def log_diagnostics(self, paths, logger=default_logger):
super().log_diagnostics(paths)
MultitaskEnv.log_diagnostics(self, paths)
xvels = get_stat_in_paths(paths, 'env_infos', 'xvel')
desired_xvels = get_stat_in_paths(paths, 'env_infos', 'desired_xvel')
xvel_errors = get_stat_in_paths(paths, 'env_infos', 'xvel_error')
statistics = OrderedDict()
for stat, name in [
(xvels, 'xvels'),
(desired_xvels, 'desired xvels'),
(xvel_errors, 'xvel errors'),
]:
statistics.update(
create_stats_ordered_dict(
'{}'.format(name),
stat,
always_show_all_stats=True,
))
statistics.update(
create_stats_ordered_dict(
'Final {}'.format(name),
[s[-1] for s in stat],
always_show_all_stats=True,
))
for key, value in statistics.items():
logger.record_tabular(key, value)
def log_diagnostics(self, paths, logger=default_logger):
super().log_diagnostics(paths)
MultitaskEnv.log_diagnostics(self, paths)
statistics = OrderedDict()
for name_in_env_infos, name_to_log in [
('x_pos', 'X Position'),
('y_pos', 'Y Position'),
('dist_from_origin', 'Distance from Origin'),
('desired_x_pos', 'Desired X Position'),
('desired_y_pos', 'Desired Y Position'),
('desired_dist_from_origin', 'Desired Distance from Origin'),
('pos_error', 'Distance to goal'),
]:
stat = get_stat_in_paths(paths, 'env_infos', name_in_env_infos)
statistics.update(create_stats_ordered_dict(
name_to_log,
stat,
always_show_all_stats=True,
exclude_max_min=True,
))
for name_in_env_infos, name_to_log in [
('dist_from_origin', 'Distance from Origin'),
('desired_dist_from_origin', 'Desired Distance from Origin'),
('pos_error', 'Distance to goal'),
]:
stat = get_stat_in_paths(paths, 'env_infos', name_in_env_infos)
statistics.update(create_stats_ordered_dict(
'Final {}'.format(name_to_log),
[s[-1] for s in stat],
always_show_all_stats=True,
))
for key, value in statistics.items():
logger.record_tabular(key, value)
def __init__(self, min_distance=0, max_distance=2, use_low_gear_ratio=True):
Serializable.quick_init(self, locals())
self.max_distance = max_distance
self.min_distance = min_distance
MultitaskEnv.__init__(self)
super().__init__(use_low_gear_ratio=use_low_gear_ratio)
self.set_goal(np.array([self.max_distance, self.max_distance]))
def __init__(
self,
max_speed=0.05,
max_distance=1,
use_low_gear_ratio=True,
speed_weight=0.9,
done_threshold=0.005,
goal_dim_weights=None,
):
Serializable.quick_init(self, locals())
self.max_distance = max_distance
self.max_speed = max_speed
self.speed_weight = speed_weight
self.done_threshold = done_threshold
self.initializing = True
# TODO: fix this hack
if speed_weight is None:
self.speed_weight = 0.9 # just for init to work
MultitaskEnv.__init__(self, goal_dim_weights=goal_dim_weights)
super().__init__(use_low_gear_ratio=use_low_gear_ratio)
self.set_goal(np.array([
self.max_distance,
self.max_distance,
self.max_speed,
self.max_speed,
]))
self.initializing = False
if speed_weight is None:
assert (
self.goal_dim_weights[0] == self.goal_dim_weights[1]
) and (
self.goal_dim_weights[2] == self.goal_dim_weights[3]
)
self.speed_weight = self.goal_dim_weights[2]
assert 0 <= self.speed_weight <= 1
def __init__(self, distance_metric_order=None, goal_dim_weights=None):
self._desired_xyz = np.zeros(3)
Serializable.quick_init(self, locals())
MultitaskEnv.__init__(
self,
distance_metric_order=distance_metric_order,
goal_dim_weights=goal_dim_weights,
)
mujoco_env.MujocoEnv.__init__(
self,
get_asset_xml('reacher_7dof.xml'),
5,
)
self.observation_space = Box(
np.array([
-2.28,
-0.52,
-1.4,
-2.32,
-1.5,
-1.094,
-1.5, # joint
-3,
-3,
-3,
-3,
-3,
-3,
-3, # velocity
-0.75,
-1.25,
-0.2, # EE xyz
]),
np.array([
1.71,
1.39,
1.7,
0,
1.5,
0,
1.5, # joints
3,
3,
3,
3,
3,
3,
3, # velocity
0.75,
0.25,
0.6, # EE xyz
]))
def log_diagnostics(self, paths, logger=default_logger):
super().log_diagnostics(paths)
MultitaskEnv.log_diagnostics(self, paths)
statistics = OrderedDict()
for stat_name in [
'pos_error',
'vel_error',
'weighted_pos_error',
'weighted_vel_error',
]:
stat = get_stat_in_paths(paths, 'env_infos', stat_name)
statistics.update(create_stats_ordered_dict(
'{}'.format(stat_name),
stat,
always_show_all_stats=True,
))
statistics.update(create_stats_ordered_dict(
'Final {}'.format(stat_name),
[s[-1] for s in stat],
always_show_all_stats=True,
))
weighted_error = (
get_stat_in_paths(paths, 'env_infos', 'weighted_pos_error')
+ get_stat_in_paths(paths, 'env_infos', 'weighted_vel_error')
)
statistics.update(create_stats_ordered_dict(
"Weighted Error",
weighted_error,
always_show_all_stats=True,
))
statistics.update(create_stats_ordered_dict(
"Final Weighted Error",
[s[-1] for s in weighted_error],
always_show_all_stats=True,
))
for key, value in statistics.items():
logger.record_tabular(key, value)
def set_goal(self, goal):
MultitaskEnv.set_goal(self, goal)
self.target_x_vel = goal
def __init__(self):
Serializable.quick_init(self, locals())
self.target_x_vel = np.random.uniform(-MAX_SPEED, MAX_SPEED)
super().__init__()
MultitaskEnv.__init__(self)
self.set_goal(np.array([5]))