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debugging

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This commit is contained in:
Niko Feith 2023-06-07 17:10:57 +02:00
parent 3e278fb0fc
commit 26a64db6d6
3 changed files with 12 additions and 3 deletions
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5
src/active_bo_ros/active_bo_ros/BayesianOptimization/BayesianOptimization.py
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@ -7,6 +7,11 @@ from active_bo_ros.AcquisitionFunctions.ExpectedImprovement import ExpectedImpro
from active_bo_ros.AcquisitionFunctions.ProbabilityOfImprovement import ProbabilityOfImprovement from active_bo_ros.AcquisitionFunctions.ProbabilityOfImprovement import ProbabilityOfImprovement
from active_bo_ros.AcquisitionFunctions.ConfidenceBound import ConfidenceBound from active_bo_ros.AcquisitionFunctions.ConfidenceBound import ConfidenceBound
from sklearn.exceptions import ConvergenceWarning
import warnings
warnings.filterwarnings('ignore', category=ConvergenceWarning)
class BayesianOptimization: class BayesianOptimization:
def __init__(self, env, nr_steps, nr_init=3, acq='ei', nr_weights=6, policy_seed=None): def __init__(self, env, nr_steps, nr_init=3, acq='ei', nr_weights=6, policy_seed=None):

1
src/active_bo_ros/active_bo_ros/active_rl_topic.py
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@ -208,6 +208,7 @@ class ActiveRLService(Node):
self.best_pol_shown = False self.best_pol_shown = False
self.eval_response_received = False self.eval_response_received = False
self.rl_pending = False self.rl_pending = False
elif self.interactive_run == 1: elif self.interactive_run == 1:
if not self.policy_sent: if not self.policy_sent:
self.rl_step = 0 self.rl_step = 0

9
src/active_bo_ros/active_bo_ros/interactive_bo.py
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@ -129,7 +129,7 @@ class ActiveBOTopic(Node):
self.seed_array = np.zeros((1, self.bo_runs)) self.seed_array = np.zeros((1, self.bo_runs))
# initialize # initialize
self.reward = np.zeros((self.bo_episodes, self.bo_runs)) self.reward = np.zeros((self.bo_episodes+self.nr_init, self.bo_runs))
self.best_pol_reward = np.zeros((1, self.bo_runs)) self.best_pol_reward = np.zeros((1, self.bo_runs))
self.best_policy = np.zeros((self.bo_steps, self.bo_runs)) self.best_policy = np.zeros((self.bo_steps, self.bo_runs))
self.best_weights = np.zeros((self.bo_nr_weights, self.bo_runs)) self.best_weights = np.zeros((self.bo_nr_weights, self.bo_runs))
@ -194,6 +194,7 @@ class ActiveBOTopic(Node):
# self.BO.initialize() # self.BO.initialize()
self.init_pending = True self.init_pending = True
self.get_logger().info('BO Initialization is starting!') self.get_logger().info('BO Initialization is starting!')
self.get_logger().info(f'{self.rl_pending}')
if self.init_pending and not self.rl_pending: if self.init_pending and not self.rl_pending:
@ -275,6 +276,7 @@ class ActiveBOTopic(Node):
active_rl_request.policy = self.best_policy[:, best_policy_idx].tolist() active_rl_request.policy = self.best_policy[:, best_policy_idx].tolist()
active_rl_request.weights = self.best_weights[:, best_policy_idx].tolist() active_rl_request.weights = self.best_weights[:, best_policy_idx].tolist()
active_rl_request.interactive_run = 1 active_rl_request.interactive_run = 1
active_rl_request.display_run = True
self.active_rl_pub.publish(active_rl_request) self.active_rl_pub.publish(active_rl_request)
@ -365,13 +367,14 @@ class ActiveBOTopic(Node):
self.reward[:, self.current_run] = self.BO.best_reward.T self.reward[:, self.current_run] = self.BO.best_reward.T
self.BO = None if self.current_run < self.bo_runs - 1:
self.BO = None
self.current_episode = 0 self.current_episode = 0
if self.bo_fixed_seed: if self.bo_fixed_seed:
self.seed_array[0, self.current_run] = self.seed self.seed_array[0, self.current_run] = self.seed
self.seed = int(np.random.randint(1, 2147483647, 1)[0]) self.seed = int(np.random.randint(1, 2147483647, 1)[0])
self.get_logger().info(f'{self.seed}') # self.get_logger().info(f'{self.seed}')
self.current_run += 1 self.current_run += 1
self.get_logger().info(f'Current Run: {self.current_run}') self.get_logger().info(f'Current Run: {self.current_run}')