ), only_info=False) -> gym.Env:
     r"""
     Overview:
         Wrap Mujoco Env to preprocess env step's return info, e.g. observation normalization, reward normalization, etc.
@@ -28,5 +30,5 @@ def wrap_mujoco(env_id, norm_obs=True, norm_reward=True, only_info=False) -> gym
         if norm_obs is not None and norm_obs.use_norm:
             wrapper_info = ObsNormEnv.__name__ + '\n'
         if norm_reward is not None and norm_reward.use_norm:
-            wrapper_info = RewardNormEnv.__name__ + '\n'
+            wrapper_info += RewardNormEnv.__name__ + '\n'
         return wrapper_info