Add generic conversion wrapper between Array API compatible frameworks

.github/workflows/docs-build-dev.yml

@@ -19,7 +19,7 @@ jobs:
 
       - uses: actions/setup-python@v5
         with:
-            python-version: '3.9'
+            python-version: '3.10'
 
       - name: Install dependencies
         run: pip install -r docs/requirements.txt

.github/workflows/docs-build-release.yml

@@ -19,7 +19,7 @@ jobs:
 
       - uses: actions/setup-python@v5
         with:
-            python-version: '3.9'
+            python-version: '3.10'
 
       - name: Install dependencies
         run: pip install -r docs/requirements.txt

.github/workflows/docs-manual-build.yml

@@ -33,7 +33,7 @@ jobs:
 
       - uses: actions/setup-python@v5
         with:
-            python-version: '3.9'
+            python-version: '3.10'
 
       - name: Install dependencies
         run: pip install -r docs/requirements.txt

.github/workflows/run-pytest.yml

@@ -10,8 +10,8 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ['3.9', '3.10', '3.11', '3.12']
-        numpy-version: ['>=1.21,<2.0', '>=2.0']
+        python-version: ['3.10', '3.11', '3.12']
+        numpy-version: ['>=1.21,<2.0', '>=2.1']
     steps:
       - uses: actions/checkout@v4
       - run: |
@@ -22,7 +22,6 @@ jobs:
       - name: Run tests
         run: docker run gymnasium-all-docker pytest tests/*
       - name: Run doctests
-        if: ${{ matrix.python-version != '3.8' }}
         run: docker run gymnasium-all-docker pytest --doctest-modules gymnasium/
 
   build-necessary:

README.md

@@ -31,7 +31,7 @@ To install the base Gymnasium library, use `pip install gymnasium`
 
 This does not include dependencies for all families of environments (there's a massive number, and some can be problematic to install on certain systems). You can install these dependencies for one family like `pip install "gymnasium[atari]"` or use `pip install "gymnasium[all]"` to install all dependencies.
 
-We support and test for Python 3.8, 3.9, 3.10, 3.11 and 3.12 on Linux and macOS. We will accept PRs related to Windows, but do not officially support it.
+We support and test for Python 3.10, 3.11 and 3.12 on Linux and macOS. We will accept PRs related to Windows, but do not officially support it.
 
 ## API
 

docs/api/wrappers/misc_wrappers.md

@@ -27,6 +27,7 @@ title: Misc Wrappers
 ## Data Conversion Wrappers
 
 ```{eval-rst}
+.. autoclass:: gymnasium.wrappers.ToArray
 .. autoclass:: gymnasium.wrappers.JaxToNumpy
 .. autoclass:: gymnasium.wrappers.JaxToTorch
 .. autoclass:: gymnasium.wrappers.NumpyToTorch

docs/api/wrappers/table.md

@@ -34,6 +34,8 @@ 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:`ToArray`
+      - 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/jax_to_numpy.py

@@ -3,19 +3,16 @@
 from __future__ import annotations
 
 import functools
-import numbers
-from collections import abc
-from typing import Any, Iterable, Mapping, SupportsFloat
 
 import numpy as np
 
 import gymnasium as gym
-from gymnasium.core import ActType, ObsType, RenderFrame, WrapperActType, WrapperObsType
+from gymnasium.core import ActType, ObsType
 from gymnasium.error import DependencyNotInstalled
+from gymnasium.wrappers.to_array import ToArray, to_xp
 
 
 try:
-    import jax
     import jax.numpy as jnp
 except ImportError:
     raise DependencyNotInstalled(
@@ -24,104 +21,13 @@
 
 __all__ = ["JaxToNumpy", "jax_to_numpy", "numpy_to_jax"]
 
-# The NoneType is not defined in Python 3.9. Remove when the minimal version is bumped to >=3.10
-_NoneType = type(None)
 
+jax_to_numpy = functools.partial(to_xp, xp=np)
 
-@functools.singledispatch
-def numpy_to_jax(value: Any) -> Any:
-    """Converts a value to a Jax Array."""
-    raise Exception(
-        f"No known conversion for Numpy type ({type(value)}) to Jax registered. Report as issue on github."
-    )
-
-
-@numpy_to_jax.register(numbers.Number)
-def _number_to_jax(
-    value: numbers.Number,
-) -> jax.Array:
-    """Converts a number (int, float, etc.) to a Jax Array."""
-    assert jnp is not None
-    return jnp.array(value)
-
-
-@numpy_to_jax.register(np.ndarray)
-def _numpy_array_to_jax(value: np.ndarray) -> jax.Array:
-    """Converts a NumPy Array to a Jax Array with the same dtype (excluding float64 without being enabled)."""
-    assert jnp is not None
-    return jnp.array(value, dtype=value.dtype)
-
-
-@numpy_to_jax.register(abc.Mapping)
-def _mapping_numpy_to_jax(value: Mapping[str, Any]) -> Mapping[str, Any]:
-    """Converts a dictionary of numpy arrays to a mapping of Jax Array."""
-    return type(value)(**{k: numpy_to_jax(v) for k, v in value.items()})
-
-
-@numpy_to_jax.register(abc.Iterable)
-def _iterable_numpy_to_jax(
-    value: Iterable[np.ndarray | Any],
-) -> Iterable[jax.Array | Any]:
-    """Converts an Iterable from Numpy Arrays to an iterable of Jax Array."""
-    if hasattr(value, "_make"):
-        # namedtuple - underline used to prevent potential name conflicts
-        # noinspection PyProtectedMember
-        return type(value)._make(numpy_to_jax(v) for v in value)
-    else:
-        return type(value)(numpy_to_jax(v) for v in value)
-
-
-@numpy_to_jax.register(_NoneType)
-def _none_numpy_to_jax(value: None) -> None:
-    """Passes through None values."""
-    return value
-
-
-@functools.singledispatch
-def jax_to_numpy(value: Any) -> Any:
-    """Converts a value to a numpy array."""
-    raise Exception(
-        f"No known conversion for Jax type ({type(value)}) to NumPy registered. Report as issue on github."
-    )
-
-
-@jax_to_numpy.register(jax.Array)
-def _devicearray_jax_to_numpy(value: jax.Array) -> np.ndarray:
-    """Converts a Jax Array to a numpy array."""
-    return np.array(value)
-
+numpy_to_jax = functools.partial(to_xp, xp=jnp)
 
-@jax_to_numpy.register(abc.Mapping)
-def _mapping_jax_to_numpy(
-    value: Mapping[str, jax.Array | Any],
-) -> Mapping[str, np.ndarray | Any]:
-    """Converts a dictionary of Jax Array to a mapping of numpy arrays."""
-    return type(value)(**{k: jax_to_numpy(v) for k, v in value.items()})
 
-
-@jax_to_numpy.register(abc.Iterable)
-def _iterable_jax_to_numpy(
-    value: Iterable[np.ndarray | Any],
-) -> Iterable[jax.Array | Any]:
-    """Converts an Iterable from Numpy arrays to an iterable of Jax Array."""
-    if hasattr(value, "_make"):
-        # namedtuple - underline used to prevent potential name conflicts
-        # noinspection PyProtectedMember
-        return type(value)._make(jax_to_numpy(v) for v in value)
-    else:
-        return type(value)(jax_to_numpy(v) for v in value)
-
-
-@jax_to_numpy.register(_NoneType)
-def _none_jax_to_numpy(value: None) -> None:
-    """Passes through None values."""
-    return value
-
-
-class JaxToNumpy(
-    gym.Wrapper[WrapperObsType, WrapperActType, ObsType, ActType],
-    gym.utils.RecordConstructorArgs,
-):
+class JaxToNumpy(ToArray):
     """Wraps a Jax-based environment such that it can be interacted with NumPy arrays.
 
     Actions must be provided as numpy arrays and observations will be returned as numpy arrays.
@@ -163,48 +69,4 @@ def __init__(self, env: gym.Env[ObsType, ActType]):
             raise DependencyNotInstalled(
                 'Jax is not installed, run `pip install "gymnasium[jax]"`'
             )
-        gym.utils.RecordConstructorArgs.__init__(self)
-        gym.Wrapper.__init__(self, env)
-
-    def step(
-        self, action: WrapperActType
-    ) -> tuple[WrapperObsType, SupportsFloat, bool, bool, dict]:
-        """Transforms the action to a jax array .
-
-        Args:
-            action: the action to perform as a numpy array
-
-        Returns:
-            A tuple containing numpy versions of the next observation, reward, termination, truncation, and extra info.
-        """
-        jax_action = numpy_to_jax(action)
-        obs, reward, terminated, truncated, info = self.env.step(jax_action)
-
-        return (
-            jax_to_numpy(obs),
-            float(reward),
-            bool(terminated),
-            bool(truncated),
-            jax_to_numpy(info),
-        )
-
-    def reset(
-        self, *, seed: int | None = None, options: dict[str, Any] | None = None
-    ) -> tuple[WrapperObsType, dict[str, Any]]:
-        """Resets the environment returning numpy-based observation and info.
-
-        Args:
-            seed: The seed for resetting the environment
-            options: The options for resetting the environment, these are converted to jax arrays.
-
-        Returns:
-            Numpy-based observations and info
-        """
-        if options:
-            options = numpy_to_jax(options)
-
-        return jax_to_numpy(self.env.reset(seed=seed, options=options))
-
-    def render(self) -> RenderFrame | list[RenderFrame] | None:
-        """Returns the rendered frames as a numpy array."""
-        return jax_to_numpy(self.env.render())
+        super().__init__(env=env, env_xp=jnp, target_xp=np)