Merge branch 'develop' into release-1.1

issp-center-dev · Jun 17, 2022 · 2b2c14e · 2b2c14e
2 parents ff131c9 + 08f1d9a
commit 2b2c14e
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Showing 2 changed files with 12 additions and 1 deletion.
diff --git a/physbo/search/discrete/policy.py b/physbo/search/discrete/policy.py
@@ -60,7 +60,7 @@ def __init__(self, test_X, config=None, initial_data=None, comm=None):
             self.mpisize = comm.size
             self.mpirank = comm.rank
             self.actions = np.array_split(self.actions, self.mpisize)[self.mpirank]
-            self.config.learning.is_disp = self.mpirank == 0
+            self.config.learning.is_disp = (self.config.learning.is_disp and self.mpirank == 0)
 
     def set_seed(self, seed):
         """
@@ -251,6 +251,9 @@ def bayes_search(
         if self.mpirank != 0:
             is_disp = False
 
+        old_disp = self.config.learning.is_disp
+        self.config.learning.is_disp = is_disp
+
         if max_num_probes is None:
             max_num_probes = 1
             simulator = None
@@ -296,6 +299,7 @@ def bayes_search(
                 break
 
             if simulator is None:
+                self.config.learning.is_disp = old_disp
                 return action
 
             time_run_simulator = time.time()
@@ -315,6 +319,7 @@ def bayes_search(
             if is_disp:
                 utility.show_search_results(self.history, N_indeed)
         self._update_predictor()
+        self.config.learning.is_disp = old_disp
         return copy.deepcopy(self.history)
 
     @staticmethod

diff --git a/physbo/search/discrete_multi/policy.py b/physbo/search/discrete_multi/policy.py
@@ -182,6 +182,9 @@ def bayes_search(
         if self.mpirank != 0:
             is_disp = False
 
+        old_disp = self.config.learning.is_disp
+        self.config.learning.is_disp = is_disp
+
         if max_num_probes is None:
             max_num_probes = 1
             simulator = None
@@ -230,9 +233,11 @@ def bayes_search(
             if N_indeed == 0:
                 if self.mpirank == 0:
                     print("WARNING: All actions have already searched.")
+                self.config.learning.is_disp = old_disp
                 return copy.deepcopy(self.history)
 
             if simulator is None:
+                self.config.learning.is_disp = old_disp
                 return action
 
             time_run_simulator = time.time()
@@ -254,6 +259,7 @@ def bayes_search(
                     self.history, N, disp_pareto_set=disp_pareto_set
                 )
         self._update_predictor()
+        self.config.learning.is_disp = old_disp
         return copy.deepcopy(self.history)
 
     def _get_actions(self, mode, N, K, alpha):