Source code for titan_pylib.ahc.ahc_settings

 1import optuna
 2
 3"""example
 4python3 ./parallel_tester.py -c -v -njobs 127
 5
 6python3 ./oprimizer.py
 7g++ ./main.cpp -O2 -std=c++20 -o a.out -I./../../../Library_cpp
 8"""
 9
10

[docs]
11class AHCSettings:
12    """
13    AHCテスターの設定ファイル
14
15    https://github.com/titan-23/Library_py/tree/main/titan_pylib/ahc/readme.md
16    """
17
18    # parallel_tester -------------------- #
19    compile_command = "g++ ./main.cpp -O2 -std=c++20 -o a.out -I./../../../Library_cpp"
20    execute_command = "./a.out"
21    input_file_names = [f"./in/{str(i).zfill(4)}.txt" for i in range(100)]
22    timeout = None
23

[docs]
24    def get_score(scores: list[float]) -> float:
25        return sum(scores) / len(scores) * 100

26
27    # ------------------------------------ #
28
29    # optimizer -------------------------- #
30    # study_name
31    study_name = "test"
32
33    # direction: minimize / maximize
34    direction = "minimize"
35
36    # parallel_tester の cpu_count
37    n_jobs_parallel_tester = 127
38
39    # optuna の試行回数
40    n_trials = 50
41
42    # optuna の cpu_count
43    n_jobs_optuna = 1
44

[docs]
45    def objective(trial: optuna.trial.Trial) -> tuple:
46        # 返り値のタプルはコマンドライン引数として渡す順番にする
47        start_temp = trial.suggest_float("start_temp", 1, 100, log=True)
48        k = trial.suggest_float("k", 0.0001, 1, log=True)
49        end_temp = start_temp * k
50        return (start_temp, end_temp)


51
52    # ------------------------------------ #