Add dm-lab (no tests yet) and dm-control-multiagent

setup.py

@@ -36,7 +36,7 @@ def get_version():
     "gym": ["gym>=0.26"],
     "atari": ["ale-py~=0.8.0"],
     # "imageio" should be "gymnasium[mujoco]>=0.26" but there are install conflicts
-    "dm-control": ["dm-control>=1.0.8", "imageio"],
+    "dm-control": ["dm-control>=1.0.8", "imageio", "h5py>=3.7.0"],
     "openspiel": ["open_spiel>=1.2", "pettingzoo>=1.22"],
 }
 extras["all"] = list({lib for libs in extras.values() for lib in libs})

shimmy/__init__.py

@@ -1,19 +1,29 @@
 """API for converting popular non-gymnasium environments to a gymnasium compatible environment."""
 
-__version__ = "0.1.0"
+__version__ = "0.2.0"
 
 
 try:
-    from shimmy.dm_control_compatibility import DmControlCompatibility
+    from shimmy.dm_control_compatibility import DmControlCompatibilityV0
 except ImportError:
     pass
 
 try:
-    from shimmy.openspiel_wrapper import OpenspielWrapperV0
+    from shimmy.dm_control_multiagent_compatibility import (
+        DmControlMultiAgentCompatibilityV0,
+    )
 except ImportError:
     pass
 
-from shimmy.openai_gym_compatibility import GymV22Compatibility, GymV26Compatibility
+try:
+    from shimmy.openspiel_compatibility import OpenspielCompatibilityV0
+except ImportError:
+    pass
+
+try:
+    from shimmy.dm_lab_compatibility import DmLabCompatibilityV0
+except ImportError:
+    pass
 
 __all__ = [
     "DmControlCompatibility",

shimmy/dm_control_compatibility.py

@@ -17,7 +17,7 @@
 from gymnasium.core import ObsType
 from gymnasium.envs.mujoco.mujoco_rendering import Viewer
 
-from shimmy.utils.dm_env import dm_obs2gym_obs, dm_spec2gym_space
+from shimmy.utils.dm_env import dm_control_step2gym_step, dm_spec2gym_space
 
 
 class EnvType(Enum):
@@ -27,7 +27,7 @@ class EnvType(Enum):
     RL_CONTROL = 1
 
 
-class DmControlCompatibility(gymnasium.Env[ObsType, np.ndarray]):
+class DmControlCompatibilityV0(gymnasium.Env[ObsType, np.ndarray]):
     """A compatibility wrapper that converts a dm-control environment into a gymnasium environment.
 
     Dm-control actually has two Environments classes, `dm_control.composer.Environment` and
@@ -81,36 +81,18 @@ def reset(
             self.np_random = np.random.RandomState(seed=seed)
 
         timestep = self._env.reset()
-        obs = dm_obs2gym_obs(timestep.observation)
-        info = {
-            "timestep.discount": timestep.discount,
-            "timestep.step_type": timestep.step_type,
-        }
+
+        obs, reward, terminated, truncated, info = dm_control_step2gym_step(timestep)
+
         return obs, info  # pyright: ignore[reportGeneralTypeIssues]
 
     def step(
         self, action: np.ndarray
     ) -> tuple[ObsType, float, bool, bool, dict[str, Any]]:
         """Steps through the dm-control environment."""
-        # Step through the dm-control environment
         timestep = self._env.step(action)
 
-        # open up the timestep and process reward and observation
-        obs = dm_obs2gym_obs(timestep.observation)
-        reward = timestep.reward or 0
-
-        # set terminated and truncated
-        terminated, truncated = False, False
-        if timestep.last():
-            if timestep.discount == 0:
-                truncated = True
-            else:
-                terminated = True
-
-        info = {
-            "timestep.discount": timestep.discount,
-            "timestep.step_type": timestep.step_type,
-        }
+        obs, reward, terminated, truncated, info = dm_control_step2gym_step(timestep)
 
         if self.render_mode == "human":
             self.viewer.render()

shimmy/dm_control_multiagent_compatibility.py

@@ -0,0 +1,167 @@
+"""Wrapper to convert a dm_env multiagent environment into a pettingzoo compatible environment."""
+from __future__ import annotations
+
+import functools
+from itertools import repeat
+from typing import Any
+
+import dm_control.composer
+import dm_env
+import gymnasium
+from gymnasium.envs.mujoco.mujoco_rendering import Viewer
+from pettingzoo import ParallelEnv
+
+from shimmy.utils.dm_env import dm_obs2gym_obs, dm_spec2gym_space
+
+
+def _unravel_ma_timestep(
+    timestep: dm_env.TimeStep, agents: list[str]
+) -> tuple[
+    dict[str, Any],
+    dict[str, float],
+    dict[str, bool],
+    dict[str, bool],
+    dict[str, Any],
+]:
+    """Opens up the timestep to return obs, reward, terminated, truncated, info."""
+    # set terminated and truncated
+    term, trunc = False, False
+    if timestep.last():
+        if timestep.discount == 0:
+            trunc = True
+        else:
+            term = True
+
+    # expand the observations
+    list_observations = [dm_obs2gym_obs(obs) for obs in timestep.observation]
+    observations: dict[str, Any] = dict(zip(agents, list_observations))
+
+    # sometimes deepmind decides not to reward people
+    rewards: dict[str, float] = dict(zip(agents, repeat(0.0)))
+    if timestep.reward:
+        rewards = dict(zip(agents, timestep.reward))
+
+    # expand everything else
+    terminations: dict[str, bool] = dict(zip(agents, repeat(term)))
+    truncations: dict[str, bool] = dict(zip(agents, repeat(trunc)))
+
+    # duplicate infos
+    info = {
+        "timestep.discount": timestep.discount,
+        "timestep.step_type": timestep.step_type,
+    }
+    info: dict[str, Any] = dict(zip(agents, repeat(info)))
+
+    return (
+        observations,
+        rewards,
+        terminations,
+        truncations,
+        info,
+    )
+
+
+class DmControlMultiAgentCompatibilityV0(ParallelEnv):
+    """Compatibility environment for multi-agent dm-control environments, primarily soccer."""
+
+    metadata = {"render_modes": ["human"]}
+
+    def __init__(
+        self,
+        env: dm_control.composer.Environment,
+        render_mode: str | None = None,
+    ):
+        """Wrapper that converts a dm control multi-agent environment into a pettingzoo environment.
+
+        Due to how the underlying environment is setup, this environment is nondeterministic, so seeding doesn't work.
+
+        Args:
+            env (dm_env.Environment): dm control multi-agent environment
+            render_mode (Optional[str]): render_mode
+        """
+        super().__init__()
+        self._env = env
+        self.render_mode = render_mode
+
+        # get action and observation specs first
+        all_obs_spaces = [
+            dm_spec2gym_space(spec) for spec in self._env.observation_spec()
+        ]
+        all_act_spaces = [dm_spec2gym_space(spec) for spec in self._env.action_spec()]
+        num_players = len(all_obs_spaces)
+
+        # agent definitions
+        self.possible_agents = ["player_" + str(r) for r in range(num_players)]
+        self.agent_id_name_mapping = dict(zip(range(num_players), self.possible_agents))
+        self.agent_name_id_mapping = dict(zip(self.possible_agents, range(num_players)))
+
+        # the official spaces
+        self.obs_spaces = dict(zip(self.possible_agents, all_obs_spaces))
+        self.act_spaces = dict(zip(self.possible_agents, all_act_spaces))
+
+        if self.render_mode == "human":
+            self.viewer = Viewer(
+                self._env.physics.model.ptr, self._env.physics.data.ptr
+            )
+
+    @functools.lru_cache(maxsize=None)
+    def observation_space(self, agent):
+        """The observation space for agent."""
+        return self.obs_spaces[agent]
+
+    @functools.lru_cache(maxsize=None)
+    def action_space(self, agent):
+        """The action space for agent."""
+        return self.act_spaces[agent]
+
+    def render(self):
+        """Renders the environment."""
+        if self.render_mode is None:
+            gymnasium.logger.warn(
+                "You are calling render method without specifying any render mode."
+            )
+            return
+
+    def close(self):
+        """Closes the environment."""
+        self._env.physics.free()
+        self._env.close()
+
+        if hasattr(self, "viewer"):
+            self.viewer.close()
+
+    def reset(self, seed=None, return_info=False, options=None):
+        """Resets the dm-control environment."""
+        self.agents = self.possible_agents[:]
+        self.num_moves = 0
+
+        timestep = self._env.reset()
+
+        observations, _, _, _, infos = _unravel_ma_timestep(timestep, self.agents)
+
+        if not return_info:
+            return observations
+        else:
+            return observations, infos
+
+    def step(self, actions):
+        """Steps through all agents with the actions."""
+        # assert that the actions _must_ have actions for all agents
+        assert len(actions) == len(
+            self.agents
+        ), f"Must have actions for all {len(self.agents)} agents, currently only found {len(actions)}."
+
+        actions = actions.values()
+        timestep = self._env.step(actions)
+
+        obs, rewards, terminations, truncations, infos = _unravel_ma_timestep(
+            timestep, self.agents
+        )
+
+        if self.render_mode == "human":
+            self.viewer.render()
+
+        if any(terminations.values()) or any(truncations.values()):
+            self.agents = []
+
+        return obs, rewards, terminations, truncations, infos

shimmy/dm_lab_compatibility.py

@@ -0,0 +1,81 @@
+"""Wrapper to convert a dm_lab environment into a gymnasium compatible environment."""
+from __future__ import annotations
+
+from typing import Any, TypeVar
+
+import gymnasium
+import numpy as np
+from gymnasium.core import ObsType
+
+from shimmy.utils.dm_lab import dm_lab_obs2gym_obs_space, dm_lab_spec2gym_space
+
+
+class DmLabCompatibilityV0(gymnasium.Env[ObsType, np.ndarray]):
+    """A compatibility wrapper that converts a dm_lab-control environment into a gymnasium environment."""
+
+    metadata = {"render_modes": [], "render_fps": 10}
+
+    def __init__(
+        self,
+        env: Any,
+        render_mode: None = None,
+    ):
+        """Initialises the environment with a render mode along with render information."""
+        self._env = env
+
+        # need to do this to figure out what observation spec the user used
+        self._env.reset()
+        self.observation_space = dm_lab_obs2gym_obs_space(self._env.observations())
+        self.action_space = dm_lab_spec2gym_space(env.action_spec())
+
+        assert (
+            render_mode is None
+        ), "Render mode must be set on dm_lab environment init. Pass `renderer='sdl'` to the config of the base env to enable human rendering."
+        self.render_mode = render_mode
+
+    def reset(
+        self, *, seed: int | None = None, options: dict[str, Any] | None = None
+    ) -> tuple[ObsType, dict[str, Any]]:
+        """Resets the dm-lab environment."""
+        super().reset(seed=seed)
+
+        self._env.reset(seed=seed)
+        info = {}
+
+        return (
+            self._env.observations(),
+            info,
+        )  # pyright: ignore[reportGeneralTypeIssues]
+
+    def step(
+        self, action: dict[str, np.ndarray]
+    ) -> tuple[ObsType, float, bool, bool, dict[str, Any]]:
+        """Steps through the dm-lab environment."""
+        # there's some funky quantization happening here, dm_lab only accepts ints as actions
+        action = np.array([a[0] for a in action.values()], dtype=np.intc)
+        reward = self._env.step(action)
+
+        obs = self._env.observations()
+        terminated = not self._env.is_running()
+        truncated = False
+        info = {}
+
+        return (  # pyright: ignore[reportGeneralTypeIssues]
+            obs,
+            reward,
+            terminated,
+            truncated,
+            info,
+        )
+
+    def render(self) -> None:
+        """Renders the dm_lab env."""
+        raise NotImplementedError
+
+    def close(self):
+        """Closes the environment."""
+        self._env.close()
+
+    def __getattr__(self, item: str):
+        """If the attribute is missing, try getting the attribute from dm_lab env."""
+        return getattr(self._env, item)

shimmy/openspiel_wrapper.py → shimmy/openspiel_compatibility.py

@@ -12,7 +12,7 @@
 from pettingzoo.utils.env import AgentID
 
 
-class OpenspielWrapperV0(pz.AECEnv):
+class OpenspielCompatibilityV0(pz.AECEnv):
     """Wrapper that converts an openspiel environment into a pettingzoo environment."""
 
     metadata = {"render_modes": []}