Fix conversion wrapper module registration and docs (#1380)

docs/api/vector/wrappers.md

@@ -74,6 +74,7 @@ title: Vector Wrappers
 ## Implemented Data Conversion wrappers
 
 ```{eval-rst}
+.. autoclass:: gymnasium.wrappers.vector.ArrayConversion
 .. autoclass:: gymnasium.wrappers.vector.JaxToNumpy
 .. autoclass:: gymnasium.wrappers.vector.JaxToTorch
 .. autoclass:: gymnasium.wrappers.vector.NumpyToTorch

docs/api/wrappers/table.md

@@ -12,6 +12,8 @@ wrapper in the page on the wrapper type
 
     * - Name
       - Description
+    * - :class:`ArrayConversion`
+      - Wraps an environment based on any Array API compatible framework, e.g. ``numpy``, ``torch``, ``jax.numpy``, such that it can be interacted with any other Array API compatible framework.
     * - :class:`AtariPreprocessing`
       - Implements the common preprocessing techniques for Atari environments (excluding frame stacking).
     * - :class:`Autoreset`
@@ -34,8 +36,6 @@ wrapper in the page on the wrapper type
       - Converts an image observation computed by ``reset`` and ``step`` from RGB to Grayscale.
     * - :class:`HumanRendering`
       - Allows human like rendering for environments that support "rgb_array" rendering.
-    * - :class:`ArrayConversion`
-      - Wraps an environment based on any Array API compatible framework, e.g. torch, jax, numpy, such that it can be interacted with any other Array API compatible framework.
     * - :class:`JaxToNumpy`
       - Wraps a Jax-based environment such that it can be interacted with NumPy arrays.
     * - :class:`JaxToTorch`

gymnasium/wrappers/__init__.py

@@ -134,6 +134,7 @@ __all__ = [
     "RecordVideo",
     "HumanRendering",
     # --- Conversion ---
+    "ArrayConversion",
     "JaxToNumpy",
     "JaxToTorch",
     "NumpyToTorch",
@@ -143,6 +144,7 @@ __all__ = [
 #   to avoid `import jax` or `import torch` on `import gymnasium`.
 _wrapper_to_class = {
     # data converters
+    "ArrayConversion": "array_conversion",
     "JaxToNumpy": "jax_to_numpy",
     "JaxToTorch": "jax_to_torch",
     "NumpyToTorch": "numpy_to_torch",

gymnasium/wrappers/array_conversion.py

@@ -137,9 +137,12 @@ def _none_array_conversion(
 
 
 class ArrayConversion(gym.Wrapper, gym.utils.RecordConstructorArgs):
-    """Wraps an Array API compatible environment so that it can be interacted with a specific Array API framework.
+    """Wraps an Array API compatible environment so that it can be interacted with with another Array API framework.
+
+    Popular Array API frameworks include ``numpy``, ``torch``, ``jax.numpy``, ``cupy`` etc. With this wrapper, you can convert outputs from your environment to
+    any of these frameworks. Conversely, actions are automatically mapped back to the environment framework, if possible without moving the
+    data or device transfers.
 
-    Actions must be provided as Array API compatible arrays and observations will be returned as Arrays of the specified xp module.
     A vector version of the wrapper exists, :class:`gymnasium.wrappers.vector.ArrayConversion`.
 
     Example:

gymnasium/wrappers/vector/__init__.py

@@ -67,6 +67,7 @@ __all__ = [
     # "RecordVideo",
     "HumanRendering",
     # --- Conversion ---
+    "ArrayConversion",
     "JaxToNumpy",
     "JaxToTorch",
     "NumpyToTorch",
@@ -77,6 +78,7 @@ __all__ = [
 #   to avoid `import jax` or `import torch` on `import gymnasium`.
 _wrapper_to_class = {
     # data converters
+    "ArrayConversion": "array_conversion",
     "JaxToNumpy": "jax_to_numpy",
     "JaxToTorch": "jax_to_torch",
     "NumpyToTorch": "numpy_to_torch",

gymnasium/wrappers/vector/array_conversion.py

@@ -22,11 +22,12 @@ __all__ = ["ArrayConversion"]
 class ArrayConversion(VectorWrapper, gym.utils.RecordConstructorArgs):
     """Wraps a vector environment returning Array API compatible arrays so that it can be interacted with through a specific framework.
 
-    Notes:
-        A vectorized version of ``gymnasium.wrappers.ArrayConversion``
+    Popular Array API frameworks include ``numpy``, ``torch``, ``jax.numpy``, ``cupy`` etc. With this wrapper, you can convert outputs from your environment to
+    any of these frameworks. Conversely, actions are automatically mapped back to the environment framework, if possible without moving the
+    data or device transfers.
 
-    Actions must be provided as Array API compatible arrays and observations, rewards, terminations and truncations will be returned in the desired framework.
-    xp here is a module that is compatible with the Array API standard, e.g. ``numpy``, ``jax`` etc.
+    Notes:
+        A vectorized version of :class:`gymnasium.wrappers.ArrayConversion`
 
     Example:
         >>> import gymnasium as gym                                         # doctest: +SKIP

gymnasium/wrappers/vector/jax_to_numpy.py

@@ -17,7 +17,7 @@ class JaxToNumpy(ArrayConversion):
     """Wraps a jax vector environment so that it can be interacted with through numpy arrays.
 
     Notes:
-        A vectorized version of ``gymnasium.wrappers.JaxToNumpy``
+        A vectorized version of :class:`gymnasium.wrappers.JaxToNumpy`
 
     Actions must be provided as numpy arrays and observations, rewards, terminations and truncations will be returned as numpy arrays.
 

tests/wrappers/test_array_conversion.py

@@ -15,8 +15,8 @@ array_api_extra = pytest.importorskip("array_api_extra")
 
 from array_api_compat import array_namespace, is_array_api_obj  # noqa: E402
 
+from gymnasium.wrappers import ArrayConversion  # noqa: E402
 from gymnasium.wrappers.array_conversion import (  # noqa: E402
-    ArrayConversion,
     array_conversion,
     module_namespace,
 )

tests/wrappers/vector/test_array_conversion.py

@@ -14,10 +14,10 @@ array_api_compat = pytest.importorskip("array_api_compat")
 from array_api_compat import array_namespace  # noqa: E402
 
 from gymnasium.wrappers.array_conversion import module_namespace  # noqa: E402
-from gymnasium.wrappers.vector.array_conversion import ArrayConversion  # noqa: E402
-from gymnasium.wrappers.vector.jax_to_numpy import JaxToNumpy  # noqa: E402
-from gymnasium.wrappers.vector.jax_to_torch import JaxToTorch  # noqa: E402
-from gymnasium.wrappers.vector.numpy_to_torch import NumpyToTorch  # noqa: E402
+from gymnasium.wrappers.vector import ArrayConversion  # noqa: E402
+from gymnasium.wrappers.vector import JaxToNumpy  # noqa: E402
+from gymnasium.wrappers.vector import JaxToTorch  # noqa: E402
+from gymnasium.wrappers.vector import NumpyToTorch  # noqa: E402
 
 
 # Define available modules