-
Notifications
You must be signed in to change notification settings - Fork 5
/
Copy pathtempo_command.txt
172 lines (100 loc) · 18.9 KB
/
tempo_command.txt
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
172
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_fgvc.py --train-type "P_VK" --config-file configs/prompt/prompt_test/FGVC/cars.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "5" MODEL.P_VK.NUM_TOKENS "5" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/cifar100.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "5" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.SHARE_PARAM_KV "False"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_fgvc.py --train-type "P_VK" --config-file configs/prompt/prompt_test/FGVC/dogs.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "60" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.ORIGIN_INIT "2"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_fgvc.py --train-type "P_VK" --config-file configs/prompt/prompt_test/FGVC/nabirds.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "5" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/caltech101.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/dtd.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/caltech101.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "32" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/svhn_cropped.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/sun397.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/caltech101.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_ProuningRewind_CVK_maskingOnVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/caltech101.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "32" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/smallnorb_evaluation.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "100" MODEL.P_VK.NUM_TOKENS "20" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/smallnorb_azimuth.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "100" MODEL.P_VK.NUM_TOKENS "20" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_ProuningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/clevr_count.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "20" MODEL.P_VK.NUM_TOKENS "20" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_fgvc_PruningRewind_BS128_TEMPO.py --config-file configs/prompt/prompt_test/FGVC/cars.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "128" MODEL.TRANSFER_TYPE "P_VK" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "5" MODEL.P_VK.NUM_TOKENS "5" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/clevr_distance.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "100" MODEL.P_VK.NUM_TOKENS "20" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/dsprites_location.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "32" MODEL.P_VK.NUM_TOKENS "6" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.MASK_QUERY "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_fgvc_fiveRuns.py --config-file configs/prompt/prompt_test/FGVC/cub.yaml MODEL.TRANSFER_TYPE "P_VK" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "5" MODEL.P_VK.NUM_TOKENS "5" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_ssl/VTAB-1k/Structured/smallnorb_evaluation.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "32" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/dtd.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "5" MODEL.P_VK.NUM_TOKENS "5" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.LAYER_BEHIND "False"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_ssl_mae/VTAB-1k/Natural/cifar100.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "128" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "False"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_swin/VTAB-1k/Structured/smallnorb_evaluation.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "32" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_swin/VTAB-1k/Natural/cifar100.yaml MODEL.TYPE "swin" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_swin/VTAB-1k/Natural/caltech101.yaml MODEL.TYPE "swin" DATA.BATCH_SIZE "80" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.LAYER_BEHIND "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_fgvc_fiveRuns.py --config-file configs/prompt/prompt_test/FGVC/cars.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.TRANSFER_TYPE "P_VK" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "200" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.MASK_CLS_TOKEN "False"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_swin/VTAB-1k/Specialized/patch_camelyon.yaml MODEL.TYPE "swin" DATA.BATCH_SIZE "80" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "5" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.LAYER_BEHIND "True"
# Cars
CUDA_VISIBLE_DEVICES=0 PORT=20000 python train.py \
--config-file configs/prompt/cars.yaml \
MODEL.TYPE "vit" \
DATA.BATCH_SIZE "64" \
MODEL.PROMPT.NUM_TOKENS "200" \
MODEL.PROMPT.DEEP "True" \
MODEL.PROMPT.DROPOUT "0.1" \
DATA.FEATURE "sup_vitb16_imagenet21k" \
DATA.NAME "StanfordCars" \
DATA.NUMBER_CLASSES "196" \
SOLVER.BASE_LR "5.0" \
SOLVER.WEIGHT_DECAY "0.0001" \
SEED 42 \
MODEL.MODEL_ROOT "/home/ch7858/vpt/models" \
DATA.DATAPATH "/shared/kgcoe-research/spl/fgvc/Stanford-cars" \
OUTPUT_DIR "output/pretrained_origin_prompt_cars"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python train.py \
--config-file configs/prompt/nabirds.yaml \
MODEL.TYPE "vit" \
DATA.BATCH_SIZE "128" \
MODEL.PROMPT.NUM_TOKENS "50" \
MODEL.PROMPT.DEEP "True" \
MODEL.PROMPT.DROPOUT "0.1" \
DATA.FEATURE "sup_vitb16_imagenet21k" \
DATA.NAME "nabirds" \
DATA.NUMBER_CLASSES "555" \
SOLVER.BASE_LR "50.0" \
SOLVER.WEIGHT_DECAY "0.0001" \
SEED 42 \
MODEL.MODEL_ROOT "/home/ch7858/vpt/models" \
DATA.DATAPATH "/shared/kgcoe-research/spl/fgvc/nabirds" \
OUTPUT_DIR "output/pretrained_origin_prompt_nabirds"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python train.py \
--config-file configs/prompt/flowers.yaml \
MODEL.TYPE "vit" \
DATA.BATCH_SIZE "128" \
MODEL.PROMPT.NUM_TOKENS "5" \
MODEL.PROMPT.DEEP "True" \
MODEL.PROMPT.DROPOUT "0.1" \
DATA.FEATURE "sup_vitb16_imagenet21k" \
DATA.NAME "OxfordFlowers" \
DATA.NUMBER_CLASSES "102" \
SOLVER.BASE_LR "25.0" \
SOLVER.WEIGHT_DECAY "0.0001" \
SEED 42 \
MODEL.MODEL_ROOT "/home/ch7858/vpt/models" \
DATA.DATAPATH "/shared/kgcoe-research/spl/fgvc/OxfordFlower" \
OUTPUT_DIR "output/pretrained_origin_prompt_flowers"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/dsprites_orientation.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "32" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "20" MODEL.P_VK.NUM_TOKENS "20" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Structured/dsprites_orientation.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "32" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "40" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_ssl_mae/VTAB-1k/Specialized/patch_camelyon.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "128" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_ssl_mae/VTAB-1k/Structured/dsprites_location.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "150" MODEL.P_VK.NUM_TOKENS "10" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
vtab-dsprites(predicted_attribute="label_x_position",num_classes=16)_P10_VK5_SHARED_1_INIT_2_ACC_0_ONVK_0
vtab-dsprites(predicted_attribute="label_orientation",num_classes=16)_P5_VK1_SHARED_1_INIT_2_ACC_0_BS128_LB1_RS224
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_ssl_moco/VTAB-1k/Specialized/eurosat.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "128" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=10000 python tune_fgvc_PruningRewind.py --config-file configs/prompt/prompt_test/FGVC/nabirds.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "128" MODEL.TRANSFER_TYPE "P_VK" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "50" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_ssl_mae/VTAB-1k/Specialized/patch_camelyon.yaml MODEL.TYPE "ssl-vit" DATA.BATCH_SIZE "128" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Specialized/diabetic_retinopathy_detection.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=30000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/cifar100.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.QUERY_PROMPT_MODE "2"
CUDA_VISIBLE_DEVICES=1 PORT=30000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Specialized/diabetic_retinopathy_detection.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" # MODEL.P_VK.QUERY_PROMPT_MODE "2"
CUDA_VISIBLE_DEVICES=1 PORT=30000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Natural/svhn_cropped.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "20" MODEL.P_VK.NUM_TOKENS "5" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=30000 python tune_vtab_PruningRewind_CVK_imagenet1k.py --train-type "P_VK" --config-file configs/prompt/prompt_test/imagenet1k.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "1" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True" MODEL.P_VK.QUERY_PROMPT_MODE "0"
CUDA_VISIBLE_DEVICES=0 PORT=20000 python tune_vtab.py --train-type "finetune" --config-file configs/finetune/VTAB-1k/Specialized/diabetic_retinopathy_detection.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "128"
CUDA_VISIBLE_DEVICES=1 PORT=30000 python tune_vtab_PruningRewind_CVK.py --train-type "P_VK" --config-file configs/prompt/prompt_test/VTAB-1k/Specialized/diabetic_retinopathy_detection.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.P_VK.DEEP "True" MODEL.P_VK.DEEP_P "True" MODEL.P_VK.DROPOUT_P "0.1" MODEL.P_VK.NUM_TOKENS_P "10" MODEL.P_VK.NUM_TOKENS "1" MODEL.P_VK.ORIGIN_INIT "2" MODEL.P_VK.SHARE_PARAM_KV "True"
CUDA_VISIBLE_DEVICES=1 PORT=30000 python tune_vtab.py --train-type "finetune" --config-file configs/finetune/VTAB-1k/Natural/cifar100.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "128" OUTPUT_DIR "DatasetChanged8000-2000FineTune"
CUDA_VISIBLE_DEVICES=0 PORT=30000 python tune_vtab_AS.py --train-type "prompt" --config-file configs/prompt/cifar100_forVPT.yaml MODEL.PROMPT.DEEP "True" MODEL.PROMPT.NUM_TOKENS "10" MODEL.PROMPT.DROPOUT "0.1" OUTPUT_DIR "A_test_as"
CUDA_VISIBLE_DEVICES=0 PORT=10000 python tune_vtab.py --train-type "finetune" --config-file configs/finetune/VTAB-1k/Natural/cifar100.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "128" OUTPUT_DIR "DatasetChanged400-100_Finetune"
# swin finetune origin
python tune_vtab.py --train-type "finetune" --config-file configs/finetune/VTAB-1k_swin/Natural/cifar100.yaml MODEL.TYPE "swin" DATA.BATCH_SIZE "128" OUTPUT_DIR "DatasetChanged_swin8000-2000FineTune"
# swin vpt origin
python tune_vtab.py --train-type "prompt" --config-file configs/prompt/prompt_swin/VTAB-1k_forVPT/Natural/cifar100.yaml MODEL.TYPE "swin" DATA.BATCH_SIZE "80" MODEL.PROMPT.DEEP "True" MODEL.PROMPT.NUM_TOKENS "10" MODEL.PROMPT.DROPOUT "0.1" OUTPUT_DIR "test_dataset"
python tune_vtab.py --train-type "prompt" --config-file configs/prompt/prompt_vpt/Natural/caltech101_forVPT.yaml MODEL.TYPE "vit" DATA.BATCH_SIZE "64" MODEL.PROMPT.DEEP "True" MODEL.PROMPT.NUM_TOKENS "10" MODEL.PROMPT.DROPOUT "0.1" OUTPUT_DIR "ft_pt"
python tune_vtab.py --train-type "prompt" --config-file configs/prompt/prompt_vpt/Structured/dsprites_orientation.yaml MODEL.PROMPT.DEEP "True" MODEL.PROMPT.NUM_TOKENS "50" MODEL.PROMPT.DROPOUT "0.1" OUTPUT_DIR "ft_pt_mixed" DATA.BATCH_SIZE "64" MODEL.PROMPT.FT_PT_MIXED "True"