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train.sh
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train.sh
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device=1
LOG=${save_dir}"res.log"
echo ${LOG}
depth=(9)
n_ctx=(12)
t_n_ctx=(4)
for i in "${!depth[@]}";do
for j in "${!n_ctx[@]}";do
## train on the VisA dataset
base_dir=${depth[i]}_${n_ctx[j]}_${t_n_ctx[0]}_multiscale
save_dir=./checkpoints/${base_dir}/
CUDA_VISIBLE_DEVICES=${device} python train.py --dataset visa --train_data_path /remote-home/iot_zhouqihang/data/Visa \
--save_path ${save_dir} \
--features_list 6 12 18 24 --image_size 518 --batch_size 8 --print_freq 1 \
--epoch 15 --save_freq 1 --depth ${depth[i]} --n_ctx ${n_ctx[j]} --t_n_ctx ${t_n_ctx[0]}
wait
done
done
LOG=${save_dir}"res.log"
echo ${LOG}
depth=(9)
n_ctx=(12)
t_n_ctx=(4)
for i in "${!depth[@]}";do
for j in "${!n_ctx[@]}";do
## train on the VisA dataset
base_dir=${depth[i]}_${n_ctx[j]}_${t_n_ctx[0]}_multiscale_visa
save_dir=./checkpoints/${base_dir}/
CUDA_VISIBLE_DEVICES=${device} python train.py --dataset mvtec --train_data_path /remote-home/iot_zhouqihang/data/mvdataset \
--save_path ${save_dir} \
--features_list 6 12 18 24 --image_size 518 --batch_size 8 --print_freq 1 \
--epoch 15 --save_freq 1 --depth ${depth[i]} --n_ctx ${n_ctx[j]} --t_n_ctx ${t_n_ctx[0]}
wait
done
done