for i in $(seq 0 4); do
  data_types=("Math1" "Math2" "FrcSub" "Junyi" "XES3G5M" "Assist17" "EdNet-1" "NeurIPS2020" "SLP-PHY" "SLP-Math" "SLP-BIO")
  batch_sizes=(256 256 32 4096 4096 4096 4096 4096 256 256 256)
  gcn_layers=(2 2 2 2 2 5 2 2 2 2 2)
   epoch=(10 10 15 12 12 12 12 10 15 15 15)
   keep_prob=(1 1 1 1 1 1 1 1 1 1 1)
   lr=(3e-3 5e-4 6e-3 5e-4 3e-3 4e-3 4e-3 1e-3 4e-3 4e-3 4e-3)
   weight_decay=(5e-4 0 5e-8 5e-6 5e-8 5e-8 5e-8 0 5e-8 5e-8 5e-8)
   activation=("ELU" "ELU" "ELU" "ELU" "ReLU" "ELU" "ReLU" "ELU" "ELU" "ELU" "ELU")
    for j in ${!data_types[@]}; do
     python exp_ulcdf.py --method=ulcdf --if_type=mirt --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=${epoch[j]}  --keep_prob=${keep_prob[j]}  --lr=${lr[j]} --weight_decay=${weight_decay[j]}
     python exp_ulcdf.py --method=ulcdf --if_type=cdmfkc --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=${epoch[j]}  --keep_prob=${keep_prob[j]}  --lr=${lr[j]} --weight_decay=${weight_decay[j]}
     python exp_ulcdf.py --method=ulcdf --if_type=irt --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=20  --keep_prob=${keep_prob[j]}  --lr=1e-4 --weight_decay=${weight_decay[j]}
     python exp_ulcdf.py --method=ulcdf --if_type=kscd --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=${epoch[j]}  --keep_prob=${keep_prob[j]}  --lr=${lr[j]} --weight_decay=${weight_decay[j]}
     python exp_ulcdf.py --method=ulcdf --if_type=kancd --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=${epoch[j]}  --keep_prob=${keep_prob[j]}  --lr=${lr[j]} --weight_decay=${weight_decay[j]}
     python exp_ulcdf.py --method=ulcdf --if_type=dp-linear --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=${epoch[j]}  --keep_prob=${keep_prob[j]}  --lr=${lr[j]} --weight_decay=${weight_decay[j]}
     python exp_ulcdf.py --method=ulcdf --if_type=ncd --activation=${activation[j]} --data_type=${data_types[j]} --test_size=0.2 --seed=$i --batch_size=${batch_sizes[j]} --device=cuda:0 --gcn_layers=${gcn_layers[j]} --epoch=${epoch[j]}  --keep_prob=${keep_prob[j]}  --lr=${lr[j]} --weight_decay=${weight_decay[j]}
   done
done
