import os

num_to_forgets = [900, 1800, 3000, 6000]

for num_to_forget in num_to_forgets:
    ## nabla
    # os.system(
    #     "python nabla_unlearning_main.py --split forget --dataset cifar10 --model resnet18k --dataroot=data/cifar10/ --filters 1.0 "
    #     "--lr 0.001 --resume /storage/4T_add/grok-adversarial/models/Resnet-CIFAR10_42_0 --resume_step 1382 --disable-bn "
    #     "--weight-decay 0.1 --batch-size 256 --epochs 10 --forget_class 0,1 --num-to-forget " + str(
    #         num_to_forget) + " --seed 3")

    ## fisher
    # os.system(
    #     'python main_forget_sparse.py --split forget --dataset cifar10 --model resnet18k --dataroot=data/cifar10/ --filters 1.0 '
    #     '--lr 0.0001 --resume /storage/4T_add/grok-adversarial/models/Resnet-CIFAR10_42_0 --resume_step 1382 '
    #     '--disable-bn --weight-decay 0.1 --batch-size 256 --epochs 5 --forget_class 0,1 '
    #     '--num-to-forget ' + str(num_to_forget) + ' --seed 3 --unlearn fisher')

    ## FT
    # os.system(
    #     "python main_forget_sparse.py --split forget --dataset cifar10 --model resnet18k --dataroot=data/cifar10/ "
    #     "--filters 1.0 --lr 0.001 --resume /storage/4T_add/grok-adversarial/models/Resnet-CIFAR10_42_0 "
    #     "--resume_step 1382 --disable-bn --weight-decay 0.1 --batch-size 256 --epochs 15 --forget_class 0,1 "
    #     "--num-to-forget " + str(num_to_forget) + " --seed 3 --unlearn FT")

    ## GA
    os.system(
        "python main_forget_sparse.py --split forget --dataset cifar10 --model resnet18k --dataroot=data/cifar10/ "
        "--filters 1.0 --lr 0.0001 --resume /storage/4T_add/grok-adversarial/models/Resnet-CIFAR10_42_0 "
        "--resume_step 1382 --disable-bn --weight-decay 0.1 --batch-size 256 --epochs 5 --forget_class 0,1 "
        "--num-to-forget " + str(num_to_forget) + " --seed 3 --unlearn GA")
