removed file deprecated
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# Adopted from: https://github.com/denisyarats/dmc2gym/blob/master/dmc2gym/wrappers.py
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# License: MIT
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# Copyright (c) 2020 Denis Yarats
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import collections
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from collections.abc import MutableMapping
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from typing import Any, Dict, Tuple, Optional, Union, Callable, SupportsFloat
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import gymnasium as gym
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import numpy as np
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from dm_control import composer
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from dm_control.rl import control
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from dm_env import specs
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from gymnasium import spaces
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from gymnasium.core import ObsType, ActType
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def _spec_to_box(spec):
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def extract_min_max(s):
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assert s.dtype == np.float64 or s.dtype == np.float32, \
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f"Only float64 and float32 types are allowed, instead {s.dtype} was found"
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dim = int(np.prod(s.shape))
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if type(s) == specs.Array:
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bound = np.inf * np.ones(dim, dtype=s.dtype)
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return -bound, bound
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elif type(s) == specs.BoundedArray:
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zeros = np.zeros(dim, dtype=s.dtype)
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return s.minimum + zeros, s.maximum + zeros
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mins, maxs = [], []
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for s in spec:
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mn, mx = extract_min_max(s)
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mins.append(mn)
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maxs.append(mx)
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low = np.concatenate(mins, axis=0)
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high = np.concatenate(maxs, axis=0)
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assert low.shape == high.shape
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return spaces.Box(low, high, dtype=s.dtype)
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def _flatten_obs(obs: MutableMapping):
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"""
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Flattens an observation of type MutableMapping, e.g. a dict to a 1D array.
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Args:
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obs: observation to flatten
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Returns: 1D array of observation
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"""
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if not isinstance(obs, MutableMapping):
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raise ValueError(f'Requires dict-like observations structure. {type(obs)} found.')
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# Keep key order consistent for non OrderedDicts
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keys = obs.keys() if isinstance(obs, collections.OrderedDict) else sorted(obs.keys())
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obs_vals = [np.array([obs[key]]) if np.isscalar(obs[key]) else obs[key].ravel() for key in keys]
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return np.concatenate(obs_vals)
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class DMCWrapper(gym.Env):
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def __init__(self,
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env: Callable[[], Union[composer.Environment, control.Environment]],
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):
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raise Exception('The fancy_gym dmc-wrapper is deprecated; shimmy should be used instead.')
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# TODO: Currently this is required to be a function because dmc does not allow to copy composers environments
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self._env = env()
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# action and observation space
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self._action_space = _spec_to_box([self._env.action_spec()])
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self._observation_space = _spec_to_box(self._env.observation_spec().values())
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self._window = None
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self.id = 'dmc'
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def __getattr__(self, item):
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"""Propagate only non-existent properties to wrapped env."""
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if item.startswith('_'):
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raise AttributeError("attempted to get missing private attribute '{}'".format(item))
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if item in self.__dict__:
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return getattr(self, item)
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return getattr(self._env, item)
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def _get_obs(self, time_step):
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obs = _flatten_obs(time_step.observation).astype(self.observation_space.dtype)
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return obs
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@property
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def observation_space(self):
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return self._observation_space
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@property
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def action_space(self):
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return self._action_space
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@property
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def dt(self):
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return self._env.control_timestep()
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def seed(self, seed=None):
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self._action_space.seed(seed)
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self._observation_space.seed(seed)
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def step(self, action: ActType) -> Tuple[ObsType, SupportsFloat, bool, bool, Dict[str, Any]]:
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assert self._action_space.contains(action)
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extra = {'internal_state': self._env.physics.get_state().copy()}
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time_step = self._env.step(action)
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reward = time_step.reward or 0.
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terminated = False
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truncated = time_step.last() and time_step.discount > 0
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obs = self._get_obs(time_step)
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extra['discount'] = time_step.discount
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return obs, reward, terminated, truncated, extra
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def reset(self, *, seed: Optional[int] = None, options: Optional[Dict[str, Any]] = None) \
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-> Tuple[ObsType, Dict[str, Any]]:
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time_step = self._env.reset()
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obs = self._get_obs(time_step)
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return obs, {}
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def render(self, mode='rgb_array', height=240, width=320, camera_id=-1, overlays=(), depth=False,
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segmentation=False, scene_option=None, render_flag_overrides=None):
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# assert mode == 'rgb_array', 'only support rgb_array mode, given %s' % mode
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if mode == "rgb_array":
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return self._env.physics.render(height=height, width=width, camera_id=camera_id, overlays=overlays,
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depth=depth, segmentation=segmentation, scene_option=scene_option,
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render_flag_overrides=render_flag_overrides)
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# Render max available buffer size. Larger is only possible by altering the XML.
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img = self._env.physics.render(height=self._env.physics.model.vis.global_.offheight,
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width=self._env.physics.model.vis.global_.offwidth,
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camera_id=camera_id, overlays=overlays, depth=depth, segmentation=segmentation,
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scene_option=scene_option, render_flag_overrides=render_flag_overrides)
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if depth:
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img = np.dstack([img.astype(np.uint8)] * 3)
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if mode == 'human':
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try:
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import cv2
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if self._window is None:
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self._window = cv2.namedWindow(self.id, cv2.WINDOW_AUTOSIZE)
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cv2.imshow(self.id, img[..., ::-1]) # Image in BGR
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cv2.waitKey(1)
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except ImportError:
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raise gym.error.DependencyNotInstalled("Rendering requires opencv. Run `pip install opencv-python`")
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# PYGAME seems to destroy some global rendering configs from the physics render
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# except ImportError:
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# import pygame
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# img_copy = img.copy().transpose((1, 0, 2))
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# if self._window is None:
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# pygame.init()
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# pygame.display.init()
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# self._window = pygame.display.set_mode(img_copy.shape[:2])
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# self.clock = pygame.time.Clock()
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#
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# surf = pygame.surfarray.make_surface(img_copy)
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# self._window.blit(surf, (0, 0))
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# pygame.event.pump()
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# self.clock.tick(30)
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# pygame.display.flip()
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def close(self):
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super().close()
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if self._window is not None:
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try:
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import cv2
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cv2.destroyWindow(self.id)
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except ImportError:
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import pygame
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pygame.display.quit()
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pygame.quit()
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@property
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def reward_range(self) -> Tuple[float, float]:
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reward_spec = self._env.reward_spec()
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if isinstance(reward_spec, specs.BoundedArray):
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return reward_spec.minimum, reward_spec.maximum
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return -float('inf'), float('inf')
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@property
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def metadata(self):
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return {'render.modes': ['human', 'rgb_array'],
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'video.frames_per_second': round(1.0 / self._env.control_timestep())}
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