-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathrun.sh
238 lines (189 loc) · 8.48 KB
/
run.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
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
#!/bin/bash
MANUAL_SEED=2222
# Bash arguments
if [[ $# -eq 0 ]]; then
GPU_ID=0
LOSS_TYPE=contrastive_loss
DATASET_NAME=cub200
elif [[ $# -eq 1 ]]; then
GPU_ID=$1
LOSS_TYPE=contrastive_loss
DATASET_NAME=cub200
elif [[ $# -eq 2 ]]; then
GPU_ID=$1
LOSS_TYPE=$2
DATASET_NAME=cub200
elif [[ $# -eq 3 ]]; then
GPU_ID=$1
LOSS_TYPE=$2
DATASET_NAME=$3
STD_VALUE=2
elif [[ $# -eq 4 ]]; then
GPU_ID=$1
LOSS_TYPE=$2
DATASET_NAME=$3
STD_VALUE=$4
fi
echo "Traing Info:"
echo "GPU_ID = ${GPU_ID}"
echo "LOSS_TYPE = ${LOSS_TYPE}"
echo "DATASET_NAME = ${DATASET_NAME}"
####### data information ####
if [ $(hostname) = 'dgx1' ]; then
# running code on the dgx1
if [[ $DATASET_NAME = "cub200" ]]; then
ROOT_DIR="/data/Guoxian_Dai/CUB_200_2011/CUB_200_2011/images"
IMAGE_TXT="/data/Guoxian_Dai/CUB_200_2011/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/data/Guoxian_Dai/CUB_200_2011/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/data/Guoxian_Dai/CUB_200_2011/CUB_200_2011/image_class_labels.txt"
elif [[ $DATASET_NAME = "online_product" ]]; then
ROOT_DIR="/data/Guoxian_Dai/Stanford_Online_Products"
IMAGE_TXT="/data/Guoxian_Dai/Stanford_Online_Products/Ebay_train.txt"
TRAIN_TEST_SPLIT_TXT="/data/Guoxian_Dai/Stanford_Online_Products/Ebay_test.txt"
fi
LEARNING_RATE=0.001
PYTHON=py_gxdai
elif [ $(hostname) = 'aduae266-lap' ]; then
# running code one nyu machine
ROOT_DIR="/home/gxdai/MMVC_LARGE2/Guoxian_Dai/data/cub_2011/CUB_200_2011/images"
IMAGE_TXT="/home/gxdai/MMVC_LARGE2/Guoxian_Dai/data/cub_2011/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/home/gxdai/MMVC_LARGE2/Guoxian_Dai/data/cub_2011/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/home/gxdai/MMVC_LARGE2/Guoxian_Dai/data/cub_2011/CUB_200_2011/image_class_labels.txt"
LEARNING_RATE=0.0001
PYTHON=python
elif [ $(hostname) = 'institute01' ]; then
# running code on the dgx1
ROOT_DIR="/raid/Guoxian_Dai/cub_2011/CUB_200_2011/images"
IMAGE_TXT="/raid/Guoxian_Dai/cub_2011/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/raid/Guoxian_Dai/cub_2011/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/raid/Guoxian_Dai/cub_2011/CUB_200_2011/image_class_labels.txt"
LEARNING_RATE=0.001
PYTHON=py_gxdai
elif [ $(hostname) = 'uranus' ]; then
echo "running code on the uranus"
echo "=========================="
echo "Activate virutalenv"
source $HOME/py2/bin/activate
source $HOME/tf_path
echo "START >>>>>>>>>>>>>>>>>>>"
if [[ $DATASET_NAME = "cub200" ]]; then
ROOT_DIR="/data1/Guoxian_Dai/CUB_200_2011/images"
IMAGE_TXT="/data1/Guoxian_Dai/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/data1/Guoxian_Dai/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/data1/Guoxian_Dai/CUB_200_2011/image_class_labels.txt"
elif [[ $DATASET_NAME = "car196" ]]; then
ROOT_DIR="/data1/Guoxian_Dai/car196"
IMAGE_TXT="/data1/Guoxian_Dai/car196/cars_annos.mat"
TRAIN_TEST_SPLIT_TXT="/data1/Guoxian_Dai/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/data1/Guoxian_Dai/CUB_200_2011/image_class_labels.txt"
fi
LEARNING_RATE=0.001
LEARNING_RATE2=0.0001
TRAIN_BATCH_SIZE=64
PYTHON=py_gxdai
elif [ $(hostname) = 'MARS' ]; then
echo "running code on 102"
echo "Activate anaconda"
ANACONDA3=/home/gxdai/anaconda3
source ${ANACONDA3}/etc/profile.d/conda.sh
source ${ANACONDA3}/bin/activate py37
if [[ $DATASET_NAME = "cub200" ]]; then
echo "DATASET_NAME = $DATASET_NAME"
ROOT_DIR="/data/Guoxian_Dai/CUB_200_2011/images"
IMAGE_TXT="/data/Guoxian_Dai/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/data/Guoxian_Dai/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/data/Guoxian_Dai/CUB_200_2011/image_class_labels.txt"
elif [[ $DATASET_NAME = "online_product" ]]; then
echo "Online product"
ROOT_DIR="/data/Guoxian_Dai/Stanford_Online_Products"
IMAGE_TXT="/data/Guoxian_Dai/Stanford_Online_Products/Ebay_train.txt"
TRAIN_TEST_SPLIT_TXT="/data/Guoxian_Dai/Stanford_Online_Products/Ebay_test.txt"
LABEL_TXT="/data/Guoxian_Dai/CUB_200_2011/image_class_labels.txt"
elif [[ $DATASET_NAME = "car196" ]]; then
ROOT_DIR="/data/Guoxian_Dai/car196"
IMAGE_TXT="/data/Guoxian_Dai/car196/cars_annos.mat"
TRAIN_TEST_SPLIT_TXT="/data/Guoxian_Dai/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/data/Guoxian_Dai/CUB_200_2011/image_class_labels.txt"
fi
LEARNING_RATE=0.001
LEARNING_RATE2=0.0001
TRAIN_BATCH_SIZE=64
PYTHON=py_gxdai
elif [ $(hostname) = 'MERCURY' ]; then
echo "running code on 101"
echo "Activate anaconda"
ANACONDA3=/home/gxdai/anaconda3
source ${ANACONDA3}/etc/profile.d/conda.sh
source ${ANACONDA3}/bin/activate py37
ROOT_DIR="/data/Guoxian_Dai/CUB_200_2011/images"
IMAGE_TXT="/data/Guoxian_Dai/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/data/Guoxian_Dai/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/data/Guoxian_Dai/CUB_200_2011/image_class_labels.txt"
LEARNING_RATE=0.0001
TRAIN_BATCH_SIZE=32
PYTHON=py_gxdai
elif [ $(hostname) = 'gxdai-Precision-7920-Tower' ]; then
# running code on the dgx1
ROOT_DIR="/home/gxdai/cub_2011/CUB_200_2011/images"
IMAGE_TXT="/home/gxdai/cub_2011/CUB_200_2011/images.txt"
TRAIN_TEST_SPLIT_TXT="/home/gxdai/cub_2011/CUB_200_2011/train_test_split.txt"
LABEL_TXT="/home/gxdai/cub_2011/CUB_200_2011/image_class_labels.txt"
LEARNING_RATE=0.001
PYTHON=python
fi
# [] for traditional shell
# [[ ]] for the updated version
# $#: the total number of arguments
MARGIN=20
MEAN_VALUE=10
# STD_VALUE=4
# change embeeding size with cmd arguments
EMBEDDING_SIZE=64
# weight file for contrastive loss on CUB dataset
# WEIGHT_FILE="checkpoint/cub200/contrastive_loss/64/model_0_.pth"
# weight file for focal contrastive loss on CUB dataset
# WEIGHT_FILE="checkpoint/cub200/focal_contrastive_loss/64/model_21_.pth"
# weight file for focal triplet loss on CUB dataset
# WEIGHT_FILE="checkpoint/cub200/focal_triplet_loss/model_69_.pth"
# weight file for triplet loss on CUB dataset
# WEIGHT_FILE="checkpoint/cub200/triplet_loss/64/model_18_.pth"
# weight file for contrastive loss on CAR dataset
# WEIGHT_FILE="checkpoint/car196/contrastive_loss/64/model_24_.pth"
# weight file for focal contrastive loss on CAR dataset
WEIGHT_FILE="checkpoint/car196/focal_contrastive_loss/64/model_24_.pth"
# weight file for triplet loss on CAR dataset
# WEIGHT_FILE="checkpoint/car196/triplet_loss/64/model_24_.pth"
# weight file for focal triplet loss on CAR dataset
# WEIGHT_FILE="checkpoint/car196/focal_triplet_loss/64/model_42_.pth"
MODE="training"
echo "${DATASET_NAME}_${LOSS_TYPE}_margin_${MARGIN}_embedding_size_${EMBEDDING_SIZE}_mean_${MEAN_VALUE}_std_${STD_VALUE}.txt" 2>&1
CUDA_VISIBLE_DEVICES=$GPU_ID $PYTHON main.py \
--dataset_name $DATASET_NAME \
--mode $MODE \
--weight_file $WEIGHT_FILE \
--manual_seed $MANUAL_SEED \
--optimizer "rmsprop" \
--pair_type "matrix" \
--train_batch_size $TRAIN_BATCH_SIZE \
--momentum 0.9 \
--learning_rate $LEARNING_RATE \
--learning_rate2 ${LEARNING_RATE2} \
--learning_rate_decay_type "fixed" \
--loss_type $LOSS_TYPE \
--margin $MARGIN \
--root_dir $ROOT_DIR \
--image_txt $IMAGE_TXT \
--train_test_split_txt $TRAIN_TEST_SPLIT_TXT \
--label_txt $LABEL_TXT \
--focal_decay_factor "1000000000.0" \
--display_step 20 \
--eval_step 3 \
--embedding_size $EMBEDDING_SIZE \
--mean_value $MEAN_VALUE \
--std_value $STD_VALUE \
--num_epochs_per_decay 5 # > "${DATASET_NAME}_${LOSS_TYPE}_margin_${MARGIN}_embedding_size_${EMBEDDING_SIZE}_mean_${MEAN_VALUE}_std_${STD_VALUE}.txt" 2>&1
#--with_regularizer
# Explannation for 2 and 1, file descriptor
# 2: stderr
# 1: stdout
# >file 2>&1: we are doing redirecting stdout 1 to file, meanwhile redirecting stderr 2 to the same place as stdout 1