Merge remote-tracking branch 'origin/clean_api' into clean_api

fancy_gym/black_box/black_box_wrapper.py

@@ -50,7 +50,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
         self.tracking_controller = tracking_controller
         # self.time_steps = np.linspace(0, self.duration, self.traj_steps)
         # self.traj_gen.set_mp_times(self.time_steps)
-        self.traj_gen.set_duration(np.array([self.duration]), np.array([self.dt]))
+        self.traj_gen.set_duration(self.duration - self.dt, self.dt)
 
         # reward computation
         self.reward_aggregation = reward_aggregation
@@ -78,8 +78,8 @@ class BlackBoxWrapper(gym.ObservationWrapper):
         self.traj_gen.set_boundary_conditions(
             bc_time=np.array(0) if not self.do_replanning else np.array([self.current_traj_steps * self.dt]),
             bc_pos=self.current_pos, bc_vel=self.current_vel)
-        self.traj_gen.set_duration(None if self.learn_sub_trajectories else np.array([self.duration]),
+        # TODO remove the - self.dt after Bruces fix.
-                                   np.array([self.dt]))
+        self.traj_gen.set_duration(None if self.learn_sub_trajectories else self.duration - self.dt, self.dt)
         traj_dict = self.traj_gen.get_trajs(get_pos=True, get_vel=True)
         trajectory_tensor, velocity_tensor = traj_dict['pos'], traj_dict['vel']
 
@@ -87,7 +87,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
 
     def _get_traj_gen_action_space(self):
         """This function can be used to set up an individual space for the parameters of the traj_gen."""
-        min_action_bounds, max_action_bounds = self.traj_gen.get_param_bounds()
+        min_action_bounds, max_action_bounds = self.traj_gen.get_params_bounds().t()
         action_space = gym.spaces.Box(low=min_action_bounds.numpy(), high=max_action_bounds.numpy(),
                                       dtype=self.env.action_space.dtype)
         return action_space

fancy_gym/black_box/factory/basis_generator_factory.py

@@ -1,5 +1,5 @@
-from mp_pytorch import PhaseGenerator, NormalizedRBFBasisGenerator, ZeroStartNormalizedRBFBasisGenerator
+from mp_pytorch.basis_gn import NormalizedRBFBasisGenerator, ZeroPaddingNormalizedRBFBasisGenerator
-from mp_pytorch.basis_gn.rhytmic_basis import RhythmicBasisGenerator
+from mp_pytorch.phase_gn import PhaseGenerator
 
 ALL_TYPES = ["rbf", "zero_rbf", "rhythmic"]
 
@@ -9,9 +9,10 @@ def get_basis_generator(basis_generator_type: str, phase_generator: PhaseGenerat
     if basis_generator_type == "rbf":
         return NormalizedRBFBasisGenerator(phase_generator, **kwargs)
     elif basis_generator_type == "zero_rbf":
-        return ZeroStartNormalizedRBFBasisGenerator(phase_generator, **kwargs)
+        return ZeroPaddingNormalizedRBFBasisGenerator(phase_generator, **kwargs)
     elif basis_generator_type == "rhythmic":
-        return RhythmicBasisGenerator(phase_generator, **kwargs)
+        raise NotImplementedError()
+        # return RhythmicBasisGenerator(phase_generator, **kwargs)
     else:
         raise ValueError(f"Specified basis generator type {basis_generator_type} not supported, "
                          f"please choose one of {ALL_TYPES}.")

fancy_gym/black_box/factory/phase_generator_factory.py

@@ -1,6 +1,7 @@
-from mp_pytorch import LinearPhaseGenerator, ExpDecayPhaseGenerator
+from mp_pytorch.phase_gn import LinearPhaseGenerator, ExpDecayPhaseGenerator
-from mp_pytorch.phase_gn.rhythmic_phase_generator import RhythmicPhaseGenerator
+
-from mp_pytorch.phase_gn.smooth_phase_generator import SmoothPhaseGenerator
+# from mp_pytorch.phase_gn.rhythmic_phase_generator import RhythmicPhaseGenerator
+# from mp_pytorch.phase_gn.smooth_phase_generator import SmoothPhaseGenerator
 
 ALL_TYPES = ["linear", "exp", "rhythmic", "smooth"]
 
@@ -12,9 +13,11 @@ def get_phase_generator(phase_generator_type, **kwargs):
     elif phase_generator_type == "exp":
         return ExpDecayPhaseGenerator(**kwargs)
     elif phase_generator_type == "rhythmic":
-        return RhythmicPhaseGenerator(**kwargs)
+        raise NotImplementedError()
+        # return RhythmicPhaseGenerator(**kwargs)
     elif phase_generator_type == "smooth":
-        return SmoothPhaseGenerator(**kwargs)
+        raise NotImplementedError()
+        # return SmoothPhaseGenerator(**kwargs)
     else:
         raise ValueError(f"Specified phase generator type {phase_generator_type} not supported, "
                          f"please choose one of {ALL_TYPES}.")

fancy_gym/black_box/factory/trajectory_generator_factory.py

@@ -1,7 +1,5 @@
-from mp_pytorch.basis_gn.basis_generator import BasisGenerator
+from mp_pytorch.basis_gn import BasisGenerator
-from mp_pytorch.mp.dmp import DMP
+from mp_pytorch.mp import ProDMP, DMP, ProMP
-from mp_pytorch.mp.idmp import IDMP
-from mp_pytorch.mp.promp import ProMP
 
 ALL_TYPES = ["promp", "dmp", "idmp"]
 
@@ -14,8 +12,10 @@ def get_trajectory_generator(
         return ProMP(basis_generator, action_dim, **kwargs)
     elif trajectory_generator_type == "dmp":
         return DMP(basis_generator, action_dim, **kwargs)
-    elif trajectory_generator_type == 'idmp':
+    elif trajectory_generator_type == 'prodmp':
-        return IDMP(basis_generator, action_dim, **kwargs)
+        from mp_pytorch.basis_gn import ProDMPBasisGenerator
+        assert isinstance(basis_generator, ProDMPBasisGenerator)
+        return ProDMP(basis_generator, action_dim, **kwargs)
     else:
         raise ValueError(f"Specified movement primitive type {trajectory_generator_type} not supported, "
                          f"please choose one of {ALL_TYPES}.")

fancy_gym/envs/__init__.py

@@ -126,7 +126,7 @@ for _dims in [5, 7]:
     register(
         id=f'Reacher{_dims}dSparse-v0',
         entry_point='fancy_gym.envs.mujoco:ReacherEnv',
-        max_episode_steps=MAX_EPISODE_STEPS_REACHER,
+        max_episode_steps=200,
         kwargs={
             "sparse": True,
             'reward_weight': 200,

fancy_gym/utils/make_env_helpers.py

@@ -10,15 +10,14 @@ import numpy as np
 from gym.envs.registration import register, registry
 
 try:
-    from dm_control import suite, manipulation, composer
+    from dm_control import suite, manipulation
-    from dm_control.rl import control
 except ImportError:
     pass
 
 try:
     import metaworld
 except Exception:
-    # catch Exception due to Mujoco-py
+    # catch Exception as Import error does not catch missing mujoco-py
     pass
 
 import fancy_gym
@@ -227,7 +226,7 @@ def make_bb_env_helper(**kwargs):
 
 
 def make_dmc(
-        env_id: Union[str, composer.Environment, control.Environment],
+        env_id: str,
         seed: int = None,
         visualize_reward: bool = True,
         time_limit: Union[None, float] = None,
@@ -274,7 +273,7 @@ def make_dmc(
     return env
 
 
-def make_metaworld(env_id, seed, **kwargs):
+def make_metaworld(env_id: str, seed: int, **kwargs):
     if env_id not in metaworld.ML1.ENV_NAMES:
         raise ValueError(f'Specified environment "{env_id}" not present in metaworld ML1.')
 

setup.py

@@ -27,8 +27,7 @@ setup(
     ],
     extras_require=extras,
     install_requires=[
-        'gym>=0.24.0',
+        'gym[mujoco]>=0.24.0',
-        'mujoco==2.2.0',
         'mp_pytorch @ git+https://github.com/ALRhub/MP_PyTorch.git@main'
     ],
     packages=[package for package in find_packages() if package.startswith("fancy_gym")],