imput

humpday/optimizers/alltopoptimizers.py

@@ -1,13 +1,13 @@
 from humpday.optimizers.pysotcube import pysot_srbf_cube, pysot_dycors_cube
-from humpday.optimizers.axcube import ax_default_cube
-from humpday.optimizers.dlibcube import DLIB_OPTIMIZERS
 from humpday.optimizers.nevergradcube import nevergrad_ngopt8_cube, nevergrad_ngopt4_cube
 from humpday.optimizers.optunacube import optuna_cmaes_cube
 from humpday.optimizers.pymoocube import pymoo_pattern_cube
 from humpday.optimizers.shgocube import shgo_powell_sobol_cube
 from humpday.optimizers.skoptcube import skopt_gp_default_cube
 from humpday.optimizers.nloptcube import nlopt_directr_cube
+from humpday.optimizers.dlibcube import DLIB_OPTIMIZERS
 
-TOP_OPTIMIZERS = [pysot_dycors_cube, pysot_srbf_cube, ax_default_cube,
+TOP_OPTIMIZERS = [pysot_dycors_cube, pysot_srbf_cube,
                   nevergrad_ngopt4_cube, nevergrad_ngopt8_cube, optuna_cmaes_cube, pymoo_pattern_cube,
                   shgo_powell_sobol_cube, skopt_gp_default_cube, nlopt_directr_cube] + DLIB_OPTIMIZERS
+

humpday/optimizers/axcube.py

@@ -14,7 +14,6 @@
     rt.setLevel(CRITICAL)
     import warnings
     warnings.filterwarnings("ignore")
-    from humpday.objectives.classic import CLASSIC_OBJECTIVES
 
 
     def ax_cube(objective, n_trials, n_dim, with_count=False, method=None):
@@ -50,14 +49,14 @@ def ax_default_cube(objective, n_trials, n_dim, with_count=False):
 else:
     AX_OPTIMIZERS = []
 
-@print_durations()
-def demo():
-    for objective in CLASSIC_OBJECTIVES:
-        print(' ')
-        print(objective.__name__)
-        for optimizer in AX_OPTIMIZERS:
-            print(optimizer(objective, n_trials=250, n_dim=6, with_count=True))
-
 
 if __name__=='__main__':
-    demo()
+    from humpday.objectives.classic import CLASSIC_OBJECTIVES
+    @print_durations()
+    def demo():
+        for objective in CLASSIC_OBJECTIVES:
+            print(' ')
+            print(objective.__name__)
+            for optimizer in AX_OPTIMIZERS:
+                print(optimizer(objective, n_trials=250, n_dim=6, with_count=True))
+