-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtrain_new_scale.sh
172 lines (155 loc) · 4.21 KB
/
train_new_scale.sh
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
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
python3 training.py \
--trainid "vanilla_200epoch_crops128_bsize32_lr0001" \
--nEpochs 200 \
--crop_size 128 \
--batchSize 32 \
--lr 0.001 \
--cuda --gpus "1";
#--resume \
#--add_noise \
#--vgg_loss \
#--regressor_loss "scale" \
#--regressor_criterion "BCELoss_mean" \
#--regressor_loss_factor=1.0 \
#--regressor_gt2onehot \
#--regressor_onorm \
#--regressor_zeroclamp
#--colorjitter
#--trainds_input test_datasets/inria-aid_short/train/images
#--valds_input test_datasets/inria-aid_short/test/images
#--step 50
# L1
python3 training.py \
--trainid "scale_L1loss_200epoch_crops64_bsize128_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 64 \
--batchSize 128 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "L1Loss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_L1loss_200epoch_crops128_bsize32_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 128 \
--batchSize 32 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "L1Loss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_L1loss_200epoch_crops256_bsize16_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 256 \
--batchSize 16 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "L1Loss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_L1loss_200epoch_crops512_bsize4_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 512 \
--batchSize 4 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "L1Loss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
# L2
python3 training.py \
--trainid "scale_MSELoss_200epoch_crops64_bsize128_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 64 \
--batchSize 128 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "MSELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_MSELoss_200epoch_crops128_bsize32_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 128 \
--batchSize 32 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "MSELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_MSELoss_200epoch_crops256_bsize16_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 256 \
--batchSize 16 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "MSELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_MSELoss_200epoch_crops512_bsize4_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 512 \
--batchSize 4 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "MSELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
# BCE
python3 training.py \
--trainid "scale_BCELoss_200epoch_crops64_bsize128_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 64 \
--batchSize 128 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "BCELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_BCELoss_200epoch_crops128_bsize32_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 128 \
--batchSize 32 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "BCELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_BCELoss_200epoch_crops256_bsize16_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 256 \
--batchSize 16 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "BCELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";
python3 training.py \
--trainid "scale_BCELoss_200epoch_crops512_bsize4_lr0001_factor010_clamp" \
--nEpochs 200 \
--crop_size 512 \
--batchSize 4 \
--lr 0.001 \
--regressor_loss "scale" \
--regressor_criterion "BCELoss_mean" \
--regressor_loss_factor 0.10 \
--regressor_zeroclamp \
--cuda --gpus "1";