added new mp wrappers to all environments
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@ -537,7 +537,7 @@ for _v in _versions:
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register(
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id=_env_id,
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entry_point='alr_envs.utils.make_env_helpers:make_mp_env_helper',
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kwargs=kwargs_dict_bp_promp_fixed_release
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kwargs=kwargs_dict_bp_promp
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)
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ALL_ALR_MOTION_PRIMITIVE_ENVIRONMENTS["ProMP"].append(_env_id)
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########################################################################################################################
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31
alr_envs/alr/classic_control/hole_reacher/new_mp_wrapper.py
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31
alr_envs/alr/classic_control/hole_reacher/new_mp_wrapper.py
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@ -0,0 +1,31 @@
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from typing import Tuple, Union
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import numpy as np
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class NewMPWrapper(RawInterfaceWrapper):
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def get_context_mask(self):
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return np.hstack([
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[self.env.random_start] * self.env.n_links, # cos
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[self.env.random_start] * self.env.n_links, # sin
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[self.env.random_start] * self.env.n_links, # velocity
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[self.env.initial_width is None], # hole width
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# [self.env.hole_depth is None], # hole depth
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[True] * 2, # x-y coordinates of target distance
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[False] # env steps
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_pos
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_vel
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@property
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def dt(self) -> Union[float, int]:
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return self.env.dt
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@ -0,0 +1,31 @@
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from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class MPWrapper(RawInterfaceWrapper):
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def context_mask(self):
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return np.hstack([
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[self.env.random_start] * self.env.n_links, # cos
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[self.env.random_start] * self.env.n_links, # sin
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[self.env.random_start] * self.env.n_links, # velocity
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[True] * 2, # x-y coordinates of target distance
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[False] # env steps
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_pos
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_vel
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@property
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def dt(self) -> Union[float, int]:
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return self.env.dt
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@ -0,0 +1,32 @@
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from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class MPWrapper(RawInterfaceWrapper):
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def context_mask(self):
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return np.hstack([
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[self.env.random_start] * self.env.n_links, # cos
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[self.env.random_start] * self.env.n_links, # sin
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[self.env.random_start] * self.env.n_links, # velocity
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[self.env.initial_via_target is None] * 2, # x-y coordinates of via point distance
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[True] * 2, # x-y coordinates of target distance
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[False] # env steps
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_pos
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.current_vel
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@property
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def dt(self) -> Union[float, int]:
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return self.env.dt
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24
alr_envs/alr/mujoco/half_cheetah_jump/new_mp_wrapper.py
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24
alr_envs/alr/mujoco/half_cheetah_jump/new_mp_wrapper.py
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@ -0,0 +1,24 @@
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from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class MPWrapper(RawInterfaceWrapper):
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def context_mask(self):
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return np.hstack([
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[False] * 17,
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[True] # goal height
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray]:
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return self.env.sim.data.qpos[3:9].copy()
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.sim.data.qvel[3:9].copy()
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@ -10,7 +10,7 @@ class MPWrapper(MPEnvWrapper):
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def active_obs(self):
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return np.hstack([
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[False] * 17,
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[True] # goal pos
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[True] # goal pos
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])
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@property
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27
alr_envs/alr/mujoco/hopper_throw/new_mp_wrapper.py
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alr_envs/alr/mujoco/hopper_throw/new_mp_wrapper.py
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@ -0,0 +1,27 @@
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from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class MPWrapper(RawInterfaceWrapper):
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def context_mask(self):
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return np.hstack([
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[False] * 17,
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[True] # goal pos
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray]:
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return self.env.sim.data.qpos[3:6].copy()
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.sim.data.qvel[3:6].copy()
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@property
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def dt(self) -> Union[float, int]:
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return self.env.dt
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@ -2,8 +2,10 @@ from alr_envs.mp.black_box_wrapper import BlackBoxWrapper
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from typing import Union, Tuple
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import numpy as np
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class MPWrapper(BlackBoxWrapper):
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class MPWrapper(RawInterfaceWrapper):
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@property
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def current_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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@ -12,7 +14,7 @@ class MPWrapper(BlackBoxWrapper):
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.sim.data.qvel.flat[:self.env.n_links]
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def get_context_mask(self):
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def context_mask(self):
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return np.concatenate([
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[False] * self.env.n_links, # cos
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[False] * self.env.n_links, # sin
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@ -21,4 +23,4 @@ class MPWrapper(BlackBoxWrapper):
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[False] * 3, # goal distance
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# self.get_body_com("target"), # only return target to make problem harder
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[False], # step
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])
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])
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28
alr_envs/alr/mujoco/walker_2d_jump/new_mp_wrapper.py
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28
alr_envs/alr/mujoco/walker_2d_jump/new_mp_wrapper.py
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@ -0,0 +1,28 @@
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from typing import Tuple, Union
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import numpy as np
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from mp_env_api import MPEnvWrapper
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from alr_envs.mp.raw_interface_wrapper import RawInterfaceWrapper
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class MPWrapper(RawInterfaceWrapper):
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def context_mask(self):
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return np.hstack([
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[False] * 17,
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[True] # goal pos
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])
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@property
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def current_pos(self) -> Union[float, int, np.ndarray]:
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return self.env.sim.data.qpos[3:9].copy()
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@property
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def current_vel(self) -> Union[float, int, np.ndarray, Tuple]:
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return self.env.sim.data.qvel[3:9].copy()
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@property
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def goal_pos(self) -> Union[float, int, np.ndarray, Tuple]:
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raise ValueError("Goal position is not available and has to be learnt based on the environment.")
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