for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
import numpy as np
def get_score(para):
return -(para["x1"] * para["x1"])
search_space = {
"x1": np.arange(-100, 100, 1),
}
def _base_test(
opt_class, n_iter, get_score=get_score, search_space=search_space, opt_para={},
):
opt = opt_class(search_space, **opt_para)
opt.search(get_score, n_iter=n_iter)
SimonBlanke /
Gradient-Free-Optimizers
