fix time aware observation wrapper issue and add try catch for rendering dmc

alr_envs/alr/mujoco/reacher/mp_wrapper.py

@@ -1,5 +1,6 @@
 from typing import Union, Tuple
 
+import gym
 import numpy as np
 
 from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
@@ -9,14 +10,13 @@ class MPWrapper(RawInterfaceWrapper):
 
     @property
     def context_mask(self):
-        return np.concatenate([
-            [False] * self.env.n_links,  # cos
-            [False] * self.env.n_links,  # sin
-            [True] * 2,  # goal position
-            [False] * self.env.n_links,  # angular velocity
-            [False] * 3,  # goal distance
-            # [False],  # step
-        ])
+        return np.concatenate([[False] * self.env.n_links,  # cos
+                               [False] * self.env.n_links,  # sin
+                               [True] * 2,  # goal position
+                               [False] * self.env.n_links,  # angular velocity
+                               [False] * 3,  # goal distance
+                               # [False],  # step
+                               ])
 
     @property
     def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:

alr_envs/black_box/black_box_wrapper.py

@@ -70,10 +70,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
 
     def observation(self, observation):
         # return context space if we are
-        mask = self.env.context_mask
-        # if self.is_time_aware:
-        #     mask = np.append(mask, False)
-        obs = observation[mask] if self.return_context_observation else observation
+        obs = observation[self.env.context_mask] if self.return_context_observation else observation
         # cast dtype because metaworld returns incorrect that throws gym error
         return obs.astype(self.observation_space.dtype)
 

alr_envs/dmc/dmc_wrapper.py

@@ -2,7 +2,6 @@
 # License: MIT
 # Copyright (c) 2020 Denis Yarats
 import collections
-import cv2
 from collections.abc import MutableMapping
 from typing import Any, Dict, Tuple, Optional, Union, Callable
 
@@ -138,11 +137,14 @@ class DMCWrapper(gym.Env):
             img = np.dstack([img.astype(np.uint8)] * 3)
 
         if mode == 'human':
-            if self._window is None:
-                self._window = cv2.namedWindow(self.id, cv2.WINDOW_AUTOSIZE)
-
-            cv2.imshow(self.id, img[..., ::-1])  # Image in BGR
-            cv2.waitKey(1)
+            try:
+                import cv2
+                if self._window is None:
+                    self._window = cv2.namedWindow(self.id, cv2.WINDOW_AUTOSIZE)
+                cv2.imshow(self.id, img[..., ::-1])  # Image in BGR
+                cv2.waitKey(1)
+            except ImportError:
+                raise gym.error.DependencyNotInstalled("Rendering requires opencv. Run `pip install opencv-python`")
             # PYGAME seems to destroy some global rendering configs from the physics render
             # except ImportError:
             #     import pygame

alr_envs/utils/make_env_helpers.py

@@ -28,7 +28,7 @@ from alr_envs.black_box.factory.controller_factory import get_controller
 from alr_envs.black_box.factory.phase_generator_factory import get_phase_generator
 from alr_envs.black_box.factory.trajectory_generator_factory import get_trajectory_generator
 from alr_envs.black_box.raw_interface_wrapper import RawInterfaceWrapper
-from alr_envs.black_box.time_aware_observation import TimeAwareObservation
+from alr_envs.utils.time_aware_observation import TimeAwareObservation
 from alr_envs.utils.utils import nested_update
 
 
@@ -148,11 +148,10 @@ def make_bb(
     if learn_sub_trajs and do_replanning:
         raise ValueError('Cannot used sub-trajectory learning and replanning together.')
 
-    if learn_sub_trajs or do_replanning:
-        # add time_step observation when replanning
-        if not any(issubclass(w, TimeAwareObservation) for w in kwargs['wrappers']):
-            # Add as first wrapper in order to alter observation
-            kwargs['wrappers'].insert(0, TimeAwareObservation)
+    # add time_step observation when replanning
+    if (learn_sub_trajs or do_replanning) and not any(issubclass(w, TimeAwareObservation) for w in kwargs['wrappers']):
+        # Add as first wrapper in order to alter observation
+        kwargs['wrappers'].insert(0, TimeAwareObservation)
 
     env = _make_wrapped_env(env_id=env_id, wrappers=wrappers, seed=seed, **kwargs)