
# choices of sparse_init are [snip, ERK, ER, uniform, uniform_plus]
sparse_init=ERK
data=cifar10

model=cifar_resnet_20_8
for seed in 18 19 20
do
    for density in 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
    do
        python main.py --sparse --seed $seed --sparse_init $sparse_init --fix --lr 0.1 --density $density --model $model --data $data --epoch 160
    done
done

model=cifar_resnet_20_16
for seed in 18 19 20
do
    for density in 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
    do
        python main.py --sparse --seed $seed --sparse_init $sparse_init --fix --lr 0.1 --density $density --model $model --data $data --epoch 160
    done
done

model=cifar_resnet_20_24
for seed in 18 19 20
do
    for density in 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
    do
        python main.py --sparse --seed $seed --sparse_init $sparse_init --fix --lr 0.1 --density $density --model $model --data $data --epoch 160
    done
done

model=cifar_resnet_20_32
for seed in 18 19 20
do
    for density in 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
    do
        python main.py --sparse --seed $seed --sparse_init $sparse_init --fix --lr 0.1 --density $density --model $model --data $data --epoch 160
    done
done

model=cifar_resnet_20_40
for seed in 18 19 20
do
    for density in 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
    do
        python main.py --sparse --seed $seed --sparse_init $sparse_init --fix --lr 0.1 --density $density --model $model --data $data --epoch 160
    done
done

model=cifar_resnet_20_56
for seed in 18 19 20
do
    for density in 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
    do
        python main.py --sparse --seed $seed --sparse_init $sparse_init --fix --lr 0.1 --density $density --model $model --data $data --epoch 160
    done
done

conda deactivate torch151