✨ initial commit

src/core/env.py

@@ -0,0 +1,59 @@
+import abc
+import dataclasses
+from typing import TypeVar, Generic, Any
+from gymnasium import spaces
+import torch
+import pathlib
+
+T = TypeVar("T")
+
+
+@dataclasses.dataclass
+class ActuatorConfig:
+    """Actuator definition — maps a joint to a motor with gear ratio and control limits.
+    Kept in the env config (not runner config) because actuators define what the robot
+    can do, which determines action space — a task-level concept.
+    This mirrors Isaac Lab's pattern of separating actuator config from the robot file."""
+    joint: str = ""
+    gear: float = 1.0
+    ctrl_range: tuple[float, float] = (-1.0, 1.0)
+
+
+@dataclasses.dataclass
+class BaseEnvConfig:
+    max_steps: int = 1000
+    model_path: pathlib.Path | None = None
+    actuators: list[ActuatorConfig] = dataclasses.field(default_factory=list)
+
+class BaseEnv(abc.ABC, Generic[T]):
+    def __init__(self, config: BaseEnvConfig):
+        self.config = config
+
+    @property
+    @abc.abstractmethod
+    def observation_space(self) -> spaces.Space:
+        ...
+
+    @property
+    @abc.abstractmethod
+    def action_space(self) -> spaces.Space:
+        ...
+
+    @abc.abstractmethod
+    def build_state(self, qpos: torch.Tensor, qvel: torch.Tensor) -> Any:
+        ...
+
+    @abc.abstractmethod
+    def compute_observations(self, state: Any) -> torch.Tensor:
+        ...
+
+    @abc.abstractmethod
+    def compute_rewards(self, state: Any, actions: torch.Tensor) -> torch.Tensor:
+        ...
+
+    @abc.abstractmethod
+    def compute_terminations(self, state: Any) -> torch.Tensor:
+        ...
+
+    def compute_truncations(self, step_counts: torch.Tensor) -> torch.Tensor:
+        return step_counts >= self.config.max_steps