mirror of
https://github.com/Farama-Foundation/Gymnasium.git
synced 2025-07-31 22:04:31 +00:00
de9eed541b
* init * add .gitignore * fix .gitignore * remove internal backend use * fix VideoRecorder test * fix .gitignore * fix order enforcing tests * adapt play.py * reformat * fix .gitignore * add type to DummyPlayEnv
464 lines
14 KiB
Python
464 lines
14 KiB
Python
from functools import partial
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from os import path
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from typing import Optional, Union
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import numpy as np
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import gym
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from gym import error, logger, spaces
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from gym.spaces import Space
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from gym.utils.renderer import Renderer
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MUJOCO_PY_NOT_INSTALLED = False
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MUJOCO_NOT_INSTALLED = False
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try:
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import mujoco_py
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except ImportError as e:
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MUJOCO_PY_IMPORT_ERROR = e
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MUJOCO_PY_NOT_INSTALLED = True
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try:
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import mujoco
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except ImportError as e:
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MUJOCO_IMPORT_ERROR = e
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MUJOCO_NOT_INSTALLED = True
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DEFAULT_SIZE = 480
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class BaseMujocoEnv(gym.Env):
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"""Superclass for all MuJoCo environments."""
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def __init__(
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self,
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model_path,
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frame_skip,
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observation_space: Space,
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render_mode: Optional[str] = None,
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width: int = DEFAULT_SIZE,
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height: int = DEFAULT_SIZE,
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camera_id: Optional[int] = None,
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camera_name: Optional[str] = None,
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):
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if model_path.startswith("/"):
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self.fullpath = model_path
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else:
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self.fullpath = path.join(path.dirname(__file__), "assets", model_path)
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if not path.exists(self.fullpath):
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raise OSError(f"File {self.fullpath} does not exist")
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self._initialize_simulation()
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self.init_qpos = self.data.qpos.ravel().copy()
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self.init_qvel = self.data.qvel.ravel().copy()
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self._viewers = {}
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self.frame_skip = frame_skip
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self.viewer = None
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assert self.metadata["render_modes"] == [
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"human",
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"rgb_array",
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"depth_array",
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"single_rgb_array",
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"single_depth_array",
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]
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assert (
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int(np.round(1.0 / self.dt)) == self.metadata["render_fps"]
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), f'Expected value: {int(np.round(1.0 / self.dt))}, Actual value: {self.metadata["render_fps"]}'
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self.observation_space = observation_space
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self._set_action_space()
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self.render_mode = render_mode
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render_frame = partial(
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self._render,
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width=width,
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height=height,
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camera_name=camera_name,
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camera_id=camera_id,
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)
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self.renderer = Renderer(self.render_mode, render_frame)
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def _set_action_space(self):
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bounds = self.model.actuator_ctrlrange.copy().astype(np.float32)
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low, high = bounds.T
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self.action_space = spaces.Box(low=low, high=high, dtype=np.float32)
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return self.action_space
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# methods to override:
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# ----------------------------
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def reset_model(self):
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"""
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Reset the robot degrees of freedom (qpos and qvel).
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Implement this in each subclass.
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"""
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raise NotImplementedError
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def viewer_setup(self):
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"""
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This method is called when the viewer is initialized.
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Optionally implement this method, if you need to tinker with camera position and so forth.
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"""
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def _initialize_simulation(self):
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"""
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Initialize MuJoCo simulation data structures mjModel and mjData.
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"""
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raise NotImplementedError
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def _reset_simulation(self):
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"""
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Reset MuJoCo simulation data structures, mjModel and mjData.
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"""
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raise NotImplementedError
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def _step_mujoco_simulation(self, ctrl, n_frames):
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"""
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Step over the MuJoCo simulation.
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"""
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raise NotImplementedError
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def _render(
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self,
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mode: str = "human",
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width: int = DEFAULT_SIZE,
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height: int = DEFAULT_SIZE,
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camera_id: Optional[int] = None,
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camera_name: Optional[str] = None,
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):
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"""
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Render a frame from the MuJoCo simulation as specified by the render_mode.
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"""
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raise NotImplementedError
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# -----------------------------
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def reset(
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self,
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*,
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seed: Optional[int] = None,
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return_info: bool = False,
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options: Optional[dict] = None,
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):
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super().reset(seed=seed)
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self._reset_simulation()
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ob = self.reset_model()
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self.renderer.reset()
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self.renderer.render_step()
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if not return_info:
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return ob
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else:
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return ob, {}
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def set_state(self, qpos, qvel):
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"""
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Set the joints position qpos and velocity qvel of the model. Override this method depending on the MuJoCo bindings used.
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"""
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assert qpos.shape == (self.model.nq,) and qvel.shape == (self.model.nv,)
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@property
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def dt(self):
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return self.model.opt.timestep * self.frame_skip
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def do_simulation(self, ctrl, n_frames):
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"""
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Step the simulation n number of frames and applying a control action.
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"""
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# Check control input is contained in the action space
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if np.array(ctrl).shape != self.action_space.shape:
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raise ValueError("Action dimension mismatch")
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self._step_mujoco_simulation(ctrl, n_frames)
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def render(self):
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return self.renderer.get_renders()
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def close(self):
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if self.viewer is not None:
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self.viewer = None
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self._viewers = {}
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def get_body_com(self, body_name):
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"""Return the cartesian position of a body frame"""
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raise NotImplementedError
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def state_vector(self):
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"""Return the position and velocity joint states of the model"""
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return np.concatenate([self.data.qpos.flat, self.data.qvel.flat])
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class MuJocoPyEnv(BaseMujocoEnv):
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def __init__(
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self,
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model_path: str,
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frame_skip: int,
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observation_space: Space,
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render_mode: Optional[str] = None,
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width: int = DEFAULT_SIZE,
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height: int = DEFAULT_SIZE,
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camera_id: Optional[int] = None,
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camera_name: Optional[str] = None,
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):
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if MUJOCO_PY_NOT_INSTALLED:
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raise error.DependencyNotInstalled(
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f"{MUJOCO_PY_IMPORT_ERROR}. (HINT: you need to install mujoco_py, and also perform the setup instructions here: https://github.com/openai/mujoco-py/.)"
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)
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logger.warn(
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"This version of the mujoco environments depends "
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"on the mujoco-py bindings, which are no longer maintained "
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"and may stop working. Please upgrade to the v4 versions of "
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"the environments (which depend on the mujoco python bindings instead), unless "
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"you are trying to precisely replicate previous works)."
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)
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super().__init__(
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model_path,
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frame_skip,
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observation_space,
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render_mode,
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width,
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height,
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camera_id,
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camera_name,
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)
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def _initialize_simulation(self):
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self.model = mujoco_py.load_model_from_path(self.fullpath)
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self.sim = mujoco_py.MjSim(self.model)
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self.data = self.sim.data
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def _reset_simulation(self):
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self.sim.reset()
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def set_state(self, qpos, qvel):
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super().set_state(qpos, qvel)
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state = self.sim.get_state()
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state = mujoco_py.MjSimState(state.time, qpos, qvel, state.act, state.udd_state)
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self.sim.set_state(state)
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self.sim.forward()
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def _step_mujoco_simulation(self, ctrl, n_frames):
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self.sim.data.ctrl[:] = ctrl
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for _ in range(n_frames):
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self.sim.step()
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def _render(
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self,
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mode: str = "human",
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width: int = DEFAULT_SIZE,
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height: int = DEFAULT_SIZE,
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camera_id: Optional[int] = None,
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camera_name: Optional[str] = None,
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):
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assert mode in self.metadata["render_modes"]
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if mode in {
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"rgb_array",
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"single_rgb_array",
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"depth_array",
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"single_depth_array",
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}:
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if camera_id is not None and camera_name is not None:
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raise ValueError(
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"Both `camera_id` and `camera_name` cannot be"
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" specified at the same time."
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)
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no_camera_specified = camera_name is None and camera_id is None
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if no_camera_specified:
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camera_name = "track"
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if camera_id is None and camera_name in self.model._camera_name2id:
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if camera_name in self.model._camera_name2id:
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camera_id = self.model.camera_name2id(camera_name)
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self._get_viewer(mode).render(width, height, camera_id=camera_id)
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if mode in {"rgb_array", "single_rgb_array"}:
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data = self._get_viewer(mode).read_pixels(width, height, depth=False)
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# original image is upside-down, so flip it
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return data[::-1, :, :]
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elif mode in {"depth_array", "single_depth_array"}:
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self._get_viewer(mode).render(width, height)
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# Extract depth part of the read_pixels() tuple
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data = self._get_viewer(mode).read_pixels(width, height, depth=True)[1]
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# original image is upside-down, so flip it
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return data[::-1, :]
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elif mode == "human":
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self._get_viewer(mode).render()
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def _get_viewer(
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self, mode
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) -> Union["mujoco_py.MjViewer", "mujoco_py.MjRenderContextOffscreen"]:
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self.viewer = self._viewers.get(mode)
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if self.viewer is None:
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if mode == "human":
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self.viewer = mujoco_py.MjViewer(self.sim)
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elif mode in {
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"rgb_array",
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"depth_array",
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"single_rgb_array",
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"single_depth_array",
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}:
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self.viewer = mujoco_py.MjRenderContextOffscreen(self.sim, -1)
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else:
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raise AttributeError(
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f"Unknown mode: {mode}, expected modes: {self.metadata['render_modes']}"
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)
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self.viewer_setup()
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self._viewers[mode] = self.viewer
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return self.viewer
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def get_body_com(self, body_name):
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return self.data.get_body_xpos(body_name)
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class MujocoEnv(BaseMujocoEnv):
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"""Superclass for MuJoCo environments."""
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def __init__(
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self,
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model_path,
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frame_skip,
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observation_space: Space,
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render_mode: Optional[str] = None,
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width: int = DEFAULT_SIZE,
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height: int = DEFAULT_SIZE,
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camera_id: Optional[int] = None,
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camera_name: Optional[str] = None,
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):
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if MUJOCO_NOT_INSTALLED:
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raise error.DependencyNotInstalled(
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f"{MUJOCO_IMPORT_ERROR}. (HINT: you need to install mujoco)"
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)
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super().__init__(
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model_path,
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frame_skip,
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observation_space,
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render_mode,
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width,
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height,
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camera_id,
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camera_name,
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)
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def _initialize_simulation(self):
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self.model = mujoco.MjModel.from_xml_path(self.fullpath)
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self.data = mujoco.MjData(self.model)
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def _reset_simulation(self):
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mujoco.mj_resetData(self.model, self.data)
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def set_state(self, qpos, qvel):
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super().set_state(qpos, qvel)
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self.data.qpos[:] = np.copy(qpos)
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self.data.qvel[:] = np.copy(qvel)
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if self.model.na == 0:
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self.data.act[:] = None
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mujoco.mj_forward(self.model, self.data)
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def _step_mujoco_simulation(self, ctrl, n_frames):
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self.data.ctrl[:] = ctrl
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mujoco.mj_step(self.model, self.data, nstep=self.frame_skip)
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# As of MuJoCo 2.0, force-related quantities like cacc are not computed
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# unless there's a force sensor in the model.
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# See https://github.com/openai/gym/issues/1541
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mujoco.mj_rnePostConstraint(self.model, self.data)
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def _render(
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self,
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mode: str = "human",
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width: int = DEFAULT_SIZE,
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height: int = DEFAULT_SIZE,
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camera_id: Optional[int] = None,
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camera_name: Optional[str] = None,
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):
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assert mode in self.metadata["render_modes"]
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if mode in {
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"rgb_array",
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"single_rgb_array",
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"depth_array",
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"single_depth_array",
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}:
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if camera_id is not None and camera_name is not None:
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raise ValueError(
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"Both `camera_id` and `camera_name` cannot be"
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" specified at the same time."
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)
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no_camera_specified = camera_name is None and camera_id is None
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if no_camera_specified:
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camera_name = "track"
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if camera_id is None:
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camera_id = mujoco.mj_name2id(
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self.model,
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mujoco.mjtObj.mjOBJ_CAMERA,
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camera_name,
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)
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self._get_viewer(mode).render(width, height, camera_id=camera_id)
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if mode in {"rgb_array", "single_rgb_array"}:
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data = self._get_viewer(mode).read_pixels(width, height, depth=False)
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# original image is upside-down, so flip it
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return data[::-1, :, :]
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elif mode in {"depth_array", "single_depth_array"}:
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self._get_viewer(mode).render(width, height)
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# Extract depth part of the read_pixels() tuple
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data = self._get_viewer(mode).read_pixels(width, height, depth=True)[1]
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# original image is upside-down, so flip it
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return data[::-1, :]
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elif mode == "human":
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self._get_viewer(mode).render()
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def close(self):
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if self.viewer is not None:
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self.viewer.close()
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super().close()
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def _get_viewer(
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self, mode, width=DEFAULT_SIZE, height=DEFAULT_SIZE
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) -> Union["gym.envs.mujoco.Viewer", "gym.envs.mujoco.RenderContextOffscreen"]:
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self.viewer = self._viewers.get(mode)
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if self.viewer is None:
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if mode == "human":
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from gym.envs.mujoco import Viewer
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self.viewer = Viewer(self.model, self.data)
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elif mode in {
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"rgb_array",
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"depth_array",
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"single_rgb_array",
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"single_depth_array",
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}:
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from gym.envs.mujoco import RenderContextOffscreen
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self.viewer = RenderContextOffscreen(
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width, height, self.model, self.data
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)
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else:
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raise AttributeError(
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f"Unexpected mode: {mode}, expected modes: {self.metadata['render_modes']}"
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)
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self.viewer_setup()
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self._viewers[mode] = self.viewer
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return self.viewer
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def get_body_com(self, body_name):
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return self.data.body(body_name).xpos
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