arg_parser.py

import argparse


def parse_args():
    parser = argparse.ArgumentParser(description="Classification of SalUn Experiments")

    ##################################### Dataset #################################################
    parser.add_argument(
        "--data_path", type=str, default="../dataset", help="location of the data corpus"
    )
    parser.add_argument("--dataset", type=str, default="rfml", help="name of the dataset to use. supports rfml and nids only")
    parser.add_argument("--drop_labels", type=str, default="ARP Spoofing,UDP Flood,Ping Sweep,SYN Flood", help="Which labels to drop for aci-iot dataset")
    parser.add_argument("--drop_feats", type=str, default="Flow ID,Src IP,Dst IP,Timestamp,Connection Type,Flow Bytes/s,Flow Packets/s", help="Which features to drop for aci-iot dataset")
    parser.add_argument("--snrs", default="all", help="which snrs to take")
    parser.add_argument(
        "--input_size", type=int, default=32, help="size of input images"
    )
    parser.add_argument(
        "--data_dir",
        type=str,
        default="./tiny-imagenet-200",
        help="dir to tiny-imagenet",
    )
    parser.add_argument("--num_workers", type=int, default=4)
    parser.add_argument("--num_classes", type=int, default=10)
    parser.add_argument("--valid_percentage", type=float, default=0.1)
    parser.add_argument("--retain_percentage", type=float, default=0.1)

    ##################################### Architecture ############################################
    parser.add_argument(
        "--arch", type=str, default="cnn5", help="model architecture"
    )
    parser.add_argument(
        "--imagenet_arch",
        action="store_true",
        help="architecture for imagenet size samples",
    )
    parser.add_argument(
        "--train_y_file",
        type=str,
        default="./labels/train_ys.pth",
        help="labels for training files",
    )
    parser.add_argument(
        "--val_y_file",
        type=str,
        default="./labels/val_ys.pth",
        help="labels for validation files",
    )

    ##################################### General setting ############################################
    parser.add_argument("--seed", default=2, type=int, help="random seed")
    parser.add_argument(
        "--train_seed",
        default=1,
        type=int,
        help="seed for training (default value same as args.seed)",
    )
    parser.add_argument("--gpu", type=int, default=0, help="gpu device id")
    parser.add_argument(
        "--workers", type=int, default=4, help="number of workers in dataloader"
    )
    parser.add_argument(
        "--save_dir",
        help="The directory used to save the trained models",
        default=None,
        type=str,
    )
    parser.add_argument("--model_path", type=str, default=None, help="the path of original model")

    ##################################### Training setting #################################################
    parser.add_argument("--batch_size", type=int, default=256, help="batch size")
    parser.add_argument("--lr", default=0.1, type=float, help="initial learning rate")
    parser.add_argument("--momentum", default=0.9, type=float, help="momentum")
    parser.add_argument("--weight_decay", default=5e-4, type=float, help="weight decay")
    parser.add_argument(
        "--epochs", default=150, type=int, help="number of total epochs to run"
    )
    parser.add_argument("--warmup", default=0, type=int, help="warm up epochs")
    parser.add_argument("--print_freq", default=100, type=int, help="print frequency")
    parser.add_argument("--decreasing_lr", default="70,120", help="decreasing strategy")
    parser.add_argument("--loss", default="none", help="loss function type")
    parser.add_argument(
        "--no_aug",
        action="store_true",
        default=False,
        help="No augmentation in training dataset (transformation).",
    )
    parser.add_argument("--no-l1-epochs", default=0, type=int, help="non l1 epochs")

    return parser.parse_args()