options.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Python version: 3.6

import argparse


def args_parser():
    parser = argparse.ArgumentParser()
    # federated arguments
    parser.add_argument('--digit_num', type=int, default=3, help="number of each user's original digits, 2-9 is "
                                                                 "meaningful")
    parser.add_argument('--share_ratio', type=float, default=0.1, help="ratio for neighbor data exchanging")
    parser.add_argument('--aggr_model', type=str, default='de',
                        help="aggregation model: de(decentralized) or ps(parameter server)")
    parser.add_argument('--iid', action='store_true', help='whether i.i.d or not')
    parser.add_argument('--excel_row', type=int, default=0, help='record result in xls file')

    parser.add_argument('--epochs', type=int, default=5, help="rounds of training")
    parser.add_argument('--num_users', type=int, default=5, help="number of users: K")
    parser.add_argument('--local_ep', type=int, default=3, help="the number of local epochs: E")
    parser.add_argument('--local_bs', type=int, default=64, help="local batch size: B")
    parser.add_argument('--bs', type=int, default=128, help="test batch size")
    parser.add_argument('--lr', type=float, default=0.01, help="learning rate")
    parser.add_argument('--momentum', type=float, default=0.5, help="SGD momentum (default: 0.5)")
    parser.add_argument('--split', type=str, default='user', help="train-test split type, user or sample")

    # model arguments
    parser.add_argument('--model', type=str, default='mlp', help='model name')
    parser.add_argument('--kernel_num', type=int, default=9, help='number of each kind of kernel')
    parser.add_argument('--kernel_sizes', type=str, default='3,4,5',
                        help='comma-separated kernel size to use for convolution')
    parser.add_argument('--norm', type=str, default='batch_norm', help="batch_norm, layer_norm, or None")
    parser.add_argument('--num_filters', type=int, default=32, help="number of filters for conv nets")
    parser.add_argument('--max_pool', type=str, default='True',
                        help="Whether use max pooling rather than strided convolutions")

    # other arguments
    parser.add_argument('--num_classes', type=int, default=10, help="number of classes")
    parser.add_argument('--num_channels', type=int, default=1, help="number of channels of imges")
    parser.add_argument('--gpu', type=int, default=0, help="GPU ID, -1 for CPU")
    parser.add_argument('--stopping_rounds', type=int, default=10, help='rounds of early stopping')
    parser.add_argument('--verbose', action='store_true', help='verbose print')
    parser.add_argument('--seed', type=int, default=1, help='random seed (default: 1)')
    parser.add_argument('--plot_model', default=False, help='plot model graph via graphviz')
    parser.add_argument('--excel_file', default='result.xlsx', help='name of xls file recording result')
    args = parser.parse_args()
    return args