import argparse


def get_parser():
    parser = argparse.ArgumentParser(description='EVP training and testing')
    parser.add_argument('--amsgrad', action='store_true',
                        help='if true, set amsgrad to True in an Adam or AdamW optimizer.')
    parser.add_argument('-b', '--batch-size', default=8, type=int)
    parser.add_argument('--ck_bert', default='bert-base-uncased', help='pre-trained BERT weights')
    parser.add_argument('--dataset', default='refcoco', help='refcoco, refcoco+, or refcocog')
    parser.add_argument('--ddp_trained_weights', action='store_true',
                        help='Only needs specified when testing,'
                             'whether the weights to be loaded are from a DDP-trained model')
    parser.add_argument('--device', default='cuda:0', help='device')  # only used when testing on a single machine
    parser.add_argument('--epochs', default=40, type=int, metavar='N', help='number of total epochs to run')
    parser.add_argument('--fusion_drop', default=0.0, type=float, help='dropout rate for PWAMs')
    parser.add_argument('--img_size', default=480, type=int, help='input image size')
    parser.add_argument("--local_rank", type=int, default=0, help='local rank for DistributedDataParallel')
    parser.add_argument("--local-rank", type=int, default=0, help='local rank for DistributedDataParallel')
    parser.add_argument('--lr', default=0.00005, type=float, help='the initial learning rate')
    parser.add_argument('--model_id', default='evp', help='name to identify the model')
    parser.add_argument('--output-dir', default='./checkpoints/', help='path where to save checkpoint weights')
    parser.add_argument('--pin_mem', action='store_true',
                        help='If true, pin memory when using the data loader.')
    parser.add_argument('--pretrained_swin_weights', default='',
                        help='path to pre-trained Swin backbone weights')
    parser.add_argument('--print-freq', default=10, type=int, help='print frequency')
    parser.add_argument('--refer_data_root', default='./refer/data/', help='REFER dataset root directory')
    parser.add_argument('--resume', default='', help='resume from checkpoint')
    parser.add_argument('--split', default='val')
    parser.add_argument('--splitBy', default='unc')
    parser.add_argument('--wd', '--weight-decay', default=1e-2, type=float, metavar='W', help='weight decay',
                        dest='weight_decay')
    parser.add_argument('-j', '--workers', default=8, type=int, metavar='N', help='number of data loading workers')
    parser.add_argument('--token_length', default=77, type=int)

    return parser


if __name__ == "__main__":
    parser = get_parser()
    args_dict = parser.parse_args()