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add tests for replanning env & adapt observation space for box pushing & add max_planning_times to replanning tasks

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Hongyi Zhou
2022-11-01 22:51:43 +01:00
parent 4f9b1fad25
commit fd4f9ae0bc
8 changed files with 40 additions and 37 deletions
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fancy_gym/black_box/black_box_wrapper.py
+13 -12
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@@ -23,7 +23,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
replanning_schedule: Optional[
Callable[[np.ndarray, np.ndarray, np.ndarray, np.ndarray, int], bool]] = None,
reward_aggregation: Callable[[np.ndarray], float] = np.sum,
max_replan_times: int = 1,
max_planning_times: int = 1,
desired_conditioning: bool = False
):
"""
@@ -61,8 +61,8 @@ class BlackBoxWrapper(gym.ObservationWrapper):
# self.traj_gen.basis_gn.show_basis(plot=True)
# spaces
# self.return_context_observation = not (learn_sub_trajectories or self.do_replanning)
self.return_context_observation = True
self.return_context_observation = not (learn_sub_trajectories or self.do_replanning)
# self.return_context_observation = True
self.traj_gen_action_space = self._get_traj_gen_action_space()
self.action_space = self._get_action_space()
@@ -82,8 +82,8 @@ class BlackBoxWrapper(gym.ObservationWrapper):
self.condition_pos = None
self.condition_vel = None
self.max_replan_times = max_replan_times
self.replan_counts = 0
self.max_planning_times = max_planning_times
self.plan_counts = 0
def observation(self, observation):
# return context space if we are
@@ -176,7 +176,7 @@ class BlackBoxWrapper(gym.ObservationWrapper):
infos = dict()
done = False
self.replan_counts += 1
self.plan_counts += 1
for t, (pos, vel) in enumerate(zip(position, velocity)):
step_action = self.tracking_controller.get_action(pos, vel, self.current_pos, self.current_vel)
c_action = np.clip(step_action, self.env.action_space.low, self.env.action_space.high)
@@ -197,12 +197,12 @@ class BlackBoxWrapper(gym.ObservationWrapper):
if done or self.replanning_schedule(self.current_pos, self.current_vel, obs, c_action,
t + 1 + self.current_traj_steps):
if self.desired_conditioning:
self.condition_pos = pos
self.condition_vel = vel
else:
self.condition_pos = self.current_pos
self.condition_vel = self.current_vel
if self.max_planning_times is not None and self.plan_counts >= self.max_planning_times:
continue
self.condition_pos = pos if self.desired_conditioning else self.current_pos
self.condition_vel = vel if self.desired_conditioning else self.current_vel
break
@@ -229,5 +229,6 @@ class BlackBoxWrapper(gym.ObservationWrapper):
def reset(self, *, seed: Optional[int] = None, return_info: bool = False, options: Optional[dict] = None):
self.current_traj_steps = 0
self.plan_counts = 0
self.traj_gen.reset()
return super(BlackBoxWrapper, self).reset()