|
1
|
|
|
import time |
|
2
|
|
|
import pytest |
|
3
|
|
|
import numpy as np |
|
4
|
|
|
|
|
5
|
|
|
from ._parametrize import optimizers |
|
6
|
|
|
|
|
7
|
|
|
|
|
8
|
|
|
def objective_function(para): |
|
9
|
|
|
score = -para["x1"] * para["x1"] |
|
10
|
|
|
return score |
|
11
|
|
|
|
|
12
|
|
|
|
|
13
|
|
|
search_space = { |
|
14
|
|
|
"x1": np.arange(-100, 100, 0.1), |
|
15
|
|
|
} |
|
16
|
|
|
|
|
17
|
|
|
|
|
18
|
|
|
@pytest.mark.parametrize(*optimizers) |
|
19
|
|
|
def test_name_0(Optimizer): |
|
20
|
|
|
opt = Optimizer(search_space, initialize={"random": 3}) |
|
21
|
|
|
opt.search(objective_function, n_iter=5) |
|
22
|
|
|
|
|
23
|
|
|
assert opt.random_seed is not None |
|
24
|
|
|
|
|
25
|
|
|
|
|
26
|
|
|
@pytest.mark.parametrize(*optimizers) |
|
27
|
|
|
def test_name_1(Optimizer): |
|
28
|
|
|
opt = Optimizer(search_space) |
|
29
|
|
|
|
|
30
|
|
|
assert opt.random_seed is not None |
|
31
|
|
|
|
|
32
|
|
|
|
|
33
|
|
|
@pytest.mark.parametrize(*optimizers) |
|
34
|
|
|
def test_name_2(Optimizer): |
|
35
|
|
|
random_state = 42 |
|
36
|
|
|
opt = Optimizer(search_space, initialize={"random": 3}, random_state=random_state) |
|
37
|
|
|
opt.search(objective_function, n_iter=5) |
|
38
|
|
|
|
|
39
|
|
|
assert opt.random_seed == random_state |
|
40
|
|
|
|
|
41
|
|
|
|
|
42
|
|
|
@pytest.mark.parametrize(*optimizers) |
|
43
|
|
|
def test_name_3(Optimizer): |
|
44
|
|
|
random_state = 42 |
|
45
|
|
|
opt = Optimizer(search_space, random_state=random_state) |
|
46
|
|
|
|
|
47
|
|
|
assert opt.random_seed == random_state |
|
48
|
|
|
|
|
49
|
|
|
|
|
50
|
|
|
@pytest.mark.parametrize(*optimizers) |
|
51
|
|
|
def test_name_4(Optimizer): |
|
52
|
|
|
n_iter = 10 |
|
53
|
|
|
|
|
54
|
|
|
opt1 = Optimizer(search_space, initialize={"random": 3}) |
|
55
|
|
|
opt1.search(objective_function, n_iter=n_iter) |
|
56
|
|
|
|
|
57
|
|
|
best_score1 = opt1.best_score |
|
58
|
|
|
|
|
59
|
|
|
opt2 = Optimizer( |
|
60
|
|
|
search_space, initialize={"random": 3}, random_state=opt1.random_seed |
|
61
|
|
|
) |
|
62
|
|
|
opt2.search(objective_function, n_iter=n_iter) |
|
63
|
|
|
|
|
64
|
|
|
best_score2 = opt2.best_score |
|
65
|
|
|
|
|
66
|
|
|
assert best_score1 == best_score2 |
|
67
|
|
|
|
SimonBlanke /
Gradient-Free-Optimizers
