def _get_args(args=None):
import sys
import os
sys.path.append(os.path.join(CUR_DIR, '..'))
from utils import util
parser, arg = util.get_args_parser('dataset')
arg('--data-directory', type=str, help='data are loading from here')
arg('--count', type=int, default=10, help='samples count to show')
arg('--phase',
type=str,
default='train',
metavar='train|valid',
help='dataset of which phase to show')
arg('--path',
'-p',
type=str,
nargs='+',
default=None,
help='path of image to show')
return parser.parse_args(args)
def _get_args(args=None):
import sys
import os
sys.path.append(os.path.join(CUR_DIR, '..'))
from utils import util
parser, arg = util.get_args_parser('Classes_make_anno')
arg('--data-directory', type=str, help='data are loading from here'),
return parser.parse_args(args)
def get_args_parser(self, actions=actions, default_action='train', args=None):
from utils.util import get_args_parser
parser, arg = get_args_parser('logloader')
actions_str = '|'.join(actions.keys())
arg('--save-directory', type=str, default='out', help='save directory')
arg('--execid', type=str, default=None, help='sub directory')
arg('--action', '-a', metavar=actions_str,
type=str, default=default_action, help='actions')
parse_args = parser.__getattribute__('parse_args')
def _parse_args(*args, **kwargs):
args = parse_args(*args, **kwargs)
args.root_log_file = 'log.log'
args.sub_log_file = 'log.log'
return args
parser.__setattr__('parse_args', _parse_args)
return parser, arg
def get_args_parser(self, description, args=None):
from utils.util import get_args_parser
parser, arg = get_args_parser(description)
arg('--phase',
type=str,
default='train',
metavar='|'.join(self.get_phases()),
help='phase to run')
arg('--batch-size',
type=int,
default=64,
metavar='N',
help='input batch size for training (default: 64)')
arg('--test-batch-size',
type=int,
default=64,
metavar='N',
help='input batch size for testing (default: 64)')
arg('--epochs',
type=int,
default=100,
metavar='N',
help='number of epochs to train (default: 100)')
arg('--lr',
type=float,
default=0.01,
metavar='LR',
help='learning rate (default: 0.01)')
arg('--momentum',
type=float,
default=0.5,
metavar='M',
help='SGD momentum (default: 0.5)')
arg('--no-cuda',
action='store_true',
default=False,
help='disables CUDA training')
arg('--seed',
type=int,
default=1,
metavar='Seed',
help='random seed (default: 1)')
arg('--log-interval',
type=int,
default=5,
metavar='N',
help='how many batches to wait before logging training status')
arg('--save-model',
action='store_true',
default=True,
help='save the current Model')
arg('--model', type=str, default='Net', help='model name')
arg('--save-directory',
type=str,
default='out',
help='learnt models and logs are saving here')
arg('--data-directory', type=str, help='data are loading from here')
arg('--model-file', type=str, help='model are loading from here')
arg('--predict-indices',
type=str,
default='all',
help='sample indices to predict')
arg('--no-cache-image',
action='store_true',
default=False,
help='should cache image in memory')
arg('--retry',
action='store_true',
default=True,
help='loss为nan时是否自动需要调整参数重试')
return parser, arg