import argparse

def parse_train_args():
    parser = argparse.ArgumentParser()
    
    parser.add_argument("--model_name",
                        "-mn",
                        type = str,
                        default = None,
                        help = 'Name of model to load or create')
    parser.add_argument("--list",
                        "-l",
                        type = str,
                        choices = ["model","train","test","net"],
                        default = None,
                        help = "List all available values")
    parser.add_argument("--net_config",
                        "-nc",
                        type = str,
                        metavar = "FILENAME",
                        default = None,
                        help = 'Name of network config file')
    parser.add_argument("--train_config",
                        "-tc",
                        type = str,
                        metavar = "FILENAME",
                        default = None,
                        help = 'Name of training config file')
    parser.add_argument("--epochs",
                        "-e",
                        type = int,
                        metavar = "NUM",
                        default = None,
                        help = "Amount of epochs to train, overrides config file")
    parser.add_argument("--batch_size",
                        "-b",
                        type = int,
                        metavar = "NUM",
                        default = 8,
                        help = "Size of batch during training, overrides config file")
    parser.add_argument("--weights",
                        "-w",
                        type = str,
                        choices = ["last","best"],
                        default = "last",
                        help = "Which model checkpoint to load")
    parser.add_argument("--verbose",
                        "-v",
                        action="store_true",
                        default = False,
                        help = "More logs")
    parser.add_argument("--new_model",
                        "-new",
                        action = 'store_true',
                        default = False,
                        help='Create new model or replace existing with that name')
    
    return vars(parser.parse_args())

def parse_test_args():
    #TODO
    pass
3362696f1668b4cb771e80f4c0fabef9e81f9a90
<mask token>

<mask token>


def parse_train_args():
    parser = argparse.ArgumentParser()
    parser.add_argument('--model_name', '-mn', type=str, default=None, help
        ='Name of model to load or create')
    parser.add_argument('--list', '-l', type=str, choices=['model', 'train',
        'test', 'net'], default=None, help='List all available values')
    parser.add_argument('--net_config', '-nc', type=str, metavar='FILENAME',
        default=None, help='Name of network config file')
    parser.add_argument('--train_config', '-tc', type=str, metavar=
        'FILENAME', default=None, help='Name of training config file')
    parser.add_argument('--epochs', '-e', type=int, metavar='NUM', default=
        None, help='Amount of epochs to train, overrides config file')
    parser.add_argument('--batch_size', '-b', type=int, metavar='NUM',
        default=8, help='Size of batch during training, overrides config file')
    parser.add_argument('--weights', '-w', type=str, choices=['last',
        'best'], default='last', help='Which model checkpoint to load')
    parser.add_argument('--verbose', '-v', action='store_true', default=
        False, help='More logs')
    parser.add_argument('--new_model', '-new', action='store_true', default
        =False, help='Create new model or replace existing with that name')
    return vars(parser.parse_args())


<mask token>

<mask token>


def parse_train_args():
    parser = argparse.ArgumentParser()
    parser.add_argument('--model_name', '-mn', type=str, default=None, help
        ='Name of model to load or create')
    parser.add_argument('--list', '-l', type=str, choices=['model', 'train',
        'test', 'net'], default=None, help='List all available values')
    parser.add_argument('--net_config', '-nc', type=str, metavar='FILENAME',
        default=None, help='Name of network config file')
    parser.add_argument('--train_config', '-tc', type=str, metavar=
        'FILENAME', default=None, help='Name of training config file')
    parser.add_argument('--epochs', '-e', type=int, metavar='NUM', default=
        None, help='Amount of epochs to train, overrides config file')
    parser.add_argument('--batch_size', '-b', type=int, metavar='NUM',
        default=8, help='Size of batch during training, overrides config file')
    parser.add_argument('--weights', '-w', type=str, choices=['last',
        'best'], default='last', help='Which model checkpoint to load')
    parser.add_argument('--verbose', '-v', action='store_true', default=
        False, help='More logs')
    parser.add_argument('--new_model', '-new', action='store_true', default
        =False, help='Create new model or replace existing with that name')
    return vars(parser.parse_args())


def parse_test_args():
    pass

import argparse


def parse_train_args():
    parser = argparse.ArgumentParser()
    parser.add_argument('--model_name', '-mn', type=str, default=None, help
        ='Name of model to load or create')
    parser.add_argument('--list', '-l', type=str, choices=['model', 'train',
        'test', 'net'], default=None, help='List all available values')
    parser.add_argument('--net_config', '-nc', type=str, metavar='FILENAME',
        default=None, help='Name of network config file')
    parser.add_argument('--train_config', '-tc', type=str, metavar=
        'FILENAME', default=None, help='Name of training config file')
    parser.add_argument('--epochs', '-e', type=int, metavar='NUM', default=
        None, help='Amount of epochs to train, overrides config file')
    parser.add_argument('--batch_size', '-b', type=int, metavar='NUM',
        default=8, help='Size of batch during training, overrides config file')
    parser.add_argument('--weights', '-w', type=str, choices=['last',
        'best'], default='last', help='Which model checkpoint to load')
    parser.add_argument('--verbose', '-v', action='store_true', default=
        False, help='More logs')
    parser.add_argument('--new_model', '-new', action='store_true', default
        =False, help='Create new model or replace existing with that name')
    return vars(parser.parse_args())


def parse_test_args():
    pass

import argparse

def parse_train_args():
    parser = argparse.ArgumentParser()
    
    parser.add_argument("--model_name",
                        "-mn",
                        type = str,
                        default = None,
                        help = 'Name of model to load or create')
    parser.add_argument("--list",
                        "-l",
                        type = str,
                        choices = ["model","train","test","net"],
                        default = None,
                        help = "List all available values")
    parser.add_argument("--net_config",
                        "-nc",
                        type = str,
                        metavar = "FILENAME",
                        default = None,
                        help = 'Name of network config file')
    parser.add_argument("--train_config",
                        "-tc",
                        type = str,
                        metavar = "FILENAME",
                        default = None,
                        help = 'Name of training config file')
    parser.add_argument("--epochs",
                        "-e",
                        type = int,
                        metavar = "NUM",
                        default = None,
                        help = "Amount of epochs to train, overrides config file")
    parser.add_argument("--batch_size",
                        "-b",
                        type = int,
                        metavar = "NUM",
                        default = 8,
                        help = "Size of batch during training, overrides config file")
    parser.add_argument("--weights",
                        "-w",
                        type = str,
                        choices = ["last","best"],
                        default = "last",
                        help = "Which model checkpoint to load")
    parser.add_argument("--verbose",
                        "-v",
                        action="store_true",
                        default = False,
                        help = "More logs")
    parser.add_argument("--new_model",
                        "-new",
                        action = 'store_true',
                        default = False,
                        help='Create new model or replace existing with that name')
    
    return vars(parser.parse_args())

def parse_test_args():
    #TODO
    pass