Demosaic/code/train-0-4rec-lambda-a.sh

#!/bin/bash

bash ./prepare.sh
username=`whoami`

CUDA_VISIBLE_DEVICES=0 python main.py --n_GPUs 1 --lr 1e-4 --decay 200-400-600-800 --epoch 1000 --batch_size 16 --n_resblocks 20 --save_models \
--model LAMBDANETACTA --scale 1 --patch_size 48 --save LAMBDANETACTA_DEMOSAIC20_R4_MSE --n_feats 64 --data_train DIV2K --recurrence 4 \
--dir_data="/data/ssd/public/$username/DNDM/dataset"  --data_range "1-800/901-942" \
--optimizer ADAMW --gclip 1.0 --spectral --loss 1*MSE

# 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