Update vector wrapper docs and add Env generic to doc (#847)

docs/api/vector.md

@@ -2,7 +2,7 @@
 title: Vector
 ---
 
-# Vector environments
+# Vectorize
 
 ```{toctree}
 :hidden:
@@ -19,10 +19,10 @@ vector/utils
 ```
 
 ### Methods
-
 ```{eval-rst}
-.. automethod:: gymnasium.vector.VectorEnv.reset
 .. automethod:: gymnasium.vector.VectorEnv.step
+.. automethod:: gymnasium.vector.VectorEnv.reset
+.. automethod:: gymnasium.vector.VectorEnv.render
 .. automethod:: gymnasium.vector.VectorEnv.close
 ```
 
@@ -47,11 +47,19 @@ vector/utils
 
 .. autoattribute:: gymnasium.vector.VectorEnv.single_observation_space
 
-    The observation space of an environment copy.
+    The observation space of a sub-environment.
 
 .. autoattribute:: gymnasium.vector.VectorEnv.spec
 
     The ``EnvSpec`` of the environment normally set during :py:meth:`gymnasium.make_vec`
+
+.. autoattribute:: gymnasium.vector.VectorEnv.render_mode
+
+    The render mode of the environment which should follow similar specifications to `Env.render_mode`.
+
+.. autoattribute:: gymnasium.vector.VectorEnv.closed
+
+    If the vector environment has been closed already.
 ```
 
 ### Additional Methods

docs/api/vector/wrappers.md

@@ -2,19 +2,19 @@
 title: Vector Wrappers
 ---
 
-# Vector Wrappers
+# Wrappers
 
 ```{eval-rst}
 .. autoclass:: gymnasium.vector.VectorWrapper
 
     .. automethod:: gymnasium.vector.VectorWrapper.step
     .. automethod:: gymnasium.vector.VectorWrapper.reset
+    .. automethod:: gymnasium.vector.VectorWrapper.render
     .. automethod:: gymnasium.vector.VectorWrapper.close
 
 .. autoclass:: gymnasium.vector.VectorObservationWrapper
 
-    .. automethod:: gymnasium.vector.VectorObservationWrapper.vector_observation
+    .. automethod:: gymnasium.vector.VectorObservationWrapper.observations
-    .. automethod:: gymnasium.vector.VectorObservationWrapper.single_observation
 
 .. autoclass:: gymnasium.vector.VectorActionWrapper
 
@@ -24,3 +24,57 @@ title: Vector Wrappers
 
     .. automethod:: gymnasium.vector.VectorRewardWrapper.rewards
 ```
+
+## Vector Only wrappers
+
+```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.DictInfoToList
+
+.. autoclass:: gymnasium.wrappers.vector.VectorizeTransformObservation
+.. autoclass:: gymnasium.wrappers.vector.VectorizeTransformAction
+.. autoclass:: gymnasium.wrappers.vector.VectorizeTransformReward
+```
+
+## Vectorized Common wrappers
+
+```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.RecordEpisodeStatistics
+```
+
+## Implemented Observation wrappers
+
+```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.TransformObservation
+.. autoclass:: gymnasium.wrappers.vector.FilterObservation
+.. autoclass:: gymnasium.wrappers.vector.FlattenObservation
+.. autoclass:: gymnasium.wrappers.vector.GrayscaleObservation
+.. autoclass:: gymnasium.wrappers.vector.ResizeObservation
+.. autoclass:: gymnasium.wrappers.vector.ReshapeObservation
+.. autoclass:: gymnasium.wrappers.vector.RescaleObservation
+.. autoclass:: gymnasium.wrappers.vector.DtypeObservation
+.. autoclass:: gymnasium.wrappers.vector.NormalizeObservation
+```
+
+## Implemented Action wrappers
+
+```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.TransformAction
+.. autoclass:: gymnasium.wrappers.vector.ClipAction
+.. autoclass:: gymnasium.wrappers.vector.RescaleAction
+```
+
+## Implemented Reward wrappers
+
+```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.TransformReward
+.. autoclass:: gymnasium.wrappers.vector.ClipReward
+.. autoclass:: gymnasium.wrappers.vector.NormalizeReward
+```
+
+## Implemented Data Conversion wrappers
+
+```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.JaxToNumpy
+.. autoclass:: gymnasium.wrappers.vector.JaxToTorch
+.. autoclass:: gymnasium.wrappers.vector.NumpyToTorch
+```

docs/api/wrappers/table.md

@@ -78,7 +78,6 @@ wrapper in the page on the wrapper type
       - Applies a function to the ``observation`` received from the environment's ``reset`` and ``step`` that is passed back to the user.
     * - :class:`TransformReward`
       - Applies a function to the ``reward`` received from the environment's ``step``.
-
 ```
 
 ## Vector only Wrappers

docs/api/wrappers/vector_wrappers.md

@@ -1,19 +0,0 @@
----
-title: Vector Wrappers
----
-
-# Vector wrappers
-
-## Vector only wrappers
-
-```{eval-rst}
-.. autoclass:: gymnasium.wrappers.vector.DictInfoToList
-```
-
-## Vectorize Transform Wrappers to Vector Wrappers
-
-```{eval-rst}
-.. autoclass:: gymnasium.wrappers.vector.VectorizeTransformObservation
-.. autoclass:: gymnasium.wrappers.vector.VectorizeTransformAction
-.. autoclass:: gymnasium.wrappers.vector.VectorizeTransformReward
-```

gymnasium/core.py

@@ -42,10 +42,16 @@ class Env(Generic[ObsType, ActType]):
     - :attr:`np_random` - The random number generator for the environment. This is automatically assigned during
       ``super().reset(seed=seed)`` and when assessing :attr:`np_random`.
 
-    .. seealso:: For modifying or extending environments use the :py:class:`gymnasium.Wrapper` class
+    .. seealso:: For modifying or extending environments use the :class:`gymnasium.Wrapper` class
 
     Note:
         To get reproducible sampling of actions, a seed can be set with ``env.action_space.seed(123)``.
+
+    Note:
+        For strict type checking (e.g., mypy or pyright), :class:`Env` is a generic class with two parameterized types: ``ObsType`` and ``ActType``.
+        The ``ObsType`` and ``ActType`` are the expected types of the observations and actions used in :meth:`reset` and :meth:`step`.
+        The environment's :attr:`observation_space` and :attr:`action_space` should have type ``Space[ObsType]`` and ``Space[ActType]``,
+        see a space's implementation to find its parameterized type.
     """
 
     # Set this in SOME subclasses
@@ -473,7 +479,11 @@ class ObservationWrapper(Wrapper[WrapperObsType, ActType, ObsType, ActType]):
     """
 
     def __init__(self, env: Env[ObsType, ActType]):
-        """Constructor for the observation wrapper."""
+        """Constructor for the observation wrapper.
+
+        Args:
+            env: Environment to be wrapped.
+        """
         Wrapper.__init__(self, env)
 
     def reset(
@@ -513,7 +523,11 @@ class RewardWrapper(Wrapper[ObsType, ActType, ObsType, ActType]):
     """
 
     def __init__(self, env: Env[ObsType, ActType]):
-        """Constructor for the Reward wrapper."""
+        """Constructor for the Reward wrapper.
+
+        Args:
+            env: Environment to be wrapped.
+        """
         Wrapper.__init__(self, env)
 
     def step(
@@ -536,20 +550,25 @@ class RewardWrapper(Wrapper[ObsType, ActType, ObsType, ActType]):
 
 
 class ActionWrapper(Wrapper[ObsType, WrapperActType, ObsType, ActType]):
-    """Superclass of wrappers that can modify the action before :meth:`env.step`.
+    """Superclass of wrappers that can modify the action before :meth:`step`.
 
     If you would like to apply a function to the action before passing it to the base environment,
     you can simply inherit from :class:`ActionWrapper` and overwrite the method :meth:`action` to implement
     that transformation. The transformation defined in that method must take values in the base environment’s
     action space. However, its domain might differ from the original action space.
-    In that case, you need to specify the new action space of the wrapper by setting :attr:`self.action_space` in
+    In that case, you need to specify the new action space of the wrapper by setting :attr:`action_space` in
     the :meth:`__init__` method of your wrapper.
 
-    Among others, Gymnasium provides the action wrappers :class:`ClipAction` and :class:`RescaleAction` for clipping and rescaling actions.
+    Among others, Gymnasium provides the action wrappers :class:`gymnasium.wrappers.ClipAction` and
+    :class:`gymnasium.wrappers.RescaleAction` for clipping and rescaling actions.
     """
 
     def __init__(self, env: Env[ObsType, ActType]):
-        """Constructor for the action wrapper."""
+        """Constructor for the action wrapper.
+
+        Args:
+            env: Environment to be wrapped.
+        """
         Wrapper.__init__(self, env)
 
     def step(
@@ -559,7 +578,7 @@ class ActionWrapper(Wrapper[ObsType, WrapperActType, ObsType, ActType]):
         return self.env.step(self.action(action))
 
     def action(self, action: WrapperActType) -> ActType:
-        """Returns a modified action before :meth:`env.step` is called.
+        """Returns a modified action before :meth:`step` is called.
 
         Args:
             action: The original :meth:`step` actions

gymnasium/envs/box2d/bipedal_walker.py

@@ -606,6 +606,7 @@ class BipedalWalker(gym.Env, EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return np.array(state, dtype=np.float32), reward, terminated, False, {}
 
     def render(self):

gymnasium/envs/box2d/lunar_lander.py

@@ -673,6 +673,7 @@ class LunarLander(gym.Env, EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return np.array(state, dtype=np.float32), reward, terminated, False, {}
 
     def render(self):

gymnasium/envs/classic_control/acrobot.py

@@ -225,7 +225,8 @@ class AcrobotEnv(Env):
 
         if self.render_mode == "human":
             self.render()
-        return (self._get_ob(), reward, terminated, False, {})
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
+        return self._get_ob(), reward, terminated, False, {}
 
     def _get_ob(self):
         s = self.state

gymnasium/envs/classic_control/cartpole.py

@@ -204,6 +204,7 @@ class CartPoleEnv(gym.Env[np.ndarray, Union[int, np.ndarray]]):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return np.array(self.state, dtype=np.float32), reward, terminated, False, {}
 
     def reset(

gymnasium/envs/classic_control/continuous_mountain_car.py

@@ -175,6 +175,7 @@ class Continuous_MountainCarEnv(gym.Env):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return self.state, reward, terminated, False, {}
 
     def reset(self, *, seed: Optional[int] = None, options: Optional[dict] = None):

gymnasium/envs/classic_control/mountain_car.py

@@ -146,6 +146,7 @@ class MountainCarEnv(gym.Env):
         self.state = (position, velocity)
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return np.array(self.state, dtype=np.float32), reward, terminated, False, {}
 
     def reset(

gymnasium/envs/classic_control/pendulum.py

@@ -141,6 +141,7 @@ class PendulumEnv(gym.Env):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return self._get_obs(), -costs, False, False, {}
 
     def reset(self, *, seed: Optional[int] = None, options: Optional[dict] = None):

gymnasium/envs/mujoco/ant.py

@@ -45,6 +45,7 @@ class AntEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/ant_v3.py

@@ -147,6 +147,7 @@ class AntEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_obs(self):

gymnasium/envs/mujoco/ant_v4.py

@@ -159,6 +159,7 @@ class AntEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_obs(self):

gymnasium/envs/mujoco/ant_v5.py

@@ -390,6 +390,7 @@ class AntEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_rew(self, x_velocity: float, action):

gymnasium/envs/mujoco/half_cheetah.py

@@ -35,6 +35,7 @@ class HalfCheetahEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/half_cheetah_v3.py

@@ -90,6 +90,7 @@ class HalfCheetahEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_obs(self):

gymnasium/envs/mujoco/half_cheetah_v4.py

@@ -93,6 +93,7 @@ class HalfCheetahEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_obs(self):

gymnasium/envs/mujoco/half_cheetah_v5.py

@@ -251,6 +251,7 @@ class HalfCheetahEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, False, False, info
 
     def _get_rew(self, x_velocity: float, action):

gymnasium/envs/mujoco/hopper.py

@@ -42,6 +42,7 @@ class HopperEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return ob, reward, terminated, False, {}
 
     def _get_obs(self):

gymnasium/envs/mujoco/hopper_v3.py

@@ -151,6 +151,7 @@ class HopperEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/hopper_v4.py

@@ -152,6 +152,7 @@ class HopperEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/hopper_v5.py

@@ -328,6 +328,7 @@ class HopperEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_rew(self, x_velocity: float, action):

gymnasium/envs/mujoco/humanoid.py

@@ -60,6 +60,7 @@ class HumanoidEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             self._get_obs(),
             reward,

gymnasium/envs/mujoco/humanoid_v3.py

@@ -174,6 +174,7 @@ class HumanoidEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/humanoid_v4.py

@@ -161,6 +161,7 @@ class HumanoidEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/humanoid_v5.py

@@ -513,6 +513,7 @@ class HumanoidEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_rew(self, x_velocity: float, action):

gymnasium/envs/mujoco/humanoidstandup.py

@@ -54,6 +54,7 @@ class HumanoidStandupEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             self._get_obs(),
             reward,

gymnasium/envs/mujoco/humanoidstandup_v4.py

@@ -63,6 +63,7 @@ class HumanoidStandupEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             self._get_obs(),
             reward,

gymnasium/envs/mujoco/humanoidstandup_v5.py

@@ -456,6 +456,7 @@ class HumanoidStandupEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return self._get_obs(), reward, False, False, info
 
     def _get_rew(self, pos_after: float, action):

gymnasium/envs/mujoco/inverted_double_pendulum.py

@@ -40,6 +40,7 @@ class InvertedDoublePendulumEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return ob, r, terminated, False, {}
 
     def _get_obs(self):

gymnasium/envs/mujoco/inverted_double_pendulum_v4.py

@@ -46,6 +46,7 @@ class InvertedDoublePendulumEnv(MujocoEnv, utils.EzPickle):
         terminated = bool(y <= 1)
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return ob, r, terminated, False, {}
 
     def _get_obs(self):

gymnasium/envs/mujoco/inverted_double_pendulum_v5.py

@@ -203,6 +203,7 @@ class InvertedDoublePendulumEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_rew(self, x, y, terminated):

gymnasium/envs/mujoco/inverted_pendulum.py

@@ -35,6 +35,7 @@ class InvertedPendulumEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return ob, reward, terminated, False, {}
 
     def reset_model(self):

gymnasium/envs/mujoco/inverted_pendulum_v4.py

@@ -40,6 +40,7 @@ class InvertedPendulumEnv(MujocoEnv, utils.EzPickle):
         terminated = bool(not np.isfinite(ob).all() or (np.abs(ob[1]) > 0.2))
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return ob, reward, terminated, False, {}
 
     def reset_model(self):

gymnasium/envs/mujoco/inverted_pendulum_v5.py

@@ -186,6 +186,7 @@ class InvertedPendulumEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/pusher.py

@@ -36,6 +36,7 @@ class PusherEnv(MuJocoPyEnv, utils.EzPickle):
             self.render()
 
         ob = self._get_obs()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/pusher_v4.py

@@ -47,6 +47,7 @@ class PusherEnv(MujocoEnv, utils.EzPickle):
             self.render()
 
         ob = self._get_obs()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/pusher_v5.py

@@ -226,9 +226,10 @@ class PusherEnv(MujocoEnv, utils.EzPickle):
         observation = self._get_obs()
         reward, reward_info = self._get_rew(action)
         info = reward_info
+
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, False, False, info
 
     def _get_rew(self, action):

gymnasium/envs/mujoco/reacher.py

@@ -33,6 +33,7 @@ class ReacherEnv(MuJocoPyEnv, utils.EzPickle):
             self.render()
 
         ob = self._get_obs()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/reacher_v4.py

@@ -41,6 +41,7 @@ class ReacherEnv(MujocoEnv, utils.EzPickle):
             self.render()
 
         ob = self._get_obs()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/reacher_v5.py

@@ -206,6 +206,7 @@ class ReacherEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, False, False, info
 
     def _get_rew(self, action):

gymnasium/envs/mujoco/swimmer.py

@@ -36,6 +36,7 @@ class SwimmerEnv(MuJocoPyEnv, utils.EzPickle):
         if self.render_mode == "human":
             self.render()
 
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return (
             ob,
             reward,

gymnasium/envs/mujoco/swimmer_v3.py

@@ -91,7 +91,7 @@ class SwimmerEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, False, False, info
 
     def _get_obs(self):

gymnasium/envs/mujoco/swimmer_v4.py

@@ -85,7 +85,7 @@ class SwimmerEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, False, False, info
 
     def _get_obs(self):

gymnasium/envs/mujoco/swimmer_v5.py

@@ -247,7 +247,7 @@ class SwimmerEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, False, False, info
 
     def _get_rew(self, x_velocity: float, action):

gymnasium/envs/mujoco/walker2d.py

@@ -36,7 +36,7 @@ class Walker2dEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return ob, reward, terminated, False, {}
 
     def _get_obs(self):

gymnasium/envs/mujoco/walker2d_v3.py

@@ -140,7 +140,7 @@ class Walker2dEnv(MuJocoPyEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/walker2d_v4.py

@@ -144,7 +144,7 @@ class Walker2dEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def reset_model(self):

gymnasium/envs/mujoco/walker2d_v5.py

@@ -322,7 +322,7 @@ class Walker2dEnv(MujocoEnv, utils.EzPickle):
 
         if self.render_mode == "human":
             self.render()
-
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return observation, reward, terminated, False, info
 
     def _get_rew(self, x_velocity: float, action):

gymnasium/envs/toy_text/blackjack.py

@@ -193,6 +193,7 @@ class BlackjackEnv(gym.Env):
 
         if self.render_mode == "human":
             self.render()
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
         return self._get_obs(), reward, terminated, False, {}
 
     def _get_obs(self):

gymnasium/envs/toy_text/cliffwalking.py

@@ -179,7 +179,8 @@ class CliffWalkingEnv(Env):
 
         if self.render_mode == "human":
             self.render()
-        return (int(s), r, t, False, {"prob": p})
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
+        return int(s), r, t, False, {"prob": p}
 
     def reset(self, *, seed: Optional[int] = None, options: Optional[dict] = None):
         super().reset(seed=seed)

gymnasium/envs/toy_text/frozen_lake.py

@@ -306,7 +306,8 @@ class FrozenLakeEnv(Env):
 
         if self.render_mode == "human":
             self.render()
-        return (int(s), r, t, False, {"prob": p})
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
+        return int(s), r, t, False, {"prob": p}
 
     def reset(
         self,

gymnasium/envs/toy_text/taxi.py

@@ -291,7 +291,8 @@ class TaxiEnv(Env):
 
         if self.render_mode == "human":
             self.render()
-        return (int(s), r, t, False, {"prob": p, "action_mask": self.action_mask(s)})
+        # truncation=False as the time limit is handled by the `TimeLimit` wrapper added during `make`
+        return int(s), r, t, False, {"prob": p, "action_mask": self.action_mask(s)}
 
     def reset(
         self,

gymnasium/vector/vector_env.py

@@ -445,7 +445,7 @@ class VectorObservationWrapper(VectorWrapper):
     ) -> tuple[ObsType, dict[str, Any]]:
         """Modifies the observation returned from the environment ``reset`` using the :meth:`observation`."""
         observations, infos = self.env.reset(seed=seed, options=options)
-        return self.observation(observations), infos
+        return self.observations(observations), infos
 
     def step(
         self, actions: ActType
@@ -453,18 +453,18 @@ class VectorObservationWrapper(VectorWrapper):
         """Modifies the observation returned from the environment ``step`` using the :meth:`observation`."""
         observations, rewards, terminations, truncations, infos = self.env.step(actions)
         return (
-            self.observation(observations),
+            self.observations(observations),
             rewards,
             terminations,
             truncations,
             infos,
         )
 
-    def observation(self, observation: ObsType) -> ObsType:
+    def observations(self, observations: ObsType) -> ObsType:
         """Defines the vector observation transformation.
 
         Args:
-            observation: A vector observation from the environment
+            observations: A vector observation from the environment
 
         Returns:
             the transformed observation

gymnasium/wrappers/common.py

@@ -462,7 +462,7 @@ class RecordEpisodeStatistics(
 
     Change logs:
      * v0.15.4 - Initially added
-     * v1.0.0 - Removed vector environment support for `wrappers.vector.RecordEpisodeStatistics` and add attribute ``time_queue``
+     * v1.0.0 - Removed vector environment support (see :class:`gymnasium.wrappers.vector.RecordEpisodeStatistics`) and add attribute ``time_queue``
     """
 
     def __init__(

gymnasium/wrappers/vector/stateful_observation.py

@@ -81,7 +81,7 @@ class NormalizeObservation(VectorObservationWrapper, gym.utils.RecordConstructor
         """Sets the property to freeze/continue the running mean calculation of the observation statistics."""
         self._update_running_mean = setting
 
-    def observation(self, observations: ObsType) -> ObsType:
+    def observations(self, observations: ObsType) -> ObsType:
         """Defines the vector observation normalization function.
 
         Args:

gymnasium/wrappers/vector/vectorize_observation.py

@@ -69,7 +69,7 @@ class TransformObservation(VectorObservationWrapper):
 
         self.func = func
 
-    def observation(self, observations: ObsType) -> ObsType:
+    def observations(self, observations: ObsType) -> ObsType:
         """Apply function to the vector observation."""
         return self.func(observations)
 
@@ -148,7 +148,7 @@ class VectorizeTransformObservation(VectorObservationWrapper):
         self.same_out = self.observation_space == self.env.observation_space
         self.out = create_empty_array(self.single_observation_space, self.num_envs)
 
-    def observation(self, observations: ObsType) -> ObsType:
+    def observations(self, observations: ObsType) -> ObsType:
         """Iterates over the vector observations applying the single-agent wrapper ``observation`` then concatenates the observations together again."""
         if self.same_out:
             return concatenate(