Change end-of-episode truncation to termination in Car Racing. Bump e…

…nv version

gymnasium/envs/__init__.py

@@ -111,7 +111,7 @@
 )
 
 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

@@ -182,6 +182,7 @@ 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
 
@@ -563,10 +564,8 @@ 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
             x, y = self.car.hull.position
             if abs(x) > PLAYFIELD or abs(y) > PLAYFIELD:
                 terminated = True

gymnasium/utils/play.py

@@ -209,7 +209,7 @@ def play(
 
     Example:
         >>> 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]),
         ...         "a": np.array([-1, 0, 0]),

gymnasium/wrappers/stateful_observation.py

@@ -308,7 +308,7 @@ 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, 4)
         >>> env.observation_space
         Box(0, 255, (4, 96, 96, 3), uint8)

gymnasium/wrappers/transform_observation.py

@@ -222,7 +222,7 @@ 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)
@@ -264,7 +264,7 @@ 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)
@@ -342,7 +342,7 @@ 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))
@@ -413,7 +413,7 @@ 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

@@ -212,7 +212,7 @@ 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)
@@ -237,7 +237,7 @@ 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)
@@ -265,7 +265,7 @@ 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)
@@ -291,7 +291,7 @@ 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

@@ -241,7 +241,7 @@ 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

@@ -23,7 +23,7 @@ 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_resize_observation.py

@@ -46,7 +46,7 @@ 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
     )
@@ -58,7 +58,7 @@ 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

@@ -41,9 +41,9 @@ 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", {"min_obs": 0, "max_obs": 1}),
         ("CartPole-v1", "DtypeObservation", {"dtype": np.int32}),
         # ("CartPole-v1", "RenderObservation", {}),  # not implemented