fixed seeding and tests

alr_envs/envs/__init__.py

@@ -154,14 +154,14 @@ register(
 )
 
 register(
-    id='ALRAntJump-v0',
+    id='AntJump-v0',
     entry_point='alr_envs.envs.mujoco:AntJumpEnv',
     max_episode_steps=MAX_EPISODE_STEPS_ANTJUMP,
 )
 
 register(
-    id='ALRHalfCheetahJump-v0',
+    id='HalfCheetahJump-v0',
-    entry_point='alr_envs.envs.mujoco:ALRHalfCheetahJumpEnv',
+    entry_point='alr_envs.envs.mujoco:HalfCheetahJumpEnv',
     max_episode_steps=MAX_EPISODE_STEPS_HALFCHEETAHJUMP,
 )
 
@@ -173,19 +173,19 @@ register(
 
 register(
     id='ALRHopperThrow-v0',
-    entry_point='alr_envs.envs.mujoco:ALRHopperThrowEnv',
+    entry_point='alr_envs.envs.mujoco:HopperThrowEnv',
     max_episode_steps=MAX_EPISODE_STEPS_HOPPERTHROW,
 )
 
 register(
     id='ALRHopperThrowInBasket-v0',
-    entry_point='alr_envs.envs.mujoco:ALRHopperThrowInBasketEnv',
+    entry_point='alr_envs.envs.mujoco:HopperThrowInBasketEnv',
     max_episode_steps=MAX_EPISODE_STEPS_HOPPERTHROWINBASKET,
 )
 
 register(
     id='ALRWalker2DJump-v0',
-    entry_point='alr_envs.envs.mujoco:ALRWalker2dJumpEnv',
+    entry_point='alr_envs.envs.mujoco:Walker2dJumpEnv',
     max_episode_steps=MAX_EPISODE_STEPS_WALKERJUMP,
 )
 
@@ -518,7 +518,7 @@ register(
 # CtxtFree are v0, Contextual are v1
 register(
     id='ALRHalfCheetahJump-v0',
-    entry_point='alr_envs.envs.mujoco:ALRHalfCheetahJumpEnv',
+    entry_point='alr_envs.envs.mujoco:HalfCheetahJumpEnv',
     max_episode_steps=MAX_EPISODE_STEPS_HALFCHEETAHJUMP,
     kwargs={
         "max_episode_steps": MAX_EPISODE_STEPS_HALFCHEETAHJUMP,
@@ -626,7 +626,7 @@ for i in _vs:
     )
     register(
     id='ALRHopperThrow-v0',
-    entry_point='alr_envs.envs.mujoco:ALRHopperThrowEnv',
+    entry_point='alr_envs.envs.mujoco:HopperThrowEnv',
     max_episode_steps=MAX_EPISODE_STEPS_HOPPERTHROW,
     kwargs={
         "max_episode_steps": MAX_EPISODE_STEPS_HOPPERTHROW,
@@ -635,7 +635,7 @@ for i in _vs:
     )   
     register(
     id='ALRHopperThrowInBasket-v0',
-    entry_point='alr_envs.envs.mujoco:ALRHopperThrowInBasketEnv',
+    entry_point='alr_envs.envs.mujoco:HopperThrowInBasketEnv',
     max_episode_steps=MAX_EPISODE_STEPS_HOPPERTHROWINBASKET,
     kwargs={
         "max_episode_steps": MAX_EPISODE_STEPS_HOPPERTHROWINBASKET,
@@ -644,7 +644,7 @@ for i in _vs:
     )
     register(
     id='ALRWalker2DJump-v0',
-    entry_point='alr_envs.envs.mujoco:ALRWalker2dJumpEnv',
+    entry_point='alr_envs.envs.mujoco:Walker2dJumpEnv',
     max_episode_steps=MAX_EPISODE_STEPS_WALKERJUMP,
     kwargs={
         "max_episode_steps": MAX_EPISODE_STEPS_WALKERJUMP,

alr_envs/envs/mujoco/__init__.py

@@ -1,9 +1,9 @@
 from .beerpong.beerpong import BeerPongEnv, BeerPongEnvFixedReleaseStep, BeerPongEnvStepBasedEpisodicReward
 from .ant_jump.ant_jump import AntJumpEnv
-from .half_cheetah_jump.half_cheetah_jump import ALRHalfCheetahJumpEnv
+from .half_cheetah_jump.half_cheetah_jump import HalfCheetahJumpEnv
 from .hopper_jump.hopper_jump_on_box import HopperJumpOnBoxEnv
-from .hopper_throw.hopper_throw import ALRHopperThrowEnv
+from .hopper_throw.hopper_throw import HopperThrowEnv
-from .hopper_throw.hopper_throw_in_basket import ALRHopperThrowInBasketEnv
+from .hopper_throw.hopper_throw_in_basket import HopperThrowInBasketEnv
 from .reacher.reacher import ReacherEnv
-from .walker_2d_jump.walker_2d_jump import ALRWalker2dJumpEnv
+from .walker_2d_jump.walker_2d_jump import Walker2dJumpEnv
 from .hopper_jump.hopper_jump import HopperJumpEnv

alr_envs/envs/mujoco/beerpong/deprecated/beerpong.py

@@ -155,7 +155,7 @@ class BeerPongEnvStepBasedEpisodicReward(BeerPongEnv):
         return ob, reward, done, infos
 
 
-# class ALRBeerBongEnvStepBased(ALRBeerBongEnv):
+# class BeerBongEnvStepBased(ALRBeerBongEnv):
 #     def __init__(self, frame_skip=1, apply_gravity_comp=True, noisy=False, rndm_goal=False, cup_goal_pos=None):
 #         super().__init__(frame_skip, apply_gravity_comp, noisy, rndm_goal, cup_goal_pos)
 #         self.release_step = 62  # empirically evaluated for frame_skip=2!

alr_envs/envs/mujoco/half_cheetah_jump/half_cheetah_jump.py

@@ -8,7 +8,7 @@ import numpy as np
 MAX_EPISODE_STEPS_HALFCHEETAHJUMP = 100
 
 
-class ALRHalfCheetahJumpEnv(HalfCheetahEnv):
+class HalfCheetahJumpEnv(HalfCheetahEnv):
     """
     ctrl_cost_weight 0.1 -> 0.0
     """

alr_envs/envs/mujoco/hopper_throw/hopper_throw.py

@@ -7,7 +7,7 @@ import numpy as np
 MAX_EPISODE_STEPS_HOPPERTHROW = 250
 
 
-class ALRHopperThrowEnv(HopperEnv):
+class HopperThrowEnv(HopperEnv):
     """
     Initialization changes to normal Hopper:
     - healthy_reward: 1.0 -> 0.0 -> 0.1
@@ -98,7 +98,7 @@ class ALRHopperThrowEnv(HopperEnv):
 
 if __name__ == '__main__':
     render_mode = "human"  # "human" or "partial" or "final"
-    env = ALRHopperThrowEnv()
+    env = HopperThrowEnv()
     obs = env.reset()
 
     for i in range(2000):

alr_envs/envs/mujoco/hopper_throw/hopper_throw_in_basket.py

@@ -8,7 +8,7 @@ import numpy as np
 MAX_EPISODE_STEPS_HOPPERTHROWINBASKET = 250
 
 
-class ALRHopperThrowInBasketEnv(HopperEnv):
+class HopperThrowInBasketEnv(HopperEnv):
     """
     Initialization changes to normal Hopper:
     - healthy_reward: 1.0 -> 0.0
@@ -130,7 +130,7 @@ class ALRHopperThrowInBasketEnv(HopperEnv):
 
 if __name__ == '__main__':
     render_mode = "human"  # "human" or "partial" or "final"
-    env = ALRHopperThrowInBasketEnv()
+    env = HopperThrowInBasketEnv()
     obs = env.reset()
 
     for i in range(2000):

alr_envs/envs/mujoco/walker_2d_jump/walker_2d_jump.py

@@ -12,7 +12,7 @@ MAX_EPISODE_STEPS_WALKERJUMP = 300
 #  as possible, while landing at a specific target position
 
 
-class ALRWalker2dJumpEnv(Walker2dEnv):
+class Walker2dJumpEnv(Walker2dEnv):
     """
     healthy reward 1.0 -> 0.005 -> 0.0025 not from alex
     penalty 10 -> 0 not from alex
@@ -95,7 +95,7 @@ class ALRWalker2dJumpEnv(Walker2dEnv):
 
 if __name__ == '__main__':
     render_mode = "human"  # "human" or "partial" or "final"
-    env = ALRWalker2dJumpEnv()
+    env = Walker2dJumpEnv()
     obs = env.reset()
 
     for i in range(6000):

alr_envs/examples/pd_control_gain_tuning.py

@@ -1,9 +1,10 @@
+from collections import OrderedDict
+
 import numpy as np
 from matplotlib import pyplot as plt
 
-from alr_envs import dmc, meta
+from alr_envs import make_bb, dmc, meta
 from alr_envs.envs import mujoco
-from alr_envs.utils.make_env_helpers import make_promp_env
 
 
 def visualize(env):
@@ -16,11 +17,12 @@ def visualize(env):
 # This might work for some environments, however, please verify either way the correct trajectory information
 # for your environment are extracted below
 SEED = 1
-# env_id = "ball_in_cup-catch"
+# env_id = "dmc:ball_in_cup-catch"
-env_id = "ALRReacherSparse-v0"
+# wrappers = [dmc.suite.ball_in_cup.MPWrapper]
-env_id = "button-press-v2"
+env_id = "Reacher5dSparse-v0"
 wrappers = [mujoco.reacher.MPWrapper]
-wrappers = [meta.goal_object_change_mp_wrapper.MPWrapper]
+# env_id = "metaworld:button-press-v2"
+# wrappers = [meta.goal_object_change_mp_wrapper.MPWrapper]
 
 mp_kwargs = {
     "num_dof": 4,
@@ -38,7 +40,7 @@ mp_kwargs = {
 # kwargs = dict(time_limit=4, episode_length=200)
 kwargs = {}
 
-env = make_promp_env(env_id, wrappers, seed=SEED, mp_kwargs=mp_kwargs, **kwargs)
+env = make_bb(env_id, wrappers, seed=SEED, mp_kwargs=mp_kwargs, **kwargs)
 env.action_space.seed(SEED)
 
 # Plot difference between real trajectory and target MP trajectory
@@ -59,7 +61,7 @@ img = ax.imshow(env.env.render("rgb_array"))
 fig.show()
 
 for t, pos_vel in enumerate(zip(pos, vel)):
-    actions = env.policy.get_action(pos_vel[0], pos_vel[1],, self.current_vel, self.current_pos
+    actions = env.policy.get_action(pos_vel[0], pos_vel[1], env.current_vel, env.current_pos)
     actions = np.clip(actions, env.full_action_space.low, env.full_action_space.high)
     _, _, _, _ = env.env.step(actions)
     if t % 15 == 0:
@@ -81,7 +83,6 @@ p2 = plt.plot(pos, c='C1', label="MP")  # , label=["MP" if i == 0 else None for
 plt.xlabel("Episode steps")
 # plt.legend()
 handles, labels = plt.gca().get_legend_handles_labels()
-from collections import OrderedDict
 
 by_label = OrderedDict(zip(labels, handles))
 plt.legend(by_label.values(), by_label.keys())

test/test_custom.py

@@ -7,7 +7,7 @@ import alr_envs  # noqa
 from alr_envs.utils.make_env_helpers import make
 
 CUSTOM_IDS = [spec.id for spec in gym.envs.registry.all() if
-              "alr_envs" in spec.entry_point and not 'make_bb_env_helper' in spec.entry_point]
+              "alr_envs" in spec.entry_point and 'make_bb_env_helper' not in spec.entry_point]
 SEED = 1
 
 

test/test_gym.py

@@ -6,7 +6,8 @@ import numpy as np
 import alr_envs
 from alr_envs import make
 
-METAWORLD_IDS = []
+GYM_IDS = [spec.id for spec in gym.envs.registry.all() if
+           "alr_envs" not in spec.entry_point and 'make_bb_env_helper' not in spec.entry_point]
 SEED = 1
 
 
@@ -58,7 +59,7 @@ class TestGymEnvironments(unittest.TestCase):
             if done:
                 break
 
-        assert done, "Done flag is not True after end of episode."
+        assert done or env.spec.max_episode_steps is None, "Done flag is not True after end of episode."
         observations.append(obs)
         env.close()
         del env