DN_RGB/code/.ipynb_checkpoints/train-1rec-raft-s-gpu1-res-checkpoint.sh

#!/bin/bash

bash ./prepare.sh
lst=0
for i in {0..3};
do
    if nvidia-smi -i $i | grep -q "python"; then 
        :
    else
        lst=$i
        break
    fi
done

# CUDA_VISIBLE_DEVICES=$lst python main.py --n_GPUs 1 --lr 1e-4 --decay 200-400-600-800 --epoch 1000 --batch_size 16 --n_resblocks 10 --save_models \
# --model RAFTNETS --scale 1 --patch_size 48 --save RAFTS_DEMOSAIC20_R4 --n_feats 64 --data_train DIV2K --recurrence 4 --data_range "1-800/901-942"

# python main.py --model LAMBDANET --n_resblocks 20 --recurrence 1 --save_results --n_GPUs 1 --chop --data_test McM+Kodak24+CBSD68+Urban100 --scale 1 \
# --pre_train ../experiment/LAMBDA_DEMOSAIC20_R1/model/model_best.pt --test_only

CUDA_VISIBLE_DEVICES=$lst python main.py --n_GPUs 1 --lr 1e-4  --batch_size 16  --n_resblocks 20 --save_models \
--epoch 1000 --decay 200-400-600-800 --model RESNET --scale 50 --patch_size 48 \
--save RAFTS_RES --n_feats 64 --data_train DIV2K --recurrence 1 \
--load RAFTS_RES --resume -1