forked from biesseck/MICA
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtrain.py
executable file
·80 lines (62 loc) · 2.56 KB
/
train.py
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
68
69
70
71
72
73
74
75
76
77
78
79
80
# -*- coding: utf-8 -*-
# Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. (MPG) is
# holder of all proprietary rights on this computer program.
# You can only use this computer program if you have closed
# a license agreement with MPG or you get the right to use the computer
# program from someone who is authorized to grant you that right.
# Any use of the computer program without a valid license is prohibited and
# liable to prosecution.
#
# Copyright©2022 Max-Planck-Gesellschaft zur Förderung
# der Wissenschaften e.V. (MPG). acting on behalf of its Max Planck Institute
# for Intelligent Systems. All rights reserved.
#
# Contact: mica@tue.mpg.de
import os
import sys
import torch
import torch.backends.cudnn as cudnn
import torch.multiprocessing as mp
from jobs import train
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '.')))
# BERNARDO
import numpy as np
import random
import socket
host_name = socket.gethostname()
if __name__ == '__main__':
from configs.config import parse_args
# BERNARDO
print('Running on \'' + host_name + '\' machine...')
if len(sys.argv) < 2:
if host_name == 'duo':
sys.argv.append('--cfg')
sys.argv.append('/home/bjgbiesseck/GitHub/BOVIFOCR_MICA_3Dreconstruction/configs/mica_duo.yml')
sys.argv.append('--test_dataset')
sys.argv.append('STIRLING')
sys.argv.append('--checkpoint')
sys.argv.append('')
cfg, args = parse_args()
if cfg.cfg_file is not None:
exp_name = cfg.cfg_file.split('/')[-1].split('.')[0]
# cfg.output_dir = os.path.join('./output', exp_name) # original
cfg.output_dir = os.path.join('./output', exp_name) + cfg.output_dir_annotation # Bernardo
cudnn.benchmark = False
cudnn.deterministic = True
torch.cuda.empty_cache()
num_gpus = torch.cuda.device_count()
# BERNARDO (from 'https://github.com/pytorch/pytorch/issues/45042#issuecomment-701115885' - on 29 Sep 2020)
seed = 440
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
random.seed(seed)
np.random.seed(seed)
torch.backends.cudnn.enabled = True
torch.backends.cudnn.benchmark = True
# BERNARDO
# print('train.py: num_gpus:', num_gpus, ' cfg:', cfg)
print('train.py: num_gpus:', num_gpus)
# mp.spawn(train, args=(num_gpus, cfg), nprocs=num_gpus, join=True) # Original
mp.spawn(train, args=(num_gpus, cfg), nprocs=1, join=True) # BERNARDO
# train(rank=num_gpus, world_size=num_gpus, cfg=cfg)
exit(0)