Change end-of-episode in CarRacing to termination as opposed to truncation

docs/introduction/basic_usage.md

@@ -127,7 +127,7 @@ In order to wrap an environment, you must first initialize a base environment. T
 ```python
 >>> import gymnasium as gym
 >>> from gymnasium.wrappers import FlattenObservation
->>> env = gym.make("CarRacing-v2")
+>>> env = gym.make("CarRacing-v3")
 >>> env.observation_space.shape
 (96, 96, 3)
 >>> wrapped_env = FlattenObservation(env)
@@ -156,7 +156,7 @@ If you have a wrapped environment, and you want to get the unwrapped environment
 
 ```python
 >>> wrapped_env
-<FlattenObservation<TimeLimit<OrderEnforcing<PassiveEnvChecker<CarRacing<CarRacing-v2>>>>>>
+<FlattenObservation<TimeLimit<OrderEnforcing<PassiveEnvChecker<CarRacing<CarRacing-v3>>>>>>
 >>> wrapped_env.unwrapped
 <gymnasium.envs.box2d.car_racing.CarRacing object at 0x7f04efcb8850>
 ```

gymnasium/envs/__init__.py

@@ -115,7 +115,7 @@
 )
 
 register(
-    id="CarRacing-v2",
+    id="CarRacing-v3",
     entry_point="gymnasium.envs.box2d.car_racing:CarRacing",
     max_episode_steps=1000,
     reward_threshold=900,

gymnasium/envs/box2d/car_racing.py

@@ -153,9 +153,9 @@ class CarRacing(gym.Env, EzPickle):
 
     ```python
     >>> import gymnasium as gym
-    >>> env = gym.make("CarRacing-v2", render_mode="rgb_array", lap_complete_percent=0.95, domain_randomize=False, continuous=False)
+    >>> env = gym.make("CarRacing-v3", render_mode="rgb_array", lap_complete_percent=0.95, domain_randomize=False, continuous=False)
     >>> env
-    <TimeLimit<OrderEnforcing<PassiveEnvChecker<CarRacing<CarRacing-v2>>>>>
+    <TimeLimit<OrderEnforcing<PassiveEnvChecker<CarRacing<CarRacing-v3>>>>>
 
     ```
 
@@ -176,7 +176,7 @@ class CarRacing(gym.Env, EzPickle):
 
     ```python
     >>> import gymnasium as gym
-    >>> env = gym.make("CarRacing-v2", domain_randomize=True)
+    >>> env = gym.make("CarRacing-v3", domain_randomize=True)
 
     # normal reset, this changes the colour scheme by default
     >>> obs, _ = env.reset()
@@ -190,6 +190,7 @@ class CarRacing(gym.Env, EzPickle):
     ```
 
     ## Version History
+    - v2: Change truncation to termination when finishing the lap (1.0.0)
     - v1: Change track completion logic and add domain randomization (0.24.0)
     - v0: Original version
 
@@ -564,6 +565,7 @@ def step(self, action: Union[np.ndarray, int]):
         step_reward = 0
         terminated = False
         truncated = False
+        info = {}
         if action is not None:  # First step without action, called from reset()
             self.reward -= 0.1
             # We actually don't want to count fuel spent, we want car to be faster.
@@ -572,18 +574,18 @@ def step(self, action: Union[np.ndarray, int]):
             step_reward = self.reward - self.prev_reward
             self.prev_reward = self.reward
             if self.tile_visited_count == len(self.track) or self.new_lap:
-                # Truncation due to finishing lap
-                # This should not be treated as a failure
-                # but like a timeout
-                truncated = True
+                # Termination due to finishing lap
+                terminated = True
+                info["lap_finished"] = True
             x, y = self.car.hull.position
             if abs(x) > PLAYFIELD or abs(y) > PLAYFIELD:
                 terminated = True
+                info["lap_finished"] = False
                 step_reward = -100
 
         if self.render_mode == "human":
             self.render()
-        return self.state, step_reward, terminated, truncated, {}
+        return self.state, step_reward, terminated, truncated, info
 
     def render(self):
         if self.render_mode is None:

gymnasium/utils/play.py

@@ -212,7 +212,7 @@ def play(
         >>> import gymnasium as gym
         >>> import numpy as np
         >>> from gymnasium.utils.play import play
-        >>> play(gym.make("CarRacing-v2", render_mode="rgb_array"), # doctest: +SKIP
+        >>> play(gym.make("CarRacing-v3", render_mode="rgb_array"),  # doctest: +SKIP
         ...     keys_to_action={
         ...         "w": np.array([0, 0.7, 0], dtype=np.float32),
         ...         "a": np.array([-1, 0, 0], dtype=np.float32),

gymnasium/wrappers/stateful_observation.py

@@ -309,7 +309,7 @@ class FrameStackObservation(
     Example:
         >>> import gymnasium as gym
         >>> from gymnasium.wrappers import FrameStackObservation
-        >>> env = gym.make("CarRacing-v2")
+        >>> env = gym.make("CarRacing-v3")
         >>> env = FrameStackObservation(env, stack_size=4)
         >>> env.observation_space
         Box(0, 255, (4, 96, 96, 3), uint8)

gymnasium/wrappers/transform_observation.py

@@ -225,7 +225,7 @@ class FlattenObservation(
     Example:
         >>> import gymnasium as gym
         >>> from gymnasium.wrappers import FlattenObservation
-        >>> env = gym.make("CarRacing-v2")
+        >>> env = gym.make("CarRacing-v3")
         >>> env.observation_space.shape
         (96, 96, 3)
         >>> env = FlattenObservation(env)
@@ -267,7 +267,7 @@ class GrayscaleObservation(
     Example:
         >>> import gymnasium as gym
         >>> from gymnasium.wrappers import GrayscaleObservation
-        >>> env = gym.make("CarRacing-v2")
+        >>> env = gym.make("CarRacing-v3")
         >>> env.observation_space.shape
         (96, 96, 3)
         >>> grayscale_env = GrayscaleObservation(env)
@@ -345,7 +345,7 @@ class ResizeObservation(
     Example:
         >>> import gymnasium as gym
         >>> from gymnasium.wrappers import ResizeObservation
-        >>> env = gym.make("CarRacing-v2")
+        >>> env = gym.make("CarRacing-v3")
         >>> env.observation_space.shape
         (96, 96, 3)
         >>> resized_env = ResizeObservation(env, (32, 32))
@@ -416,7 +416,7 @@ class ReshapeObservation(
     Example:
         >>> import gymnasium as gym
         >>> from gymnasium.wrappers import ReshapeObservation
-        >>> env = gym.make("CarRacing-v2")
+        >>> env = gym.make("CarRacing-v3")
         >>> env.observation_space.shape
         (96, 96, 3)
         >>> reshape_env = ReshapeObservation(env, (24, 4, 96, 1, 3))

gymnasium/wrappers/vector/vectorize_observation.py

@@ -213,7 +213,7 @@ class FlattenObservation(VectorizeTransformObservation):
 
     Example:
         >>> import gymnasium as gym
-        >>> envs = gym.make_vec("CarRacing-v2", num_envs=3, vectorization_mode="sync")
+        >>> envs = gym.make_vec("CarRacing-v3", num_envs=3, vectorization_mode="sync")
         >>> obs, info = envs.reset(seed=123)
         >>> obs.shape
         (3, 96, 96, 3)
@@ -238,7 +238,7 @@ class GrayscaleObservation(VectorizeTransformObservation):
 
     Example:
         >>> import gymnasium as gym
-        >>> envs = gym.make_vec("CarRacing-v2", num_envs=3, vectorization_mode="sync")
+        >>> envs = gym.make_vec("CarRacing-v3", num_envs=3, vectorization_mode="sync")
         >>> obs, info = envs.reset(seed=123)
         >>> obs.shape
         (3, 96, 96, 3)
@@ -266,7 +266,7 @@ class ResizeObservation(VectorizeTransformObservation):
 
     Example:
         >>> import gymnasium as gym
-        >>> envs = gym.make_vec("CarRacing-v2", num_envs=3, vectorization_mode="sync")
+        >>> envs = gym.make_vec("CarRacing-v3", num_envs=3, vectorization_mode="sync")
         >>> obs, info = envs.reset(seed=123)
         >>> obs.shape
         (3, 96, 96, 3)
@@ -292,7 +292,7 @@ class ReshapeObservation(VectorizeTransformObservation):
 
     Example:
         >>> import gymnasium as gym
-        >>> envs = gym.make_vec("CarRacing-v2", num_envs=3, vectorization_mode="sync")
+        >>> envs = gym.make_vec("CarRacing-v3", num_envs=3, vectorization_mode="sync")
         >>> obs, info = envs.reset(seed=123)
         >>> obs.shape
         (3, 96, 96, 3)

tests/envs/registration/test_make.py

@@ -242,7 +242,7 @@ def test_make_human_rendering(register_rendering_testing_envs):
         TypeError,
         match=re.escape("got an unexpected keyword argument 'render'"),
     ):
-        gym.make("CarRacing-v2", render="human")
+        gym.make("CarRacing-v3", render="human")
 
     # This test checks that a user can create an environment without the metadata including the render mode
     with pytest.warns(

tests/envs/test_env_implementation.py

@@ -54,7 +54,7 @@ def test_carracing_domain_randomize():
     CarRacing DomainRandomize should have different colours at every reset.
     However, it should have same colours when `options={"randomize": False}` is given to reset.
     """
-    env: CarRacing = gym.make("CarRacing-v2", domain_randomize=True).unwrapped
+    env: CarRacing = gym.make("CarRacing-v3", domain_randomize=True).unwrapped
 
     road_color = env.road_color
     bg_color = env.bg_color

tests/wrappers/test_normalize_observation.py

@@ -68,7 +68,7 @@ def test_update_running_mean_property():
 
 def test_normalize_obs_with_vector():
     def thunk():
-        env = gym.make("CarRacing-v2")
+        env = gym.make("CarRacing-v3")
         env = gym.wrappers.GrayscaleObservation(env)
         env = gym.wrappers.NormalizeObservation(env)
         return env

tests/wrappers/test_resize_observation.py

@@ -47,7 +47,7 @@ def test_resize_observation_wrapper(env):
 
 @pytest.mark.parametrize("shape", ((10, 10), (20, 20), (60, 60), (100, 100)))
 def test_resize_shapes(shape: tuple[int, int]):
-    env = ResizeObservation(gym.make("CarRacing-v2"), shape)
+    env = ResizeObservation(gym.make("CarRacing-v3"), shape)
     assert env.observation_space == Box(
         low=0, high=255, shape=shape + (3,), dtype=np.uint8
     )
@@ -59,7 +59,7 @@ def test_resize_shapes(shape: tuple[int, int]):
 
 
 def test_invalid_input():
-    env = gym.make("CarRacing-v2")
+    env = gym.make("CarRacing-v3")
 
     with pytest.raises(AssertionError):
         ResizeObservation(env, ())

tests/wrappers/vector/test_vector_wrappers.py

@@ -42,9 +42,9 @@ def custom_environments():
     (
         ("CustomDictEnv-v0", "FilterObservation", {"filter_keys": ["a"]}),
         ("CartPole-v1", "FlattenObservation", {}),
-        ("CarRacing-v2", "GrayscaleObservation", {}),
-        ("CarRacing-v2", "ResizeObservation", {"shape": (35, 45)}),
-        ("CarRacing-v2", "ReshapeObservation", {"shape": (96, 48, 6)}),
+        ("CarRacing-v3", "GrayscaleObservation", {}),
+        ("CarRacing-v3", "ResizeObservation", {"shape": (35, 45)}),
+        ("CarRacing-v3", "ReshapeObservation", {"shape": (96, 48, 6)}),
         (
             "CartPole-v1",
             "RescaleObservation",
@@ -53,7 +53,7 @@ def custom_environments():
                 "max_obs": np.array([1, np.inf, 1, np.inf]),
             },
         ),
-        ("CarRacing-v2", "DtypeObservation", {"dtype": np.int32}),
+        ("CarRacing-v3", "DtypeObservation", {"dtype": np.int32}),
         # ("CartPole-v1", "RenderObservation", {}),  # not implemented
         # ("CartPole-v1", "TimeAwareObservation", {}),  # not implemented
         # ("CartPole-v1", "FrameStackObservation", {}),  # not implemented