Add padding_type parameter to FrameSkipObservation and change default to "reset" to preserve backwards comp

gymnasium/wrappers/stateful_observation.py

@@ -299,42 +299,75 @@ class FrameStackObservation(
     is an array with shape [3], so if we stack 4 observations, the processed observation
     has shape [4, 3].
 
-    No vector version of the wrapper exists.
+    Users have options for the padded observation used:
 
-    Note:
-        - After :meth:`reset` is called, the frame buffer will be filled with the initial observation.
-          I.e. the observation returned by :meth:`reset` will consist of `num_stack` many identical frames.
+     * "reset" (default) - The reset value is repeated
+     * "zero" - A "zero"-like instance of the observation space
+     * custom - An instance of the observation space
+
+    No vector version of the wrapper exists.
 
     Example:
         >>> import gymnasium as gym
         >>> from gymnasium.wrappers import FrameStackObservation
         >>> env = gym.make("CarRacing-v2")
-        >>> env = FrameStackObservation(env, 4)
+        >>> env = FrameStackObservation(env, stack_size=4)
         >>> env.observation_space
         Box(0, 255, (4, 96, 96, 3), uint8)
         >>> obs, _ = env.reset()
         >>> obs.shape
         (4, 96, 96, 3)
 
+    Example with different padding observations:
+        >>> env = gym.make("CartPole-v1")
+        >>> env.reset(seed=123)
+        (array([ 0.01823519, -0.0446179 , -0.02796401, -0.03156282], dtype=float32), {})
+        >>> stacked_env = FrameStackObservation(env, 3)   # the default is padding_type="reset"
+        >>> stacked_env.reset(seed=123)
+        (array([[ 0.01823519, -0.0446179 , -0.02796401, -0.03156282],
+               [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282],
+               [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282]],
+              dtype=float32), {})
+
+
+        >>> stacked_env = FrameStackObservation(env, 3, padding_type="zero")
+        >>> stacked_env.reset(seed=123)
+        (array([[ 0.        ,  0.        ,  0.        ,  0.        ],
+               [ 0.        ,  0.        ,  0.        ,  0.        ],
+               [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282]],
+              dtype=float32), {})
+        >>> stacked_env = FrameStackObservation(env, 3, padding_type=np.array([1, -1, 0, 2], dtype=np.float32))
+        >>> stacked_env.reset(seed=123)
+        (array([[ 1.        , -1.        ,  0.        ,  2.        ],
+               [ 1.        , -1.        ,  0.        ,  2.        ],
+               [ 0.01823519, -0.0446179 , -0.02796401, -0.03156282]],
+              dtype=float32), {})
+
     Change logs:
      * v0.15.0 - Initially add as ``FrameStack`` with support for lz4
      * v1.0.0 - Rename to ``FrameStackObservation`` and remove lz4 and ``LazyFrame`` support
+      along with adding the ``padding_type`` parameter
     """
 
     def __init__(
         self,
         env: gym.Env[ObsType, ActType],
         stack_size: int,
         *,
-        zeros_obs: ObsType | None = None,
+        padding_type: str | ObsType = "reset",
     ):
         """Observation wrapper that stacks the observations in a rolling manner.
 
         Args:
             env: The environment to apply the wrapper
-            stack_size: The number of frames to stack with zero_obs being used originally.
-            zeros_obs: Keyword only parameter that allows a custom padding observation at :meth:`reset`
+            stack_size: The number of frames to stack.
+            padding_type: The padding type to use when stacking the observations, options: "reset", "zero", custom obs
         """
+        gym.utils.RecordConstructorArgs.__init__(
+            self, stack_size=stack_size, padding_type=padding_type
+        )
+        gym.Wrapper.__init__(self, env)
+
         if not np.issubdtype(type(stack_size), np.integer):
             raise TypeError(
                 f"The stack_size is expected to be an integer, actual type: {type(stack_size)}"
@@ -343,22 +376,31 @@ def __init__(
             raise ValueError(
                 f"The stack_size needs to be greater than one, actual value: {stack_size}"
             )
-
-        gym.utils.RecordConstructorArgs.__init__(self, stack_size=stack_size)
-        gym.Wrapper.__init__(self, env)
+        if isinstance(padding_type, str) and (
+            padding_type == "reset" or padding_type == "zero"
+        ):
+            self.padding_value: ObsType = create_zero_array(env.observation_space)
+        elif padding_type in env.observation_space:
+            self.padding_value = padding_type
+            padding_type = "_custom"
+        else:
+            if isinstance(padding_type, str):
+                raise ValueError(  # we are guessing that the user just entered the "reset" or "zero" wrong
+                    f"Unexpected `padding_type`, expected 'reset', 'zero' or a custom observation space, actual value: {padding_type!r}"
+                )
+            else:
+                raise ValueError(
+                    f"Unexpected `padding_type`, expected 'reset', 'zero' or a custom observation space, actual value: {padding_type!r} not an instance of env observation ({env.observation_space})"
+                )
 
         self.observation_space = batch_space(env.observation_space, n=stack_size)
         self.stack_size: Final[int] = stack_size
+        self.padding_type: Final[str] = padding_type
 
-        self.zero_obs: Final[ObsType] = (
-            zeros_obs if zeros_obs else create_zero_array(env.observation_space)
-        )
-        self._stacked_obs = deque(
-            [self.zero_obs for _ in range(self.stack_size)], maxlen=self.stack_size
-        )
-        self._stacked_array = create_empty_array(
-            env.observation_space, n=self.stack_size
+        self.obs_queue = deque(
+            [self.padding_value for _ in range(self.stack_size)], maxlen=self.stack_size
         )
+        self.stacked_obs = create_empty_array(env.observation_space, n=self.stack_size)
 
     def step(
         self, action: WrapperActType
@@ -371,13 +413,11 @@ def step(
         Returns:
             Stacked observations, reward, terminated, truncated, and info from the environment
         """
-        obs, reward, terminated, truncated, info = super().step(action)
-        self._stacked_obs.append(obs)
+        obs, reward, terminated, truncated, info = self.env.step(action)
+        self.obs_queue.append(obs)
 
         updated_obs = deepcopy(
-            concatenate(
-                self.env.observation_space, self._stacked_obs, self._stacked_array
-            )
+            concatenate(self.env.observation_space, self.obs_queue, self.stacked_obs)
         )
         return updated_obs, reward, terminated, truncated, info
 
@@ -393,15 +433,16 @@ def reset(
         Returns:
             The stacked observations and info
         """
-        obs, info = super().reset(seed=seed, options=options)
+        obs, info = self.env.reset(seed=seed, options=options)
+
+        if self.padding_type == "reset":
+            self.padding_value = obs
         for _ in range(self.stack_size - 1):
-            self._stacked_obs.append(self.zero_obs)
-        self._stacked_obs.append(obs)
+            self.obs_queue.append(self.padding_value)
+        self.obs_queue.append(obs)
 
         updated_obs = deepcopy(
-            concatenate(
-                self.env.observation_space, self._stacked_obs, self._stacked_array
-            )
+            concatenate(self.env.observation_space, self.obs_queue, self.stacked_obs)
         )
         return updated_obs, info
 

tests/wrappers/test_frame_stack_observation.py

@@ -1,32 +1,29 @@
 """Test suite for FrameStackObservation wrapper."""
 import re
 
+import numpy as np
 import pytest
 
 import gymnasium as gym
 from gymnasium.utils.env_checker import data_equivalence
 from gymnasium.vector.utils import iterate
 from gymnasium.wrappers import FrameStackObservation
-from gymnasium.wrappers.utils import create_zero_array
 from tests.wrappers.utils import SEED, TESTING_OBS_ENVS, TESTING_OBS_ENVS_IDS
 
 
 @pytest.mark.parametrize("env", TESTING_OBS_ENVS, ids=TESTING_OBS_ENVS_IDS)
-def test_env_obs(env, stack_size: int = 3):
-    """Test different environment observations for testing."""
+def test_different_obs_spaces(env, stack_size: int = 3):
+    """Test across a large number of observation spaces to check if the FrameStack wrapper ."""
     obs, _ = env.reset(seed=SEED)
     env.action_space.seed(SEED)
 
-    unstacked_obs = [
-        create_zero_array(env.observation_space) for _ in range(stack_size - 1)
-    ]
-    unstacked_obs.append(obs)
+    unstacked_obs = [obs for _ in range(stack_size)]
     for _ in range(stack_size * 2):
         obs, _, _, _, _ = env.step(env.action_space.sample())
         unstacked_obs.append(obs)
 
     env = FrameStackObservation(env, stack_size=stack_size)
-    env.action_space.seed(SEED)
+    env.action_space.seed(seed=SEED)
 
     obs, _ = env.reset(seed=SEED)
     stacked_obs = [obs]
@@ -50,25 +47,76 @@ def test_stack_size(stack_size: int):
     """Test different stack sizes for FrameStackObservation wrapper."""
     env = gym.make("CartPole-v1")
     env.action_space.seed(seed=SEED)
-    first_obs, _ = env.reset(seed=SEED)
-    second_obs, _, _, _, _ = env.step(env.action_space.sample())
 
-    zero_obs = create_zero_array(env.observation_space)
+    # Perform a series of actions and store the resulting observations
+    unstacked_obs = []
+    obs, _ = env.reset(seed=SEED)
+    unstacked_obs.append(obs)
+    first_obs = obs  # Store the first observation
+    for _ in range(5):
+        obs, _, _, _, _ = env.step(env.action_space.sample())
+        unstacked_obs.append(obs)
 
     env = FrameStackObservation(env, stack_size=stack_size)
-
     env.action_space.seed(seed=SEED)
+
+    # Perform the same series of actions and store the resulting stacked observations
+    stacked_obs = []
     obs, _ = env.reset(seed=SEED)
-    unstacked_obs = list(iterate(env.observation_space, obs))
-    assert len(unstacked_obs) == stack_size
-    assert data_equivalence(
-        [zero_obs for _ in range(stack_size - 1)], unstacked_obs[:-1]
-    )
-    assert data_equivalence(first_obs, unstacked_obs[-1])
+    stacked_obs.append(obs)
+    for _ in range(5):
+        obs, _, _, _, _ = env.step(env.action_space.sample())
+        stacked_obs.append(obs)
 
-    obs, _, _, _, _ = env.step(env.action_space.sample())
-    unstacked_obs = list(iterate(env.observation_space, obs))
-    assert data_equivalence(second_obs, unstacked_obs[-1])
+    # Check that the frames in each stacked observation match the corresponding observations
+    for i in range(len(stacked_obs)):
+        frames = list(iterate(env.observation_space, stacked_obs[i]))
+        for j in range(stack_size):
+            if i - j < 0:
+                # Use the first observation instead of a zero observation
+                expected_obs = first_obs
+            else:
+                expected_obs = unstacked_obs[i - j]
+            assert data_equivalence(expected_obs, frames[stack_size - 1 - j])
+
+
+def test_padding_type():
+    env = gym.make("CartPole-v1")
+    reset_obs, _ = env.reset(seed=123)
+    action = env.action_space.sample()
+    step_obs, _, _, _, _ = env.step(action)
+
+    stacked_env = FrameStackObservation(env, stack_size=3)  # default = "reset"
+    stacked_obs, _ = stacked_env.reset(seed=123)
+    assert np.all(np.stack([reset_obs, reset_obs, reset_obs]) == stacked_obs)
+    stacked_obs, _, _, _, _ = stacked_env.step(action)
+    assert np.all(np.stack([reset_obs, reset_obs, step_obs]) == stacked_obs)
+
+    stacked_env = FrameStackObservation(env, stack_size=3, padding_type="zero")
+    stacked_obs, _ = stacked_env.reset(seed=123)
+    assert np.all(np.stack([np.zeros(4), np.zeros(4), reset_obs]) == stacked_obs)
+    stacked_obs, _, _, _, _ = stacked_env.step(action)
+    assert np.all(np.stack([np.zeros(4), reset_obs, step_obs]) == stacked_obs)
+
+    stacked_env = FrameStackObservation(
+        env, stack_size=3, padding_type=np.array([1, -1, 0, 2], dtype=np.float32)
+    )
+    stacked_obs, _ = stacked_env.reset(seed=123)
+    assert np.all(
+        np.stack(
+            [
+                np.array([1, -1, 0, 2], dtype=np.float32),
+                np.array([1, -1, 0, 2], dtype=np.float32),
+                reset_obs,
+            ]
+        )
+        == stacked_obs
+    )
+    stacked_obs, _, _, _, _ = stacked_env.step(action)
+    assert np.all(
+        np.stack([np.array([1, -1, 0, 2], dtype=np.float32), reset_obs, step_obs])
+        == stacked_obs
+    )
 
 
 def test_stack_size_failures():
@@ -85,6 +133,24 @@ def test_stack_size_failures():
 
     with pytest.raises(
         ValueError,
-        match=re.escape("The stack_size needs to be greater than one, actual value: 0"),
+        match=re.escape("The stack_size needs to be greater than one, actual value: 1"),
+    ):
+        FrameStackObservation(env, stack_size=1)
+
+    with pytest.raises(
+        ValueError,
+        match=re.escape(
+            "Unexpected `padding_type`, expected 'reset', 'zero' or a custom observation space, actual value: 'unknown'"
+        ),
+    ):
+        FrameStackObservation(env, stack_size=3, padding_type="unknown")
+
+    invalid_padding = np.array([1, 2, 3, 4, 5])
+    assert invalid_padding not in env.observation_space
+    with pytest.raises(
+        ValueError,
+        match=re.escape(
+            "Unexpected `padding_type`, expected 'reset', 'zero' or a custom observation space, actual value: array([1, 2, 3, 4, 5])"
+        ),
     ):
-        FrameStackObservation(env, stack_size=0)
+        FrameStackObservation(env, stack_size=3, padding_type=invalid_padding)