import random, argparse
from .share_args import add_shared_args


def obtain_cls_kd_args():
    parser = argparse.ArgumentParser(
        description="Train a classification model on typical image classification datasets.",
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
    )
    parser.add_argument("--resume", type=str, help="Resume path.")
    parser.add_argument("--init_model", type=str, help="The initialization model path.")
    parser.add_argument(
        "--model_config", type=str, help="The path to the model configuration"
    )
    parser.add_argument(
        "--optim_config", type=str, help="The path to the optimizer configuration"
    )
    parser.add_argument("--procedure", type=str, help="The procedure basic prefix.")
    parser.add_argument(
        "--KD_checkpoint",
        type=str,
        help="The teacher checkpoint in knowledge distillation.",
    )
    parser.add_argument(
        "--KD_alpha", type=float, help="The alpha parameter in knowledge distillation."
    )
    parser.add_argument(
        "--KD_temperature",
        type=float,
        help="The temperature parameter in knowledge distillation.",
    )
    # parser.add_argument('--KD_feature',       type=float,                 help='Knowledge distillation at the feature level.')
    add_shared_args(parser)
    # Optimization options
    parser.add_argument(
        "--batch_size", type=int, default=2, help="Batch size for training."
    )
    args = parser.parse_args()

    if args.rand_seed is None or args.rand_seed < 0:
        args.rand_seed = random.randint(1, 100000)
    assert args.save_dir is not None, "save-path argument can not be None"
    return args