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main_stage2.sh
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main_stage2.sh
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## noise-free degradations with isotropic Gaussian blurs
# training knowledge distillation
CUDA_VISIBLE_DEVICES=0 python3 main_stage2.py --dir_data='/root/datasets' \
--model='blindsr' \
--scale='4' \
--blur_type='iso_gaussian' \
--noise=0.0 \
--sig_min=0.2 \
--sig_max=4.0 \
--sig 2.6 \
--n_GPUs=1 \
--epochs_encoder 0 \
--epochs_sr 600 \
--data_test Set5 \
--st_save_epoch 95 \
--n_feats 128 \
--patch_size 64 \
--task_iter 5 \
--test_iter 5 \
--meta_batch_size 5 \
--task_batch_size 16 \
--lr_sr 1e-4 \
--lr_task 1e-2 \
--pre_train="./experiment/stage1.pt" \
--resume 0 \
--test_every 240 \
--print_every 40 \
--lr_decay_sr 150 \
--data_train DF2K \
--save stage2
#--batch_size 32 \
# anisotropic + noise
# CUDA_VISIBLE_DEVICES=0 python3 main_stage2.py --dir_data='/root/datasets' \
# --model='blindsr' \
# --scale='4' \
# --blur_type='aniso_gaussian' \
# --noise=25.0 \
# --lambda_min=0.2 \
# --lambda_max=4.0 \
# --n_GPUs=1 \
# --epochs_encoder 0 \
# --epochs_sr 600 \
# --data_test Set5 \
# --st_save_epoch 95 \
# --n_feats 128 \
# --patch_size 64 \
# --task_iter 5 \
# --test_iter 5 \
# --meta_batch_size 5 \
# --task_batch_size 16 \
# --lr_sr 1e-4 \
# --lr_task 1e-2 \
# --pre_train="./experiment/stage1.pt" \
# --resume 0 \
# --test_every 240 \
# --print_every 40 \
# --lr_decay_sr 150 \
# --data_train DF2K \
# --save stage2