sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
E ->>+ BP : __init__(action_space, file_name, file_names_per_episode, ...)
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- E :
E ->>+ BP : pre_episode
BP -->>- E :
E ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ BP : dynamic_call
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : get_next_amount(action)
BP -->>- MS : action, amount
end
MS ->>+ BP : post_action(action, amount)
BP -->>- MS :
MS -->>- E : action, amount
E ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- E :
Last active
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tbp.monty sequence diagrams
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant DL as InformedEnvironmentDataLoader
participant GPOOS as get_perc_on_obj_semantic
E ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->>+ Dataset : reset
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
DL ->>+ Dataset : env._agents[0].action_space_type
Dataset -->>- DL : action_space_type
alt not action_space_type == "surface_agent"
DL ->> DL : get_good_view("view_finder")
activate DL
DL -->> DL : See details of get_good_view below within __next__ call
deactivate DL
end
deactivate DL
DL -->>- E :
E ->>+ DL : __iter__
DL -->>- E :
E ->>+ DL : __next__
alt _counter=0
DL ->> DL : first_step
activate DL
DL ->> BP : state[agent_id]["motor_only_step"]=isinstance(MotorSystem, SurfacePolicy)
DL -->> E : i, observation
deactivate DL
else
DL ->>+ IP : use_goal_state_driven_actions
IP -->>- DL : use_goal_state_driven_actions?
DL ->>+ JTGM : driving_goal_state
JTGM -->>- DL : driving_goal_state?
alt use_goal_state_driven_actions and driving_goal_state is not None
DL ->> DL : execute_jump_attempt
activate DL
DL ->>+ BP : state
BP -->>- DL : state
DL ->>+ JTGM : derive_habitat_goal_state
alt driving_goal_state is not None
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->> DL : target_loc, target_quat
else
JTGM -->> DL : None, None
end
deactivate JTGM
DL ->>+ Dataset : __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset : __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : get_depth_at_center(observation, ...)
IP -->>- DL :
alt depth_at_center < 1.0
DL ->> DL : handle_successful_jump
activate DL
DL ->> DL : get_good_view("view_finder")
activate DL
alt num_distractors > 0
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
end
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
loop while not close_enough
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
end
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
deactivate DL
deactivate DL
else
DL ->> DL : handle_failed_jump
activate DL
DL ->>+ Dataset: __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset: __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ BP : state
BP -->>- DL : state
deactivate DL
end
DL ->> BP : state[agent_id]["motor_only_step"]=True
DL ->>+ BP : action
BP -->>- DL : action
DL ->>+ IP : post_action(action, 0)
IP -->>- DL :
DL -->> E : i, observation
deactivate DL
else
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ IP : dynamic_call
IP ->>+ BP : last_action
BP -->>- IP : last_action, last_amount
IP ->>+ PO : get_on_object
PO -->>- IP : on_object?
alt not on_object
IP -->> MS : last_action, -last_amount
else
IP ->>+ BP : dynamic_call
BP ->> BP : get_random_action(action)
BP ->> BP : get_next_amount(action)
BP -->>- IP : action, amount
IP -->> MS: action, amount
end
deactivate IP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
alt "orient" in action or "tangentially" in action
DL ->> DL : update_habitat_sim_constraint
activate DL
DL --x CRASH : get_next_constraint
deactivate DL
else
DL ->>+ Dataset: __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=True|False
end
DL -->>- E : i, observation
end
end
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant NSP as NaiveScanPolicy
participant DL as InformedEnvironmentDataLoader
participant GPOOS as get_perc_on_obj_semantic
E ->>+ NSP : __init__
NSP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- NSP :
NSP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ NSP : pre_episode
NSP ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- NSP :
NSP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->>+ Dataset : reset
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
DL ->>+ Dataset : env._agents[0].action_space_type
Dataset -->>- DL : action_space_type
alt not action_space_type == "surface_agent"
DL ->> DL : get_good_view("view_finder")
activate DL
DL -->> DL : See details of get_good_view below within __next__ call
deactivate DL
end
deactivate DL
DL -->>- E :
E ->>+ DL : __iter__
DL -->>- E :
E ->>+ DL : __next__
alt _counter=0
DL ->> DL : first_step
activate DL
DL ->> BP : state[agent_id]["motor_only_step"]=isinstance(MotorSystem, SurfacePolicy)
DL -->> E : i, observation
deactivate DL
else
DL ->>+ IP : use_goal_state_driven_actions
IP -->>- DL : use_goal_state_driven_actions?
DL ->>+ JTGM : driving_goal_state
JTGM -->>- DL : driving_goal_state?
alt use_goal_state_driven_actions and driving_goal_state is not None
DL ->> DL : execute_jump_attempt
activate DL
DL ->>+ BP : state
BP -->>- DL : state
DL ->>+ JTGM : derive_habitat_goal_state
alt driving_goal_state is not None
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->> DL : target_loc, target_quat
else
JTGM -->> DL : None, None
end
deactivate JTGM
DL ->>+ Dataset : __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset : __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : get_depth_at_center(observation, ...)
IP -->>- DL :
alt depth_at_center < 1.0
DL ->> DL : handle_successful_jump
activate DL
DL ->> DL : get_good_view("view_finder")
activate DL
alt num_distractors > 0
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
end
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
loop while not close_enough
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
end
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
deactivate DL
deactivate DL
else
DL ->> DL : handle_failed_jump
activate DL
DL ->>+ Dataset: __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset: __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ BP : state
BP -->>- DL : state
deactivate DL
end
DL ->> BP : state[agent_id]["motor_only_step"]=True
DL ->>+ BP : action
BP -->>- DL : action
DL ->>+ IP : post_action(action, 0)
IP -->>- DL :
DL -->> E : i, observation
deactivate DL
else
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ NSP : dynamic_call
alt steps_per_action * fixed_amount >= 90
NSP -->> DL : StopIteration
else
NSP ->> NSP : check_cycle_action
NSP -->> MS : action, amount
end
deactivate NSP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
alt "orient" in action or "tangentially" in action
DL ->> DL : update_habitat_sim_constraint
activate DL
DL --x CRASH : get_next_constraint
deactivate DL
else
DL ->>+ Dataset: __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=True|False
end
DL -->>- E : i, observation
end
end
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant SP as SurfacePolicy
participant DL as InformedEnvironmentDataLoader
participant GPOOS as get_perc_on_obj_semantic
E ->>+ SP : __init__
SP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->>+ SP : get_next_amount(action)
alt no processed_observations
SP -->> SP : None
end
SP -->>- BP :
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- SP :
SP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->>+ Dataset : reset
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
DL ->>+ Dataset : env._agents[0].action_space_type
Dataset -->>- DL : action_space_type
alt not action_space_type == "surface_agent"
DL ->> DL : get_good_view("view_finder")
activate DL
alt num_distractors > 0
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
end
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
loop while not close_enough
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
end
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
deactivate DL
end
deactivate DL
DL -->>- E :
E ->>+ DL : __iter__
DL -->>- E :
E ->>+ DL : __next__
alt _counter=0
DL ->> DL : first_step
activate DL
DL ->> BP : state[agent_id]["motor_only_step"]=isinstance(MotorSystem, SurfacePolicy)
DL -->> E : i, observation
deactivate DL
else
DL ->>+ IP : use_goal_state_driven_actions
IP -->>- DL : use_goal_state_driven_actions?
DL ->>+ JTGM : driving_goal_state
JTGM -->>- DL : driving_goal_state?
alt use_goal_state_driven_actions and driving_goal_state is not None
DL ->> DL : execute_jump_attempt
activate DL
DL ->>+ BP : state
BP -->>- DL : state
DL ->>+ JTGM : derive_habitat_goal_state
alt driving_goal_state is not None
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->> DL : target_loc, target_quat
else
JTGM -->> DL : None, None
end
deactivate JTGM
DL ->>+ Dataset : __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset : __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : get_depth_at_center(observation, ...)
IP -->>- DL :
alt depth_at_center < 1.0
DL ->> DL : handle_successful_jump
activate DL
DL ->>+ BP : action=agent_id+".move_tangentially"
DL --x CRASH : action_details.append
deactivate DL
else
DL ->> DL : handle_failed_jump
activate DL
DL ->>+ Dataset: __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset: __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ BP : state
BP -->>- DL : state
deactivate DL
end
DL ->> BP : state[agent_id]["motor_only_step"]=True
DL ->>+ BP : action
BP -->>- DL : action
DL ->>+ IP : post_action(action, 0)
IP -->>- DL :
DL -->> E : i, observation
deactivate DL
else
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ SP : dynamic_call
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverate < 0.1
SP -->> MS : None, None
else action is None
SP ->> SP : action=agent_id+".move_forward"
SP ->> SP : get_next_action
activate SP
SP ->>+ BP : last_action
BP -->>- SP : last_action, last_amount
alt "move_forward" in last_action
SP -->> SP : "orient_horizontal"
else "orient_horizontal" in last_action
SP -->> SP : "orient_vertical"
else "orient_vertical" in last_action
SP -->> SP : "move_tangentially"
else "move_tangentially" in last_action
SP ->>+ PO : get_on_object
PO -->>- SP : on_object?
alt if not on_object
SP -->> SP : "orient_horizontal"
else
SP -->> SP : "move_forward"
end
end
deactivate SP
SP ->> SP : get_next_amount(action)
activate SP
alt no processed_observations
SP -->> SP : None
end
alt "move_tangentially" in action
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverage < 0.2
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
SP -->> SP : amount / (4 / object_coverage)
else object_coverage < 0.75
SP -->> SP : amount / 4
else
SP -->> SP : amount
end
end
deactivate SP
SP -->> MS: action, amount
end
deactivate SP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
alt action is None
DL ->>+ SP : touch_object
SP ->>+ IP : get_depth_at_center
IP -->>- SP :
SP -->>- DL : action, amount, constraint
DL ->> Dataset: env._env._sim.agents[0].agent_config.action_space[self._action].actuation.constraint=constraint
DL ->> BP : state[agent_id]["motor_only_step"]=True
else "orient" in action or "tangentially" in action
DL ->> DL : update_habitat_sim_constraint
activate DL
DL ->>+ SP : get_next_constraint
SP ->>+ PO : non_morphological_features["mean_depth"]
PO -->>- SP : depth
SP -->>- DL : constraint
DL ->> Dataset: env._env._sim.agents[0].agent_config.action_space[self._action].actuation.constraint=constraint
deactivate DL
else
DL ->>+ Dataset: __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=True|False
end
DL -->>- E : i, observation
end
end
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant SP as SurfacePolicy
participant SPCI as SurfacePolicyCurvatureInformed
participant DL as InformedEnvironmentDataLoader
participant GPOOS as get_perc_on_obj_semantic
E ->>+ SPCI : __init__
SPCI ->>+ SP : __init__
SP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->>+ SP : get_next_amount(action)
alt no processed_observations
SP -->> SP : None
end
SP -->>- BP :
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- SP :
SP -->>- SPCI :
SPCI -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ SPCI : pre_episode
SPCI ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- SPCI :
SPCI -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->>+ Dataset : reset
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
DL ->>+ Dataset : env._agents[0].action_space_type
Dataset -->>- DL : action_space_type
alt not action_space_type == "surface_agent"
DL ->> DL : get_good_view("view_finder")
activate DL
alt num_distractors > 0
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
end
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
loop while not close_enough
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
end
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
deactivate DL
end
deactivate DL
DL -->>- E :
E ->>+ DL : __iter__
DL -->>- E :
E ->>+ DL : __next__
alt _counter=0
DL ->> DL : first_step
activate DL
DL ->> BP : state[agent_id]["motor_only_step"]=isinstance(MotorSystem, SurfacePolicy)
DL -->> E : i, observation
deactivate DL
else
DL ->>+ IP : use_goal_state_driven_actions
IP -->>- DL : use_goal_state_driven_actions?
DL ->>+ JTGM : driving_goal_state
JTGM -->>- DL : driving_goal_state?
alt use_goal_state_driven_actions and driving_goal_state is not None
DL ->> DL : execute_jump_attempt
activate DL
DL ->>+ BP : state
BP -->>- DL : state
DL ->>+ JTGM : derive_habitat_goal_state
alt driving_goal_state is not None
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->> DL : target_loc, target_quat
else
JTGM -->> DL : None, None
end
deactivate JTGM
DL ->>+ Dataset : __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset : __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : get_depth_at_center(observation, ...)
IP -->>- DL :
alt depth_at_center < 1.0
DL ->> DL : handle_successful_jump
activate DL
DL ->>+ BP : action=agent_id+".move_tangentially"
DL ->> DL : action_details.append
deactivate DL
else
DL ->> DL : handle_failed_jump
activate DL
DL ->>+ Dataset: __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset: __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ BP : state
BP -->>- DL : state
deactivate DL
end
DL ->> BP : state[agent_id]["motor_only_step"]=True
DL ->>+ BP : action
BP -->>- DL : action
DL ->>+ IP : post_action(action, 0)
IP -->>- DL :
DL -->> E : i, observation
deactivate DL
else
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ SP : dynamic_call
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverate < 0.1
SP -->> MS : None, None
else action is None
SP ->> SP : action=agent_id+".move_forward"
SP ->> SP : get_next_action
activate SP
SP ->>+ BP : last_action
BP -->>- SP : last_action, last_amount
alt "move_forward" in last_action
SP -->> SP : "orient_horizontal"
else "orient_horizontal" in last_action
SP -->> SP : "orient_vertical"
else "orient_vertical" in last_action
SP -->> SP : "move_tangentially"
else "move_tangentially" in last_action
SP ->>+ PO : get_on_object
PO -->>- SP : on_object?
alt if not on_object
SP -->> SP : "orient_horizontal"
else
SP -->> SP : "move_forward"
end
end
deactivate SP
SP ->> SP : get_next_amount(action)
activate SP
alt no processed_observations
SP -->> SP : None
end
alt "move_tangentially" in action
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverage < 0.2
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
SP -->> SP : amount / (4 / object_coverage)
else object_coverage < 0.75
SP -->> SP : amount / 4
else
SP -->> SP : amount
end
end
deactivate SP
SP -->> MS: action, amount
end
deactivate SP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
alt action is None
DL ->>+ SP : touch_object
SP ->>+ IP : get_depth_at_center
IP -->>- SP :
SP -->>- DL : action, amount, constraint
DL ->> Dataset: env._env._sim.agents[0].agent_config.action_space[self._action].actuation.constraint=constraint
DL ->> BP : state[agent_id]["motor_only_step"]=True
else "orient" in action or "tangentially" in action
DL ->> DL : update_habitat_sim_constraint
activate DL
DL ->>+ SPCI : get_next_constraint(action, amount)
alt "move_tangentially" in action
SPCI ->>+ PO : get_feature_by_name("pose_fully_defined")
PO -->>- SPCI : pose_fully_defined?
alt pose_fully_defined and ignoring_pc_counter >= min_general_steps
SPCI ->> SPCI : perform_pc_guided_step
activate SPCI
SPCI ->> SPCI : check_for_preference_change
SPCI ->> SPCI : determine_pc_for_use
activate SPCI
SPCI ->>+ PO : get_feature_by_name("principal_curvatures")
PO -->>- SPCI : principal_curvatures
deactivate SPCI
SPCI ->>+ PO : get_curvature_directions
PO -->>- SPCI : curvature_directions
SPCI ->> SPCI : get_inverse_agent_rot
alt int(np.argmax(np.abs(rotated_form))) == int(2)
SPCI ->> SPCI : perform_standard_tang_step
end
SPCI ->> SPCI : update_tangential_reps
SPCI ->> SPCI : check_for_flipped_pc
SPCI ->> SPCI : avoid_revisiting_locations
deactivate SPCI
end
end
SPCI -->>- DL : constraint
DL ->> Dataset: env._env._sim.agents[0].agent_config.action_space[self._action].actuation.constraint=constraint
deactivate DL
else
DL ->>+ Dataset: __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=True|False
end
DL -->>- E : i, observation
end
end
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
NOTE: TouchPolicy's touch_object is never invoked because isinstance(TouchPolicy, SurfacePolicy) -> False
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant TP as TouchPolicy
participant DL as InformedEnvironmentDataLoader
participant GPOOS as get_perc_on_obj_semantic
E ->>+ TP : __init__
TP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->>+ TP : get_next_amount(action)
TP -->>- BP : None
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- TP :
TP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ TP : pre_episode
TP ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- TP :
TP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->>+ Dataset : reset
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
DL ->>+ Dataset : env._agents[0].action_space_type
Dataset -->>- DL : action_space_type
alt not action_space_type == "surface_agent"
DL ->> DL : get_good_view("view_finder")
activate DL
DL -->> DL : See details of get_good_view below within __next__ call
deactivate DL
end
deactivate DL
DL -->>- E :
E ->>+ DL : __iter__
DL -->>- E :
E ->>+ DL : __next__
alt _counter=0
DL ->> DL : first_step
activate DL
DL ->> BP : state[agent_id]["motor_only_step"]=isinstance(MotorSystem, SurfacePolicy)
DL -->> E : i, observation
deactivate DL
else
DL ->>+ IP : use_goal_state_driven_actions
IP -->>- DL : use_goal_state_driven_actions?
DL ->>+ JTGM : driving_goal_state
JTGM -->>- DL : driving_goal_state?
alt use_goal_state_driven_actions and driving_goal_state is not None
DL ->> DL : execute_jump_attempt
activate DL
DL ->>+ BP : state
BP -->>- DL : state
DL ->>+ JTGM : derive_habitat_goal_state
alt driving_goal_state is not None
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->> DL : target_loc, target_quat
else
JTGM -->> DL : None, None
end
deactivate JTGM
DL ->>+ Dataset : __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset : __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ TP : get_depth_at_center(observation, ...)
TP -->>- DL :
alt depth_at_center < 1.0
DL ->> DL : handle_successful_jump
activate DL
DL ->> DL : get_good_view("view_finder")
activate DL
alt num_distractors > 0
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
end
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
loop while not close_enough
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ IP : move_close_enough
IP ->>+ GPOOS : __call__(view, target_semantic_id)
GPOOS -->>- IP : perc_on_target_obj
IP -->>- DL : action, amount, close_enough
end
DL ->>+ IP : search_for_object
IP ->>+ BP : get_agent_state
BP -->>- IP : state
IP -->>- DL : actions, amounts, on_object
alt not on_object
loop actions, amounts
DL ->>+ Dataset : __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
end
end
deactivate DL
deactivate DL
else
DL ->> DL : handle_failed_jump
activate DL
DL ->>+ Dataset: __getitem__(agent_id + ".set_agent_pose", target_amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ Dataset: __getitem__(agent_id + ".set_sensor_rotation", quaternion.one)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->>+ BP : state
BP -->>- DL : state
deactivate DL
end
DL ->> BP : state[agent_id]["motor_only_step"]=True
DL ->>+ BP : action
BP -->>- DL : action
DL ->>+ IP : post_action(action, 0)
IP -->>- DL :
DL -->> E : i, observation
deactivate DL
else
DL ->>+ TP : __call__
TP ->> TP : get_next_action
activate TP
TP ->>+ BP : last_action
BP -->>- TP : action, amount
alt "move_tangentially" in action
TP ->>+ PO : ["features"]["on_object"]
PO -->>- TP : on_object?
end
deactivate TP
TP ->> TP : get_next_amount(action)
activate TP
alt
TP ->>+ PO : features
PO -->>- TP :
end
deactivate TP
TP ->>+ IP : post_action(action, amount)
IP -->>- TP :
TP -->>- DL : action, amount
alt "orient" in action or "tangentially" in action
DL ->> DL : update_habitat_sim_constraint
activate DL
DL ->>+ TP : get_next_constraint
TP ->>+ PO : ["features"]["depth"]
PO -->>- TP : depth
TP -->>- DL : constraint
DL ->> Dataset : env._env._sim.agents[0].agent_config.action_space[self._action].actuation.constraint=constraint
deactivate DL
else
DL ->>+ Dataset: __getitem__(action, amount)
Dataset -->>- DL : observation, state
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=True|False
end
DL -->>- E : i, observation
end
end
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
E ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- E :
E ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ IP : dynamic_call
IP ->>+ BP : last_action
BP -->>- IP : last_action, last_amount
IP ->>+ PO : get_on_object
PO -->>- IP : on_object?
alt not on_object
IP -->> MS : last_action, -last_amount
else
IP ->>+ BP : dynamic_call
BP ->> BP : get_random_action(action)
BP ->> BP : get_next_amount(action)
BP -->>- IP : action, amount
IP -->> MS: action, amount
end
deactivate IP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- E : action, amount
E ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant NSP as NaiveScanPolicy
participant DL as DataLoader
E ->>+ NSP : __init__
NSP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- NSP :
NSP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ NSP : pre_episode
NSP ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- NSP :
NSP -->>- E :
E ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ NSP : dynamic_call
alt if steps_per_action * fixed_amount >= 90
NSP -->> DL : StopIteration
else
NSP ->> NSP : check_cycle_action
NSP -->> MS : action, amount
end
deactivate NSP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- E : action, amount
E ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant DL as OmniglotDataLoader
E ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
deactivate DL
DL -->>- E :
E ->>+ DL : __iter__
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
DL -->>- E :
E ->>+ DL : __next__
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ IP : dynamic_call
IP ->>+ BP : last_action
BP -->>- IP : last_action, last_amount
IP ->>+ PO : get_on_object
PO -->>- IP : on_object?
alt not on_object
IP -->> MS : last_action, -last_amount
else
IP ->>+ BP : dynamic_call
BP ->> BP : get_random_action(action)
BP ->> BP : get_next_amount(action)
BP -->>- IP : action, amount
IP -->> MS: action, amount
end
deactivate IP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
DL ->> BP : state=state
DL -->>- E : i, observation
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant DL as SaccadeOnImageDataLoader
E ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
deactivate DL
DL -->>- E :
E ->>+ DL : __next__
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ IP : dynamic_call
IP ->>+ BP : last_action
BP -->>- IP : last_action, last_amount
IP ->>+ PO : get_on_object
PO -->>- IP : on_object?
alt not on_object
IP -->> MS : last_action, -last_amount
else
IP ->>+ BP : dynamic_call
BP ->> BP : get_random_action(action)
BP ->> BP : get_next_amount(action)
BP -->>- IP : action, amount
IP -->> MS: action, amount
end
deactivate IP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
DL ->> BP : state=state
DL -->>- E : i, observation
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant DL as SaccadeOnImageFromStreamDataLoader
E ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->> BP : get_next_amount(action)
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ DL : pre_episode
DL ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- DL :
DL ->> DL : reset_agent
activate DL
DL ->> BP : state=state
DL ->> BP : state[agent_id]["motor_only_step"]=False
deactivate DL
DL -->>- E :
E ->>+ DL : __next__
DL ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ IP : dynamic_call
IP ->>+ BP : last_action
BP -->>- IP : last_action, last_amount
IP ->>+ PO : get_on_object
PO -->>- IP : on_object?
alt not on_object
IP -->> MS : last_action, -last_amount
else
IP ->>+ BP : dynamic_call
BP ->> BP : get_random_action(action)
BP ->> BP : get_next_amount(action)
BP -->>- IP : action, amount
IP -->> MS: action, amount
end
deactivate IP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- DL : action, amount
DL ->> BP : state=state
DL -->>- E : i, observation
E ->>+ DL : post_episode
DL ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- DL :
DL -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant SP as SurfacePolicy
E ->>+ SP : __init__
SP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->>+ SP : get_next_amount(action)
alt no processed_observations
SP -->> SP : None
end
SP -->>- BP :
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- SP :
SP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ SP : pre_episode
SP ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- SP :
SP -->>- E :
E ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ SP : dynamic_call
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverage < 0.1
SP -->> E : None, None
else
SP ->> SP : get_next_action
activate SP
SP ->>+ BP : last_action
BP -->>- SP : last_action
alt "move_forward" in last_action
SP -->> SP : "orient_horizontal"
else "orient_horizontal" in last_action
SP -->> SP : "orient_vertical"
else "orient_vertical" in last_action
SP -->> SP : "move_tangentially"
else "move_tangentially" in last_action
SP ->>+ PO : get_on_object
PO -->>- SP : on_object?
alt if not on_object
SP -->> SP : "orient_horizontal"
else
SP -->> SP : "move_forward"
end
end
deactivate SP
SP ->> SP : get_next_amount(action)
activate SP
alt no processed_observations
SP -->> SP : None
end
alt "move_tangentially" in action
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverage < 0.2
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
SP -->> SP : amount / (4 / object_coverage)
else object_coverage < 0.75
SP -->> SP : amount / 4
else
SP -->> SP : amount
end
end
deactivate SP
SP -->> E : action, amount
end
deactivate SP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- E : action, amount
E ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant SP as SurfacePolicy
participant SPC as SurfacePolicyCurvatureInformed
E ->>+ SPC : __init__
SPC ->>+ SP : __init__
SP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->>+ SP : get_next_amount(action)
alt no processed_observations
SP -->> SP : None
end
SP -->>- BP :
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- SP :
SP -->>- SPC :
SPC -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ SPC : pre_episode
SPC ->>+ SP : pre_episode
SP ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- SP :
SP -->>- SPC :
SPC -->>- E :
E ->>+ MS : __call__
alt is_predefined
MS ->>+ BP : predefined_call
BP -->>- MS: action, amount
else
MS ->>+ SP : dynamic_call
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverage < 0.1
SP -->> E : None, None
else
SP ->> SP : get_next_action
activate SP
SP ->>+ BP : last_action
BP -->>- SP : last_action
alt "move_forward" in last_action
SP -->> SP : "orient_horizontal"
else "orient_horizontal" in last_action
SP -->> SP : "orient_vertical"
else "orient_vertical" in last_action
SP -->> SP : "move_tangentially"
else "move_tangentially" in last_action
SP ->>+ PO : get_on_object
PO -->>- SP : on_object?
alt if not on_object
SP -->> SP : "orient_horizontal"
else
SP -->> SP : "move_forward"
end
end
deactivate SP
SP ->> SP : get_next_amount(action)
activate SP
alt no processed_observations
SP -->> SP : None
end
alt "move_tangentially" in action
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
alt object_coverage < 0.2
SP ->>+ PO : get_feature_by_name("object_coverage")
PO -->>- SP : object_coverage
SP -->> SP : amount / (4 / object_coverage)
else object_coverage < 0.75
SP -->> SP : amount / 4
else
SP -->> SP : amount
end
end
deactivate SP
SP -->> E : action, amount
end
deactivate SP
end
MS ->>+ IP : post_action(action, amount)
IP -->>- MS :
MS -->>- E : action, amount
E ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- E :
sequenceDiagram
participant E as entrypoint
participant AS as ActionSpace
participant MS as MotorSystem
participant BP as BasePolicy
participant RAF as read_action_file
participant JTGM as JumpToGoalStateMixin
participant IP as InformedPolicy
participant TP as TouchPolicy
E ->>+ TP : __init__
TP ->>+ IP : __init__
IP ->>+ BP : __init__
BP ->>+ AS : sample
AS -->>- BP : action
BP ->> BP : get_random_action(action)
activate BP
loop
alt if rand() < switch_frequency:
BP ->>+ AS : sample
AS -->>- BP : action
end
break if action != agent_id+".set_agent_pose" and action != agent_id+".set_sensor_rotation"
BP -->> BP : action
end
end
deactivate BP
BP ->> BP : create_action_name_to_sample_fn
BP ->>+ TP : get_next_amount(action)
alt if no processed_observations
TP -->> TP : None
end
TP -->>- BP :
alt if file_names_per_episode is not None
BP ->> BP : is_predefined = True
end
alt if file_name is not None
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
BP ->> BP : is_predefined = True
end
BP -->>- IP :
alt use_goal_state_driven_actions
IP ->>+ JTGM : __init__
JTGM -->>- IP :
end
IP -->>- TP :
TP -->>- E :
create participant PO as processed_observations
E ->> PO :
E ->>+ TP : pre_episode
TP ->>+ IP : pre_episode
alt use_goal_state_driven_actions
IP ->>+ JTGM : pre_episode
JTGM ->> JTGM : set_driving_goal_state(None)
JTGM -->>- IP :
end
IP ->>+ BP : pre_episode
BP -->>- IP :
IP -->>- TP :
TP -->>- E :
E ->>+ TP : __call__
TP ->> TP : get_next_action
activate TP
TP ->>+ BP : last_action
BP -->>- TP : last_action
alt "move_forward" in last_action
TP -->> TP : "orient_horizontal"
else "orient_horizontal" in last_action
TP -->> TP : "orient_vertical"
else "orient_vertical" in last_action
TP -->> TP : "move_tangentially"
else "move_tangentially" in last_action
TP ->>+ PO : get_on_object
PO -->>- TP : on_object?
alt if not on_object
TP -->> TP : "orient_horizontal"
else
TP -->> TP : "move_forward"
end
end
deactivate TP
TP ->> TP : get_next_amount(action)
activate TP
alt if no processed_observations
TP -->> TP : None
else
alt "orient" in action
TP ->> TP : orienting_angle_from_normal(action)
activate TP
TP ->>+ PO : point_normal
PO -->>- TP :
deactivate TP
end
end
deactivate TP
TP -->>- E : action, amount
E ->>+ BP : post_episode
alt file_names_per_episode is not None
alt episode_count in file_names_per_episode
BP ->>+ RAF : __call__(file_name)
RAF -->>- BP : action_list, amount_list
end
end
BP -->>- E :
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