forked from devsisters/pointer-network-tensorflow
-
Notifications
You must be signed in to change notification settings - Fork 0
/
config.py
63 lines (55 loc) · 2.96 KB
/
config.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
#-*- coding: utf-8 -*-
import argparse
def str2bool(v):
return v.lower() in ('true', '1')
arg_lists = []
parser = argparse.ArgumentParser()
def add_argument_group(name):
arg = parser.add_argument_group(name)
arg_lists.append(arg)
return arg
# Network
net_arg = add_argument_group('Network')
net_arg.add_argument('--hidden_dim', type=int, default=256, help='')
net_arg.add_argument('--num_layers', type=int, default=1, help='')
net_arg.add_argument('--input_dim', type=int, default=2, help='')
net_arg.add_argument('--max_enc_length', type=int, default=None, help='')
net_arg.add_argument('--max_dec_length', type=int, default=None, help='')
net_arg.add_argument('--init_min_val', type=float, default=-0.08, help='for uniform random initializer')
net_arg.add_argument('--init_max_val', type=float, default=+0.08, help='for uniform random initializer')
net_arg.add_argument('--num_glimpse', type=int, default=1, help='')
net_arg.add_argument('--use_terminal_symbol', type=str2bool, default=True, help='Not implemented yet')
# Data
data_arg = add_argument_group('Data')
data_arg.add_argument('--task', type=str, default='tsp')
data_arg.add_argument('--batch_size', type=int, default=128)
data_arg.add_argument('--min_data_length', type=int, default=5)
data_arg.add_argument('--max_data_length', type=int, default=10)
data_arg.add_argument('--train_num', type=int, default=1000000)
data_arg.add_argument('--valid_num', type=int, default=1000)
data_arg.add_argument('--test_num', type=int, default=1000)
# Training / test parameters
train_arg = add_argument_group('Training')
train_arg.add_argument('--is_train', type=str2bool, default=True, help='')
train_arg.add_argument('--optimizer', type=str, default='rmsprop', help='')
train_arg.add_argument('--max_step', type=int, default=1000000, help='')
train_arg.add_argument('--lr_start', type=float, default=0.001, help='')
train_arg.add_argument('--lr_decay_step', type=int, default=5000, help='')
train_arg.add_argument('--lr_decay_rate', type=float, default=0.96, help='')
train_arg.add_argument('--max_grad_norm', type=float, default=2.0, help='')
train_arg.add_argument('--checkpoint_secs', type=int, default=300, help='')
# Misc
misc_arg = add_argument_group('Misc')
misc_arg.add_argument('--log_step', type=int, default=50, help='')
misc_arg.add_argument('--num_log_samples', type=int, default=3, help='')
misc_arg.add_argument('--log_level', type=str, default='INFO', choices=['INFO', 'DEBUG', 'WARN'], help='')
misc_arg.add_argument('--log_dir', type=str, default='logs')
misc_arg.add_argument('--data_dir', type=str, default='data')
misc_arg.add_argument('--output_dir', type=str, default='outputs')
misc_arg.add_argument('--load_path', type=str, default='')
misc_arg.add_argument('--debug', type=str2bool, default=False)
misc_arg.add_argument('--gpu_memory_fraction', type=float, default=1.0)
misc_arg.add_argument('--random_seed', type=int, default=123, help='')
def get_config():
config, unparsed = parser.parse_known_args()
return config, unparsed