Sumo-Net/generate_job_parameters.py at master · MrHuff/Sumo-Net · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
import os
import shutil
import pickle

def save_obj(obj, name ,folder):
    with open(f'{folder}'+ name + '.pkl', 'wb') as f:
        pickle.dump(obj, f, pickle.HIGHEST_PROTOCOL)

def load_obj(name,folder):
    with open(f'{folder}' + name, 'rb') as f:
        return pickle.load(f)

# nets = ['survival_net_basic','cox_time_benchmark','deepsurv_benchmark','cox_CC_benchmark','cox_linear_benchmark','deephit_benchmark']
# validate_on = [0,0,0,0,0,1]
# nets = ['deephit_benchmark']
# validate_on = [1]
# nets = ['weibull_net','lognormal_net']
# validate_on = [0,0]
# nets = ['lognormal_net']
# validate_on = [0]


nets = ['survival_net_basic']
validate_on = [0]
def generate_job_params(directory='job_dir'):
    if not os.path.exists(directory):
        os.makedirs(directory)
    else:
        shutil.rmtree(directory)
        os.makedirs(directory)
    base_dict = {
        'dataset': 0,
        'seed': 2,
        'total_epochs': 100,
        # 'total_epochs': 25,
        'patience': 20,
        'hyperits': 50,

        'grid_size': 100,
        'test_grid_size': 100,
        'validation_interval': 4,
        'loss_type': 0,
        'net_type': 'ocean_net',
        'fold_idx': 0,
        'savedir': f'{directory}_results',
        'direct_dif': ['autograd'],
        'use_sotle': False,
    }
    counter = 0
    for seed in [1,2,1337,3,4]:
        for fold_idx in [0,1,2,3,4]:
            for dataset in [3]:
            # for dataset in [0,1,2,3]:
                for l_type in [0]:
                    for net_t,sel_crit in zip(nets,validate_on):
                        base_dict['dataset']=dataset
                        base_dict['loss_type']=l_type
                        base_dict['net_type']=net_t
                        base_dict['fold_idx']=fold_idx
                        base_dict['selection_criteria'] = sel_crit
                        base_dict['seed']=seed
                        save_obj(base_dict,f'job_{counter}',directory+'/')
                        counter +=1

if __name__ == '__main__':
        # generate_job_params(directory='testing')
        generate_job_params(directory='sumo_net_flchain_1')