Comments (4)
Yap, we are fixing this but. It happens that you need to have the continuous variables first and later the discrete ones. The optimization is carried out correctly in this case but it is a pain from the user perspective. We will have this fixed in the upcoming days.
Javier
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I followed your instruction and now I have the continuous variables first and later the discrete ones.
However, the instance creation method prints lots of junk messages, which does not happen when I set all variables to "continuous".
hyper_parameters_opt = GPyOpt.methods.BayesianOptimization(f = model.test_hyperpara, domain = model.hyper_parameters_domain, normalize_Y= True, exact_feval = True, model_type= 'GP', acquisition_type ='EI', acquisition_jitter = 0.25)
It also happens in run_optimization() method. How to turn it off?
Junks printed:
0 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 1 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 2 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 3 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 4 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 5 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 6 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] ------------------------------- 7 [1] [[1] [2] [3] [4] [5] [6] [7] [8]] -------------------------------
from gpyopt.
I dug a little bit and found out the following:
GPyOpt/optimization/acquisition_optimizer.py: print(i) GPyOpt/optimization/acquisition_optimizer.py: print(self.discrete_dims) GPyOpt/optimization/acquisition_optimizer.py: print(self.discrete_values) GPyOpt/optimization/acquisition_optimizer.py: print("-------------------------------")
You may use logger instead of print(), otherwise the users cannot turn it off. It slows down the process because those printing takes time.
I commented those "print" out and the junk messages are gone.
from gpyopt.
Hi Zhang,
This issue has been fixed in the devel branch.
Javier
from gpyopt.
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from gpyopt.