traineval.py 文件源码

def _GetArguments():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
    parser.add_argument("--interactive", action="store_true", default=False,
        help="Run the script in an interactive mode")
    parser.add_argument("--verbose", action="store_true", default=False,
        help="Visualize all logs")
    parser.add_argument("--voc_devkit_dir", default="data/VOCdevkit",
        help="Root directory of VOC development kit")
    parser.add_argument("--voc_version", default="VOC2007",
        help="Target VOC dataset version")
    parser.add_argument("--model", default="resnet18",
        help="Pretrained model")
    parser.add_argument("--batch_size", default=100, type=int,
        help="Batch size")
    parser.add_argument("--num_data_loading_workers", default=4, type=int,
        help="Number of data loading workers")
    parser.add_argument("--num_epochs", default=50, type=int,
        help="Number of epochs for training")
    parser.add_argument("--initial_learning_rate", default=0.1, type=float,
        help="Initial learning rate for SGD")
    parser.add_argument("--learning_rate_decay_epoch", default=50, type=int,
        help="How frequently the learning rate will be decayed")
    parser.add_argument("--momentum", default=0.9, type=float,
        help="Momentum for learning rate of SGD")
    parser.add_argument("--seed", default=111, type=int,
        help="Random seed")
    parser.add_argument("--save_dir", default="temp_result",
        help="Directory for saving results of train / test")
    args = parser.parse_args()
    params = vars(args)
    print (json.dumps(params, indent=2))
    return params