def update_metric(self, *args: Any, episode, action, task: EmbodiedTask,
**kwargs: Any):
current_position = self._sim.get_agent_state().position.tolist()
discrete = getattr(task, "is_discrete")
if discrete:
curr_viewpoint_id = episode.curr_viewpoint.image_id
goal = episode.goals[-1].image_id
scan = episode.scan
distance_to_target = \
task.get_distance_to_target(scan, curr_viewpoint_id, goal)
else:
current_position = self._sim.get_agent_state().position.tolist()
distance_to_target = self._sim.geodesic_distance(
current_position, episode.goals[-1].get_position())
if np.isinf(distance_to_target):
print("WARNING: The Oracle distance might be compromised " +
"The geodesic_distance failed " +
"looking for a snap_point instead")
new_position = np.array(current_position, dtype='f')
new_position = self._sim._sim.pathfinder.snap_point(
new_position)
if np.isnan(new_position[0]):
print("ERROR: The Oracle distance is compromised " +
"The geodesic_distance failed " + "Cannot find path")
else:
current_position = new_position
distance_to_target = self._sim.geodesic_distance(
current_position, episode.goals[-1].get_position())
self._metric = distance_to_target
def update_metric(self, *args: Any, episode, action, task: EmbodiedTask,
**kwargs: Any):
ep_success = 0
current_position = self._sim.get_agent_state().position.tolist()
discrete = getattr(task, "is_discrete")
if discrete:
curr_viewpoint_id = episode.curr_viewpoint.image_id
goal = episode.goals[-1].image_id
scan = episode.scan
distance_to_target = \
task.get_distance_to_target(scan, curr_viewpoint_id, goal)
else:
distance_to_target = self._sim.geodesic_distance(
current_position, episode.goals[-1].get_position())
if np.isinf(distance_to_target):
print("WARNING: The Success metric might be compromised " +
"The geodesic_distance failed " +
"looking for a snap_point instead")
new_position = np.array(current_position, dtype='f')
new_position = self._sim._sim.pathfinder.snap_point(
new_position)
if np.isnan(new_position[0]):
print("ERROR: The Success metric is compromised " +
"The geodesic_distance failed " + "Cannot find path")
else:
current_position = new_position
distance_to_target = self._sim.geodesic_distance(
current_position, episode.goals[-1].get_position())
if (hasattr(task, "is_stop_called") and task.is_stop_called
and distance_to_target < self._config.SUCCESS_DISTANCE):
ep_success = 1
self._agent_episode_distance += self._euclidean_distance(
current_position, self._previous_position)
self._previous_position = current_position
self._metric = ep_success * (self._start_end_episode_distance / max(
self._start_end_episode_distance, self._agent_episode_distance))
# removing rounding error of 0.0000025 meters
if self._metric >= 0.9999975:
self._metric = 1.0
def update_metric(self, *args: Any, episode, task: EmbodiedTask,
**kwargs: Any):
ep_success = 0
discrete = getattr(task, "is_discrete")
if discrete:
curr_viewpoint_id = episode.curr_viewpoint.image_id
goal = episode.goals[-1].image_id
scan = episode.scan
distance_to_target = \
task.get_distance_to_target(scan, curr_viewpoint_id, goal)
else:
current_position = self._sim.get_agent_state().position.tolist()
distance_to_target = self._sim.geodesic_distance(
current_position, episode.goals[-1].get_position())
if np.isinf(distance_to_target):
print("WARNING: The Oracle distance might be compromised " +
"The geodesic_distance failed " +
"looking for a snap_point instead")
new_position = np.array(current_position, dtype='f')
new_position = self._sim._sim.pathfinder.snap_point(
new_position)
if np.isnan(new_position[0]):
print("ERROR: The Oracle distance is compromised " +
"The geodesic_distance failed " + "Cannot find path")
else:
current_position = new_position
distance_to_target = self._sim.geodesic_distance(
current_position, episode.goals[-1].get_position())
if (self._nearest_distance == -1
or distance_to_target < self._nearest_distance):
self._nearest_distance = distance_to_target
if (hasattr(task, "is_stop_called") and task.is_stop_called and
self._nearest_distance < self._config.ORACLE_SUCCESS_DISTANCE):
ep_success = 1
self._metric = ep_success
