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Works for one use input

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Niko Feith 2023-03-27 16:57:11 +02:00
parent 76b8f5e2d2
commit 10f938cc13
3 changed files with 68 additions and 52 deletions
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29
src/active_bo_ros/active_bo_ros/active_bo_service.py
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@ -4,6 +4,8 @@ from active_bo_msgs.srv import ActiveRL
import rclpy import rclpy
from rclpy.node import Node from rclpy.node import Node
from rclpy.callback_groups import ReentrantCallbackGroup
from active_bo_ros.BayesianOptimization.BayesianOptimization import BayesianOptimization from active_bo_ros.BayesianOptimization.BayesianOptimization import BayesianOptimization
from active_bo_ros.ReinforcementLearning.ContinuousMountainCar import Continuous_MountainCarEnv from active_bo_ros.ReinforcementLearning.ContinuousMountainCar import Continuous_MountainCarEnv
@ -13,11 +15,18 @@ import numpy as np
class ActiveBOService(Node): class ActiveBOService(Node):
def __init__(self): def __init__(self):
super().__init__('active_bo_service') super().__init__('active_bo_service')
self.active_bo_srv = self.create_service(ActiveBO, 'active_bo_srv', self.active_bo_callback)
self.active_rl_client = self.create_client(ActiveRL, 'active_rl_srv') bo_callback_group = ReentrantCallbackGroup()
rl_callback_group = ReentrantCallbackGroup()
self.rl_trigger_ = False self.srv = self.create_service(ActiveBO,
'active_bo_srv',
self.active_bo_callback,
callback_group=bo_callback_group)
self.active_rl_client = self.create_client(ActiveRL,
'active_rl_srv',
callback_group=rl_callback_group)
self.env = Continuous_MountainCarEnv() self.env = Continuous_MountainCarEnv()
self.distance_penalty = 0 self.distance_penalty = 0
@ -56,18 +65,22 @@ class ActiveBOService(Node):
arl_request.old_policy = old_policy.tolist() arl_request.old_policy = old_policy.tolist()
arl_request.old_weights = old_weights.tolist() arl_request.old_weights = old_weights.tolist()
self.get_logger().info('Calling: Active RL')
future_rl = self.active_rl_client.call_async(arl_request) future_rl = self.active_rl_client.call_async(arl_request)
while rclpy.ok(): while not future_rl.done():
rclpy.spin_once(self) rclpy.spin_once(self)
if future_rl.done(): self.get_logger().info('waiting for response!')
self.get_logger().info('Received: Active RL')
try: try:
arl_response = future_rl.result() arl_response = future_rl.result()
self.get_logger().info('active RL Response: %s' % arl_response)
BO.add_new_observation(arl_response.reward, arl_response.new_weights) BO.add_new_observation(arl_response.reward, arl_response.new_weights)
except Exception as e: except Exception as e:
self.get_logger().error('active RL Service failed %r' % (e,)) self.get_logger().error('active RL Service failed %r' % (e,))
break
future_rl = None
# BO part # BO part
else: else:
@ -96,6 +109,8 @@ def main(args=None):
rclpy.spin(active_bo_service) rclpy.spin(active_bo_service)
rclpy.shutdown()
if __name__ == '__main__': if __name__ == '__main__':
main() main()

69
src/active_bo_ros/active_bo_ros/active_rl_service.py
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@ -1,6 +1,6 @@
from active_bo_msgs.srv import ActiveRL from active_bo_msgs.srv import ActiveRL
from active_bo_msgs.msg import ImageFeedback from active_bo_msgs.msg import ImageFeedback
from active_bo_msgs.srv import ActiveRLEval from active_bo_msgs.msg import ActiveRLEval
import rclpy import rclpy
from rclpy.node import Node from rclpy.node import Node
@ -17,44 +17,42 @@ class ActiveRLService(Node):
def __init__(self): def __init__(self):
super().__init__('active_rl_service') super().__init__('active_rl_service')
srv_callback_group = ReentrantCallbackGroup() srv_callback_group = ReentrantCallbackGroup()
eval_callback_group = ReentrantCallbackGroup() sub_callback_group = ReentrantCallbackGroup()
self.rl_srv = self.create_service(ActiveRL, self.srv = self.create_service(ActiveRL,
'active_rl_srv', 'active_rl_srv',
self.active_rl_callback, self.active_rl_callback,
callback_group=srv_callback_group) callback_group=srv_callback_group)
self.publisher = self.create_publisher(ImageFeedback, 'rl_feedback', 1) self.publisher = self.create_publisher(ImageFeedback, 'rl_feedback', 1)
self.active_rl_eval_client = self.create_client(ActiveRLEval, self.eval_pub = self.create_publisher(ActiveRLEval, 'active_rl_eval_request', 1)
'active_rl_eval_srv', self.eval_sub = self.create_subscription(ActiveRLEval,
callback_group=eval_callback_group) 'active_rl_eval_response',
self.active_rl_eval_callback,
# self.eval_pub = self.create_publisher(ActiveRLEval, 'active_rl_eval_request', 1) 1,
# self.eval_sub = self.create_subscription(ActiveRLEval, callback_group=sub_callback_group)
# 'active_rl_eval_response', self.eval_response_received = False
# self.active_rl_eval_callback, self.eval_response = None
# 10, self.eval_response_received_first = False
# callback_group=sub_callback_group)
# self.eval_response_received = False
# self.eval_response = None
# self.eval_response_received_first = False
self.env = Continuous_MountainCarEnv(render_mode='rgb_array') self.env = Continuous_MountainCarEnv(render_mode='rgb_array')
self.distance_penalty = 0 self.distance_penalty = 0
# def active_rl_eval_callback(self, response): def active_rl_eval_callback(self, response):
# # if not self.eval_response_received_first: # if not self.eval_response_received_first:
# # self.eval_response_received_first = True # self.eval_response_received_first = True
# # self.get_logger().info('/active_rl_eval_response connected!') # self.get_logger().info('/active_rl_eval_response connected!')
# # else: # else:
# # self.eval_response = response
# # self.eval_response_received = True
# self.eval_response = response # self.eval_response = response
# self.eval_response_received = True # self.eval_response_received = True
self.eval_response = response
self.eval_response_received = True
def active_rl_callback(self, request, response): def active_rl_callback(self, request, response):
self.get_logger().info('Active RL: Called')
feedback_msg = ImageFeedback() feedback_msg = ImageFeedback()
reward = 0 reward = 0
@ -62,9 +60,9 @@ class ActiveRLService(Node):
old_policy = request.old_policy old_policy = request.old_policy
old_weights = request.old_weights old_weights = request.old_weights
eval_request = ActiveRLEval.Request() eval_request = ActiveRLEval()
eval_request.old_policy = old_policy eval_request.policy = old_policy
eval_request.old_weights = old_weights eval_request.weights = old_weights
self.env.reset() self.env.reset()
@ -95,17 +93,16 @@ class ActiveRLService(Node):
break break
self.get_logger().info('Enter new solution!') self.get_logger().info('Enter new solution!')
# self.eval_pub.publish(eval_request) self.eval_pub.publish(eval_request)
#
# while not self.eval_response_received:
# rclpy.spin_once(self)
eval_response = self.active_rl_eval_client.call(eval_request) while not self.eval_response_received:
self.get_logger().info('Active RL Eval Srv started!') rclpy.spin_once(self)
new_policy = eval_response.new_policy
new_weights = eval_response.new_weights
self.get_logger().info('Topic responded!')
new_policy = self.eval_response.policy
new_weights = self.eval_response.weights
self.eval_response_received = False
self.eval_response = None
reward = 0 reward = 0
step_count = 0 step_count = 0
@ -157,6 +154,8 @@ def main(args=None):
rclpy.spin(active_rl_service) rclpy.spin(active_rl_service)
rclpy.shutdown()
if __name__ == '__main__': if __name__ == '__main__':
main() main()

2
src/active_bo_ros/active_bo_ros/rl_service.py
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@ -71,5 +71,7 @@ def main(args=None):
rclpy.spin(rl_service) rclpy.spin(rl_service)
rclpy.shutdown()
if __name__ == '__main__': if __name__ == '__main__':
main() main()