diff --git a/envs/wrappers.py b/envs/wrappers.py
index 80f4f19..af52602 100644
--- a/envs/wrappers.py
+++ b/envs/wrappers.py
@@ -4,18 +4,15 @@ import numpy as np
 import uuid
 
 
-class TimeLimit:
+class TimeLimit(gym.Wrapper):
     def __init__(self, env, duration):
-        self._env = env
+        super().__init__(env)
         self._duration = duration
         self._step = None
 
-    def __getattr__(self, name):
-        return getattr(self._env, name)
-
     def step(self, action):
         assert self._step is not None, "Must reset environment."
-        obs, reward, done, info = self._env.step(action)
+        obs, reward, done, info = self.env.step(action)
         self._step += 1
         if self._step >= self._duration:
             done = True
@@ -26,22 +23,18 @@ class TimeLimit:
 
     def reset(self):
         self._step = 0
-        return self._env.reset()
+        return self.env.reset()
 
 
-class NormalizeActions:
+class NormalizeActions(gym.Wrapper):
     def __init__(self, env):
-        self._env = env
+        super().__init__(env)
         self._mask = np.logical_and(
             np.isfinite(env.action_space.low), np.isfinite(env.action_space.high)
         )
         self._low = np.where(self._mask, env.action_space.low, -1)
         self._high = np.where(self._mask, env.action_space.high, 1)
 
-    def __getattr__(self, name):
-        return getattr(self._env, name)
-
-    @property
     def action_space(self):
         low = np.where(self._mask, -np.ones_like(self._low), self._low)
         high = np.where(self._mask, np.ones_like(self._low), self._high)
@@ -50,21 +43,18 @@ class NormalizeActions:
     def step(self, action):
         original = (action + 1) / 2 * (self._high - self._low) + self._low
         original = np.where(self._mask, original, action)
-        return self._env.step(original)
+        return self.env.step(original)
 
 
-class OneHotAction:
+class OneHotAction(gym.Wrapper):
     def __init__(self, env):
         assert isinstance(env.action_space, gym.spaces.Discrete)
-        self._env = env
+        super().__init__(env)
         self._random = np.random.RandomState()
 
-    def __getattr__(self, name):
-        return getattr(self._env, name)
 
-    @property
     def action_space(self):
-        shape = (self._env.action_space.n,)
+        shape = (self.env.action_space.n,)
         space = gym.spaces.Box(low=0, high=1, shape=shape, dtype=np.float32)
         space.sample = self._sample_action
         space.discrete = True
@@ -76,29 +66,26 @@ class OneHotAction:
         reference[index] = 1
         if not np.allclose(reference, action):
             raise ValueError(f"Invalid one-hot action:\n{action}")
-        return self._env.step(index)
+        return self.env.step(index)
 
     def reset(self):
-        return self._env.reset()
+        return self.env.reset()
 
     def _sample_action(self):
-        actions = self._env.action_space.n
+        actions = self.env.action_space.n
         index = self._random.randint(0, actions)
         reference = np.zeros(actions, dtype=np.float32)
         reference[index] = 1.0
         return reference
 
 
-class RewardObs:
+class RewardObs(gym.Wrapper):
     def __init__(self, env):
-        self._env = env
+        super().__init__(env)
 
-    def __getattr__(self, name):
-        return getattr(self._env, name)
 
-    @property
     def observation_space(self):
-        spaces = self._env.observation_space.spaces
+        spaces = self.env.observation_space.spaces
         if "reward" not in spaces:
             spaces["reward"] = gym.spaces.Box(
                 -np.inf, np.inf, shape=(1,), dtype=np.float32
@@ -106,39 +93,35 @@ class RewardObs:
         return gym.spaces.Dict(spaces)
 
     def step(self, action):
-        obs, reward, done, info = self._env.step(action)
+        obs, reward, done, info = self.env.step(action)
         if "reward" not in obs:
             obs["reward"] = reward
         return obs, reward, done, info
 
     def reset(self):
-        obs = self._env.reset()
+        obs = self.env.reset()
         if "reward" not in obs:
             obs["reward"] = 0.0
         return obs
 
 
-class SelectAction:
+class SelectAction(gym.Wrapper):
     def __init__(self, env, key):
-        self._env = env
+        super().__init__(env)
         self._key = key
 
-    def __getattr__(self, name):
-        return getattr(self._env, name)
 
     def step(self, action):
-        return self._env.step(action[self._key])
+        return self.env.step(action[self._key])
 
-class UUID:
+class UUID(gym.Wrapper):
     def __init__(self, env):
-        self._env = env
+        super().__init__(env)
         timestamp = datetime.datetime.now().strftime("%Y%m%dT%H%M%S")
         self.id = f"{timestamp}-{str(uuid.uuid4().hex)}"
 
-    def __getattr__(self, name):
-        return getattr(self._env, name)
 
     def reset(self):
         timestamp = datetime.datetime.now().strftime("%Y%m%dT%H%M%S")
         self.id = f"{timestamp}-{str(uuid.uuid4().hex)}"
-        return self._env.reset()
+        return self.env.reset()