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Initialize observation spaces and pytest (#2929)

Browse Source 
* Remove step initialization for mujoco obs spaces

	* remove step initialization for mujoco obs space

	* pre-commit

pytest obs space mujoco
This commit is contained in:
Rodrigo de Lazcano
2022-06-30 10:59:59 -04:00
committed by GitHub
parent 7f6effbc0d
commit 61a39f41bc
30 changed files with 364 additions and 37 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
gym/envs/mujoco/ant.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class AntEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,8 +18,16 @@ class AntEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(
low=-np.inf, high=np.inf, shape=(111,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "ant.xml", 5, mujoco_bindings="mujoco_py", **kwargs
self,
"ant.xml",
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

17
gym/envs/mujoco/ant_v3.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"distance": 4.0,
@@ -50,8 +51,22 @@ class AntEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(111,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(113,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 5, mujoco_bindings="mujoco_py", **kwargs
self,
xml_file,
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
@property

15
gym/envs/mujoco/ant_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"distance": 4.0,
@@ -215,7 +216,19 @@ class AntEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
mujoco_env.MujocoEnv.__init__(self, xml_file, 5, **kwargs)
obs_shape = 27
if not exclude_current_positions_from_observation:
obs_shape += 2
if use_contact_forces:
obs_shape += 84
observation_space = Box(
low=-np.inf, high=np.inf, shape=(obs_shape,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 5, observation_space=observation_space, **kwargs
)
@property
def healthy_reward(self):

9
gym/envs/mujoco/half_cheetah.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class HalfCheetahEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,8 +18,14 @@ class HalfCheetahEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "half_cheetah.xml", 5, mujoco_bindings="mujoco_py", **kwargs
self,
"half_cheetah.xml",
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

17
gym/envs/mujoco/half_cheetah_v3.py
View File

@@ -4,6 +4,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"distance": 4.0,
@@ -43,8 +44,22 @@ class HalfCheetahEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(18,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 5, mujoco_bindings="mujoco_py", **kwargs
self,
xml_file,
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
def control_cost(self, action):

14
gym/envs/mujoco/half_cheetah_v4.py
View File

@@ -4,6 +4,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"distance": 4.0,
@@ -162,7 +163,18 @@ class HalfCheetahEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
mujoco_env.MujocoEnv.__init__(self, "half_cheetah.xml", 5, **kwargs)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(18,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "half_cheetah.xml", 5, observation_space=observation_space, **kwargs
)
def control_cost(self, action):
control_cost = self._ctrl_cost_weight * np.sum(np.square(action))

9
gym/envs/mujoco/hopper.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class HopperEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,8 +18,14 @@ class HopperEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "hopper.xml", 4, mujoco_bindings="mujoco_py", **kwargs
self,
"hopper.xml",
4,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

17
gym/envs/mujoco/hopper_v3.py
View File

@@ -4,6 +4,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
@@ -58,8 +59,22 @@ class HopperEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(12,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 4, mujoco_bindings="mujoco_py", **kwargs
self,
xml_file,
4,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
@property

14
gym/envs/mujoco/hopper_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
@@ -180,7 +181,18 @@ class HopperEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
mujoco_env.MujocoEnv.__init__(self, "hopper.xml", 4, **kwargs)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(12,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "hopper.xml", 4, observation_space=observation_space, **kwargs
)
@property
def healthy_reward(self):

11
gym/envs/mujoco/humanoid.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
def mass_center(model, sim):
@@ -23,8 +24,16 @@ class HumanoidEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(
low=-np.inf, high=np.inf, shape=(376,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "humanoid.xml", 5, mujoco_bindings="mujoco_py", **kwargs
self,
"humanoid.xml",
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

16
gym/envs/mujoco/humanoid_v3.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 1,
@@ -58,9 +59,22 @@ class HumanoidEnv(mujoco_env.MujocoEnv, utils.EzPickle):
self._exclude_current_positions_from_observation = (
exclude_current_positions_from_observation
)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(376,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(378,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 5, mujoco_bindings="mujoco_py", **kwargs
self,
xml_file,
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
@property

14
gym/envs/mujoco/humanoid_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 1,
@@ -248,7 +249,18 @@ class HumanoidEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
mujoco_env.MujocoEnv.__init__(self, "humanoid.xml", 5, **kwargs)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(376,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(378,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "humanoid.xml", 5, observation_space=observation_space, **kwargs
)
@property
def healthy_reward(self):

11
gym/envs/mujoco/humanoidstandup.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class HumanoidStandupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,8 +18,16 @@ class HumanoidStandupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(
low=-np.inf, high=np.inf, shape=(376,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "humanoidstandup.xml", 5, mujoco_bindings="mujoco_py", **kwargs
self,
"humanoidstandup.xml",
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

12
gym/envs/mujoco/humanoidstandup_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class HumanoidStandupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -189,7 +190,16 @@ class HumanoidStandupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
mujoco_env.MujocoEnv.__init__(self, "humanoidstandup.xml", 5, **kwargs)
observation_space = Box(
low=-np.inf, high=np.inf, shape=(376,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self,
"humanoidstandup.xml",
5,
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)
def _get_obs(self):

3
gym/envs/mujoco/inverted_double_pendulum.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class InvertedDoublePendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,11 +18,13 @@ class InvertedDoublePendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self,
"inverted_double_pendulum.xml",
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

10
gym/envs/mujoco/inverted_double_pendulum_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class InvertedDoublePendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -123,7 +124,14 @@ class InvertedDoublePendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
mujoco_env.MujocoEnv.__init__(self, "inverted_double_pendulum.xml", 5, **kwargs)
observation_space = Box(low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self,
"inverted_double_pendulum.xml",
5,
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)
def step(self, action):

9
gym/envs/mujoco/inverted_pendulum.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class InvertedPendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -18,8 +19,14 @@ class InvertedPendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
observation_space = Box(low=-np.inf, high=np.inf, shape=(4,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "inverted_pendulum.xml", 2, mujoco_bindings="mujoco_py", **kwargs
self,
"inverted_pendulum.xml",
2,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
def step(self, a):

10
gym/envs/mujoco/inverted_pendulum_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class InvertedPendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -95,7 +96,14 @@ class InvertedPendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
mujoco_env.MujocoEnv.__init__(self, "inverted_pendulum.xml", 2, **kwargs)
observation_space = Box(low=-np.inf, high=np.inf, shape=(4,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self,
"inverted_pendulum.xml",
2,
observation_space=observation_space,
**kwargs
)
def step(self, a):
reward = 1.0

12
gym/envs/mujoco/mujoco_env.py
View File

@@ -7,6 +7,7 @@ import numpy as np
import gym
from gym import error, logger, spaces
from gym.spaces import Space
from gym.utils.renderer import Renderer
DEFAULT_SIZE = 480
@@ -39,6 +40,7 @@ class MujocoEnv(gym.Env):
self,
model_path,
frame_skip,
observation_space: Space,
render_mode: Optional[str] = None,
width: int = DEFAULT_SIZE,
height: int = DEFAULT_SIZE,
@@ -120,11 +122,7 @@ class MujocoEnv(gym.Env):
)
self.renderer = Renderer(self.render_mode, render_frame)
action = self.action_space.sample()
observation, _reward, done, _info = self.step(action)
assert not done
self._set_observation_space(observation)
self.observation_space = observation_space
def _set_action_space(self):
bounds = self.model.actuator_ctrlrange.copy().astype(np.float32)
@@ -132,10 +130,6 @@ class MujocoEnv(gym.Env):
self.action_space = spaces.Box(low=low, high=high, dtype=np.float32)
return self.action_space
def _set_observation_space(self, observation):
self.observation_space = convert_observation_to_space(observation)
return self.observation_space
# methods to override:
# ----------------------------

9
gym/envs/mujoco/pusher.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class PusherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -18,8 +19,14 @@ class PusherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
observation_space = Box(low=-np.inf, high=np.inf, shape=(23,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "pusher.xml", 5, mujoco_bindings="mujoco_py", **kwargs
self,
"pusher.xml",
5,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
def step(self, a):

6
gym/envs/mujoco/pusher_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class PusherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -140,7 +141,10 @@ class PusherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
mujoco_env.MujocoEnv.__init__(self, "pusher.xml", 5, **kwargs)
observation_space = Box(low=-np.inf, high=np.inf, shape=(23,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "pusher.xml", 5, observation_space=observation_space, **kwargs
)
def step(self, a):
vec_1 = self.get_body_com("object") - self.get_body_com("tips_arm")

9
gym/envs/mujoco/reacher.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class ReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -18,8 +19,14 @@ class ReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
observation_space = Box(low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "reacher.xml", 2, mujoco_bindings="mujoco_py", **kwargs
self,
"reacher.xml",
2,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
def step(self, a):

6
gym/envs/mujoco/reacher_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class ReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -130,7 +131,10 @@ class ReacherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
def __init__(self, **kwargs):
utils.EzPickle.__init__(self)
mujoco_env.MujocoEnv.__init__(self, "reacher.xml", 2, **kwargs)
observation_space = Box(low=-np.inf, high=np.inf, shape=(11,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "reacher.xml", 2, observation_space=observation_space, **kwargs
)
def step(self, a):
vec = self.get_body_com("fingertip") - self.get_body_com("target")

9
gym/envs/mujoco/swimmer.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class SwimmerEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,8 +18,14 @@ class SwimmerEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(low=-np.inf, high=np.inf, shape=(8,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "swimmer.xml", 4, mujoco_bindings="mujoco_py", **kwargs
self,
"swimmer.xml",
4,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

17
gym/envs/mujoco/swimmer_v3.py
View File

@@ -4,6 +4,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {}
@@ -40,8 +41,22 @@ class SwimmerEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(8,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(10,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 4, mujoco_bindings="mujoco_py", **kwargs
self,
xml_file,
4,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
def control_cost(self, action):

14
gym/envs/mujoco/swimmer_v4.py
View File

@@ -4,6 +4,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {}
@@ -152,8 +153,17 @@ class SwimmerEnv(mujoco_env.MujocoEnv, utils.EzPickle):
self._exclude_current_positions_from_observation = (
exclude_current_positions_from_observation
)
mujoco_env.MujocoEnv.__init__(self, "swimmer.xml", 4, **kwargs)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(8,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(10,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "swimmer.xml", 4, observation_space=observation_space, **kwargs
)
def control_cost(self, action):
control_cost = self._ctrl_cost_weight * np.sum(np.square(action))

9
gym/envs/mujoco/walker2d.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
class Walker2dEnv(mujoco_env.MujocoEnv, utils.EzPickle):
@@ -17,8 +18,14 @@ class Walker2dEnv(mujoco_env.MujocoEnv, utils.EzPickle):
}
def __init__(self, **kwargs):
observation_space = Box(low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64)
mujoco_env.MujocoEnv.__init__(
self, "walker2d.xml", 4, mujoco_bindings="mujoco_py", **kwargs
self,
"walker2d.xml",
4,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
utils.EzPickle.__init__(self)

17
gym/envs/mujoco/walker2d_v3.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
@@ -53,8 +54,22 @@ class Walker2dEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(18,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, xml_file, 4, mujoco_bindings="mujoco_py", **kwargs
self,
xml_file,
4,
mujoco_bindings="mujoco_py",
observation_space=observation_space,
**kwargs
)
@property

14
gym/envs/mujoco/walker2d_v4.py
View File

@@ -2,6 +2,7 @@ import numpy as np
from gym import utils
from gym.envs.mujoco import mujoco_env
from gym.spaces import Box
DEFAULT_CAMERA_CONFIG = {
"trackbodyid": 2,
@@ -182,7 +183,18 @@ class Walker2dEnv(mujoco_env.MujocoEnv, utils.EzPickle):
exclude_current_positions_from_observation
)
mujoco_env.MujocoEnv.__init__(self, "walker2d.xml", 4, **kwargs)
if exclude_current_positions_from_observation:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(17,), dtype=np.float64
)
else:
observation_space = Box(
low=-np.inf, high=np.inf, shape=(18,), dtype=np.float64
)
mujoco_env.MujocoEnv.__init__(
self, "walker2d.xml", 4, observation_space=observation_space, **kwargs
)
@property
def healthy_reward(self):

60
tests/envs/test_mujoco.py
View File

@@ -3,6 +3,7 @@ import pytest
import gym
from gym import envs
from gym.envs.registration import EnvSpec
from tests.envs.utils import mujoco_testing_env_specs
EPS = 1e-6
@@ -37,6 +38,65 @@ def verify_environments_match(
break
EXCLUDE_POS_FROM_OBS = [
"Ant",
"HalfCheetah",
"Hopper",
"Humanoid",
"Swimmer",
"Walker2d",
]
@pytest.mark.parametrize(
"env_spec",
mujoco_testing_env_specs,
ids=[env_spec.id for env_spec in mujoco_testing_env_specs],
)
def test_obs_space_mujoco_environments(env_spec: EnvSpec):
"""Check that the returned observations are contained in the observation space of the environment"""
env = env_spec.make(disable_env_checker=True)
reset_obs = env.reset()
assert env.observation_space.contains(
reset_obs
), f"Obseravtion returned by reset() of {env_spec.id} is not contained in the default observation space {env.observation_space}."
action = env.action_space.sample()
step_obs, _, _, _ = env.step(action)
assert env.observation_space.contains(
step_obs
), f"Obseravtion returned by step(action) of {env_spec.id} is not contained in the default observation space {env.observation_space}."
if env_spec.name in EXCLUDE_POS_FROM_OBS and (
env_spec.version == 4 or env_spec.version == 3
):
env = env_spec.make(
disable_env_checker=True, exclude_current_positions_from_observation=False
)
reset_obs = env.reset()
assert env.observation_space.contains(
reset_obs
), f"Obseravtion of {env_spec.id} is not contained in the default observation space {env.observation_space} when excluding current position from observation."
step_obs, _, _, _ = env.step(action)
assert env.observation_space.contains(
step_obs
), f"Obseravtion returned by step(action) of {env_spec.id} is not contained in the default observation space {env.observation_space} when excluding current position from observation."
# Ant-v4 has the option of including contact forces in the observation space with the use_contact_forces argument
if env_spec.name == "Ant" and env_spec.version == 4:
env = env_spec.make(disable_env_checker=True, use_contact_forces=True)
reset_obs = env.reset()
assert env.observation_space.contains(
reset_obs
), f"Obseravtion of {env_spec.id} is not contained in the default observation space {env.observation_space} when using contact forces."
step_obs, _, _, _ = env.step(action)
assert env.observation_space.contains(
step_obs
), f"Obseravtion returned by step(action) of {env_spec.id} is not contained in the default observation space {env.observation_space} when using contact forces."
MUJOCO_V2_V3_ENVS = [
spec.name
for spec in mujoco_testing_env_specs