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Add AntMaze-Ultra #220

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Add AntMaze-Ultra #220

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d3a2d37
update
ZhengyaoJiang May 12, 2022
52666d4
resolve conflict
ZhengyaoJiang May 12, 2022
ea78d54
add autodownload
ZhengyaoJiang May 13, 2022
18bd8a7
antmaze-ultra-v2
imoneoi Feb 11, 2023
9585d13
remove deprecated warning
imoneoi Feb 19, 2023
726eef4
Merge remote-tracking branch 'upstream/master'
imoneoi Aug 27, 2023
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82 changes: 58 additions & 24 deletions d4rl/locomotion/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@
'maze_map': maze_env.U_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_u-maze_noisy_multistart_False_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -46,7 +46,7 @@
'maze_map': maze_env.U_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_u-maze_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -63,7 +63,7 @@
'maze_map': maze_env.BIG_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_big-maze_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -80,7 +80,7 @@
'maze_map': maze_env.BIG_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_big-maze_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -97,7 +97,7 @@
'maze_map': maze_env.HARDEST_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_hardest-maze_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -114,7 +114,7 @@
'maze_map': maze_env.HARDEST_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_hardest-maze_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -131,7 +131,7 @@
'maze_map': maze_env.U_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v1/Ant_maze_umaze_noisy_multistart_False_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -148,7 +148,7 @@
'maze_map': maze_env.U_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v1/Ant_maze_umaze_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -165,7 +165,7 @@
'maze_map': maze_env.BIG_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v1/Ant_maze_medium_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -182,7 +182,7 @@
'maze_map': maze_env.BIG_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v1/Ant_maze_medium_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -199,7 +199,7 @@
'maze_map': maze_env.HARDEST_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v1/Ant_maze_large_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -216,7 +216,7 @@
'maze_map': maze_env.HARDEST_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v1/Ant_maze_large_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -232,7 +232,7 @@
'maze_map': maze_env.U_MAZE_EVAL_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_umaze_eval_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -248,7 +248,7 @@
'maze_map': maze_env.U_MAZE_EVAL_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_umaze_eval_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -264,7 +264,7 @@
'maze_map': maze_env.BIG_MAZE_EVAL_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_medium_eval_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -280,7 +280,7 @@
'maze_map': maze_env.BIG_MAZE_EVAL_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_medium_eval_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -296,7 +296,7 @@
'maze_map': maze_env.HARDEST_MAZE_EVAL_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_large_eval_noisy_multistart_True_multigoal_False_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -312,7 +312,7 @@
'maze_map': maze_env.HARDEST_MAZE_EVAL_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_new/Ant_maze_large_eval_noisy_multistart_True_multigoal_True_sparse.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -329,7 +329,7 @@
'maze_map': maze_env.U_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v2/Ant_maze_u-maze_noisy_multistart_False_multigoal_False_sparse_fixed.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -346,7 +346,7 @@
'maze_map': maze_env.U_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v2/Ant_maze_u-maze_noisy_multistart_True_multigoal_True_sparse_fixed.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -363,7 +363,7 @@
'maze_map': maze_env.BIG_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v2/Ant_maze_big-maze_noisy_multistart_True_multigoal_False_sparse_fixed.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -380,7 +380,7 @@
'maze_map': maze_env.BIG_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v2/Ant_maze_big-maze_noisy_multistart_True_multigoal_True_sparse_fixed.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -397,7 +397,7 @@
'maze_map': maze_env.HARDEST_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v2/Ant_maze_hardest-maze_noisy_multistart_True_multigoal_True_sparse_fixed.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand All @@ -414,7 +414,41 @@
'maze_map': maze_env.HARDEST_MAZE_TEST,
'reward_type':'sparse',
'dataset_url':'http://rail.eecs.berkeley.edu/datasets/offline_rl/ant_maze_v2/Ant_maze_hardest-maze_noisy_multistart_True_multigoal_False_sparse_fixed.hdf5',
'non_zero_reset':False,
'non_zero_reset':False,
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
'ref_max_score': 1.0,
'v2_resets': True,
}
)

register(
id='antmaze-ultra-diverse-v2',
entry_point='d4rl.locomotion.ant:make_ant_maze_env',
max_episode_steps=2000,
kwargs={
'maze_map': maze_env.ULTRA_MAZE_TEST,
'reward_type':'sparse',
'non_zero_reset':False,
'dataset_url':'https://github.com/ZhengyaoJiang/d4rl/releases/download/public/Ant_maze_ultra_noisy_multistart_True_multigoal_True_sparse.hdf5',
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
'ref_max_score': 1.0,
'v2_resets': True,
}
)

register(
id='antmaze-ultra-play-v2',
entry_point='d4rl.locomotion.ant:make_ant_maze_env',
max_episode_steps=2000,
kwargs={
'maze_map': maze_env.ULTRA_MAZE_TEST,
'reward_type':'sparse',
'non_zero_reset':False,
'dataset_url':'https://github.com/ZhengyaoJiang/d4rl/releases/download/public/Ant_maze_ultra_noisy_multistart_True_multigoal_False_sparse.hdf5',
'eval':True,
'maze_size_scaling': 4.0,
'ref_min_score': 0.0,
Expand Down
49 changes: 42 additions & 7 deletions d4rl/locomotion/maze_env.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -52,13 +52,30 @@
[1, 0, 0, 1, G, 0, G, 1, 0, G, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]

ULTRA_MAZE = [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, R, 0, 0, G, 0, 0, 0, 1, 0, 0, G, 0, 0, G, 1],
[1, 0, 1, 1, 1, G, 1, 0, 1, G, 1, 1, 0, 1, 0, 1],
[1, 0, 1, 1, 1, 0, 1, G, 0, 0, 0, 1, 0, 1, 0, 1],
[1, 0, 0, G, 1, 0, 1, 1, 0, 1, 1, 1, G, 1, 0, 1],
[1, G, 1, 0, 0, 0, 1, G, 0, 0, G, 0, 0, 0, G, 1],
[1, 0, 0, 0, 1, G, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1],
[1, 0, 1, G, 1, 1, 1, 0, 1, 0, 0, G, 1, 0, 1, 1],
[1, G, 0, 0, 0, 0, 0, G, 1, 0, 1, 0, 0, G, 0, 1],
[1, 1, 0, 1, 1, G, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1],
[1, 1, 0, 1, 0, 0, 1, 0, 1, G, 0, 0, 0, 0, G, 1],
[1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1]]




# Maze specifications with a single target goal
U_MAZE_TEST = [[1, 1, 1, 1, 1],
[1, R, 0, 0, 1],
[1, 1, 1, 0, 1],
[1, G, 0, 0, 1],
[1, 1, 1, 1, 1]]

# effective size 6*6
BIG_MAZE_TEST = [[1, 1, 1, 1, 1, 1, 1, 1],
[1, R, 0, 1, 1, 0, 0, 1],
[1, 0, 0, 1, 0, 0, 0, 1],
Expand All @@ -68,6 +85,7 @@
[1, 0, 0, 0, 1, 0, G, 1],
[1, 1, 1, 1, 1, 1, 1, 1]]

# effective size 7*10
HARDEST_MAZE_TEST = [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, R, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1],
[1, 0, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1],
Expand All @@ -78,6 +96,21 @@
[1, 0, 0, 1, 0, 0, 0, 1, 0, G, 0, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]

# effective size 14*14 -> 10*14
ULTRA_MAZE_TEST = [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, R, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1],
[1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1],
[1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1],
[1, 0, 0, 0, 1, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 1],
[1, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1],
[1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1],
[1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1],
[1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1],
[1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1],
[1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, G, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]


# Maze specifications for evaluation
U_MAZE_EVAL = [[1, 1, 1, 1, 1],
[1, 0, 0, R, 1],
Expand Down Expand Up @@ -208,8 +241,8 @@ def __init__(
def _xy_to_rowcol(self, xy):
size_scaling = self._maze_size_scaling
xy = (max(xy[0], 1e-4), max(xy[1], 1e-4))
return (int(1 + (xy[1]) / size_scaling),
int(1 + (xy[0]) / size_scaling))
return (int((xy[1]+self._init_torso_y+0.25*size_scaling) / size_scaling),
int((xy[0]+self._init_torso_x+0.25*size_scaling) / size_scaling))

def _get_reset_location(self,):
prob = (1.0 - self._np_maze_map) / np.sum(1.0 - self._np_maze_map)
Expand All @@ -226,11 +259,11 @@ def _get_reset_location(self,):

def _rowcol_to_xy(self, rowcol, add_random_noise=False):
row, col = rowcol
x = col * self._maze_size_scaling - self._init_torso_x
y = row * self._maze_size_scaling - self._init_torso_y
x = col * self._maze_size_scaling - self._init_torso_x - 0.125*self._maze_size_scaling
y = row * self._maze_size_scaling - self._init_torso_y - 0.125*self._maze_size_scaling
if add_random_noise:
x = x + np.random.uniform(low=0, high=self._maze_size_scaling * 0.25)
y = y + np.random.uniform(low=0, high=self._maze_size_scaling * 0.25)
x = x + np.random.uniform(low=0, high=self._maze_size_scaling * 0.25) - 0.125*self._maze_size_scaling
y = y + np.random.uniform(low=0, high=self._maze_size_scaling * 0.25) - 0.125*self._maze_size_scaling
return (x, y)

def goal_sampler(self, np_random, only_free_cells=True, interpolate=True):
Expand Down Expand Up @@ -313,6 +346,8 @@ def _get_best_next_rowcol(self, current_rowcol, target_rowcol):

visited = {}
to_visit = [target_rowcol]
if self._maze_map[current_rowcol[0]][current_rowcol[1]] not in [0, RESET, GOAL]:
print()
while to_visit:
next_visit = []
for rowcol in to_visit:
Expand All @@ -337,7 +372,7 @@ def _get_best_next_rowcol(self, current_rowcol, target_rowcol):
next_visit.append(next_rowcol)
to_visit = next_visit

raise ValueError('No path found to target.')
raise ValueError(f'No path found from {current_rowcol} to targe {target_rowcol}.')

def create_navigation_policy(self,
goal_reaching_policy_fn,
Expand Down
10 changes: 9 additions & 1 deletion scripts/generation/generate_ant_maze_datasets.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -75,6 +75,8 @@ def main():
maze = maze_env.BIG_MAZE
elif args.maze == 'large':
maze = maze_env.HARDEST_MAZE
elif args.maze == 'ultra':
maze = maze_env.ULTRA_MAZE
elif args.maze == 'umaze_eval':
maze = maze_env.U_MAZE_EVAL
elif args.maze == 'medium_eval':
Expand Down Expand Up @@ -124,7 +126,13 @@ def _goal_reaching_policy_fn(obs, goal):
ts = 0
num_episodes = 0
for _ in range(args.num_samples):
act, waypoint_goal = data_collection_policy(s)
try:
act, waypoint_goal = data_collection_policy(s)
except Exception as e:
print(e)
#curr_frame = env.physics.render(width=500, height=500, depth=False)
#frames = np.array([curr_frame])
#save_video('./videos/', args.env + '_navigation', frames, num_episodes)

if args.noisy:
act = act + np.random.randn(*act.shape)*0.2
Expand Down