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Python error: the following arguments are required :

I am not familiar with Python, trying to build some DNN. So when I tried to parse some arguments I got this error in main.
usage: main.py [-h] [-j N] [--resume PATH] [--epochs N] [--start-epoch N] [-b N] [--lr LR]
[--weight-decay W] [-e] [--print-freq N]
DIR
main.py: error: the following arguments are required: DIR
Here is some part of the code:
# Parse arguments and prepare program
parser = argparse.ArgumentParser(description='Training and Using ColorNet')
parser.add_argument('data', metavar='DIR', help='path to dataset')
parser.add_argument('-j', '--workers', default=0, type=int, metavar='N', help='number of data loading workers (default: 0)')
parser.add_argument('--resume', default='', type=str, metavar='PATH', help='path to .pth file checkpoint (default: none)')
parser.add_argument('--epochs', default=50, type=int, metavar='N', help='number of total epochs to run')
parser.add_argument('--start-epoch', default=0, type=int, metavar='N', help='manual epoch number (overridden if loading from checkpoint)')
parser.add_argument('-b', '--batch-size', default=16, type=int, metavar='N', help='size of mini-batch (default: 16)')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float, metavar='LR', help='learning rate at start of training')
parser.add_argument('--weight-decay', '--wd', default=1e-10, type=float, metavar='W', help='weight decay (default: 1e-4)')
parser.add_argument('-e', '--evaluate', dest='evaluate', action='store_true', help='use this flag to validate without training')
parser.add_argument('--print-freq', '-p', default=10, type=int, metavar='N', help='print frequency (default: 10)')
# Current best losses
best_losses = 1000.0
use_gpu = torch.cuda.is_available()
def main():
global args, best_losses, use_gpu
args = parser.parse_args()
print('Arguments: {}'.format(args))
I read some comments to change
parser.parse_args()
to
parser.parse_args(args)
but it didn't work :)

As DIR doesn't have a default value, you need to supply one when running the program. The easiest way to do this is via a command line interface. Consult the documentation of the library you are using for further hints on that.

Regarding installation of utils.logger module

when i am trying to install that particular module utils.logger ,it is showing
ERROR: Could not find a version that satisfies the requirement utils.logger (from versions: none)
ERROR: No matching distribution found for utils.logger.Sorry if my way of interpretation of question is not in an appropriate manner as i am a novice.
This is the code
import logging
import functools
import argparse
import os
from datetime import datetime
from utils.logger import setlogger
from utils.train_utils import train_utils
args = None
def parse_args():
parser = argparse.ArgumentParser(description='Train')
# basic parameters
parser.add_argument('--model_name', type=str, default='cnn_2d', help='the name of the model')
parser.add_argument('--data_name', type=str, default='CWRUSlice', help='the name of the data')
parser.add_argument('--data_dir', type=str, default= "E:\Data\西储大学轴承数据中心网站", help='the directory of the data')
parser.add_argument('--normlizetype', type=str, choices=['0-1', '1-1', 'mean-std'], default='0-1', help='data normalization methods')
parser.add_argument('--processing_type', type=str, choices=['R_A', 'R_NA', 'O_A'], default='R_A',
help='R_A: random split with data augmentation, R_NA: random split without data augmentation, O_A: order split with data augmentation')
parser.add_argument('--cuda_device', type=str, default='0', help='assign device')
parser.add_argument('--checkpoint_dir', type=str, default='./checkpoint', help='the directory to save the model')
parser.add_argument("--pretrained", type=bool, default=True, help='whether to load the pretrained model')
parser.add_argument('--batch_size', type=int, default=64, help='batchsize of the training process')
parser.add_argument('--num_workers', type=int, default=0, help='the number of training process')
# optimization information
parser.add_argument('--opt', type=str, choices=['sgd', 'adam'], default='adam', help='the optimizer')
parser.add_argument('--lr', type=float, default=0.001, help='the initial learning rate')
parser.add_argument('--momentum', type=float, default=0.9, help='the momentum for sgd')
parser.add_argument('--weight_decay', type=float, default=1e-5, help='the weight decay')
parser.add_argument('--lr_scheduler', type=str, choices=['step', 'exp', 'stepLR', 'fix'], default='fix', help='the learning rate schedule')
parser.add_argument('--gamma', type=float, default=0.1, help='learning rate scheduler parameter for step and exp')
parser.add_argument('--steps', type=str, default='9', help='the learning rate decay for step and stepLR')
# save, load and display information
parser.add_argument('--max_epoch', type=int, default=100, help='max number of epoch')
parser.add_argument('--print_step', type=int, default=100, help='the interval of log training information')
args = parser.parse_args()
return args
if name == 'main':
args = parse_args()
os.environ['CUDA_VISIBLE_DEVICES'] = args.cuda_device.strip()
# Prepare the saving path for the model
sub_dir = args.model_name+'_'+args.data_name + '_' + datetime.strftime(datetime.now(), '%m%d-%H%M%S')
save_dir = os.path.join(args.checkpoint_dir, sub_dir)
if not os.path.exists(save_dir):
os.makedirs(save_dir)
# set the logger
setlogger(os.path.join(save_dir, 'training.log'))
# save the args
for k, v in args.__dict__.items():
logging.info("{}: {}".format(k, v))
trainer = train_utils(args, save_dir)
trainer.setup()
trainer.train()

SystemExit 2 error in the compilation of code when calling -e', '--episode', type=int, default=2000,

my code is a below:
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-e', '--episode', type=int, default=2000,
help='number of episode to run')
parser.add_argument('-b', '--batch_size', type=int, default=32,
help='batch size for experience replay')
parser.add_argument('-i', '--initial_invest', type=int, default=20000,
help='initial investment amount')
parser.add_argument('-m', '--mode', type=str, required=True,
help='either "train" or "test"')
parser.add_argument('-w', '--weights', type=str, help='a trained model weights')
args = parser.parse_args()
maybe_make_dir('weights')
maybe_make_dir('portfolio_val')
Error:-
usage: [-h] [-e EPISODE] [-b BATCH_SIZE] [-i INITIAL_INVEST] -m MODE
[-w WEIGHTS]
: error: the following arguments are required: -m/--mode
An exception has occurred, use %tb to see the full traceback.
SystemExit: 2
So in the above error i am not able to understand what is the mistake i have also imported all the libraries correctly.

try changing this:
parser.add_argument('-m', '--mode', type=str, required=True,
help='either "train" or "test"')
to this: (notice nargs and const)
parser.add_argument('-m', '--mode',nargs='?', const='' , type=str, required=True,
help='either "train" or "test"')
then you can add this to your code:
if len(args.mode) == 0:
print('-m either "train" or "test"')
import sys
sys.exit() #closes python script
as explained here: https://stackoverflow.com/a/58396626/13093413

python get changed (non-default) cli arguments?

Given an argument parser with n arguments, where I change the default value of only a small subset every run from the command line, is there a clean way of extracting a dict/namespace of all the non-default k,v arguments?
parser = argparse.ArgumentParser()
parser.add_argument("--a",type=str,default='a')
parser.add_argument("--b",type=str,default='b')
parser.add_argument("--c",type=str,default='c')
parser.add_argument("--d",type=str,default='d')
And
python run.py --a "e"
I would like to have
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--a",type=str,default='a')
parser.add_argument("--b",type=str,default='b')
parser.add_argument("--c",type=str,default='c')
parser.add_argument("--d",type=str,default='d')
non_default = parse_non_default(parser) # non_default = {'a':'e'}

You could lookup the parser and compare which values differenciate:
import argparse
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--a", type=str, default='a')
parser.add_argument("--b", type=str, default='b')
parser.add_argument("--c", type=str, default='c')
parser.add_argument("--d", type=str, default='d')
parser.add_argument("--n", type=int, default=999)
args = parser.parse_args(['--a', 'e']) # Test CLI arguments!
non_default = {
opt.dest: getattr(args, opt.dest)
for opt in parser._option_string_actions.values()
if hasattr(args, opt.dest) and opt.default != getattr(args, opt.dest)
}
print(non_default)
main()
Out:
{'a': 'e'}

python - argparse one argument instead of several others

For example I have options:
parser.add_argument('-b', action="store_true")
parser.add_argument('-c', action="store_true")
parser.add_argument('-d', action="store_true")
I want to enable all of them with synonym option "-a". Is it possible?

I think it is simplest to do this after parse_args():
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-b', action="store_true")
parser.add_argument('-c', action="store_true")
parser.add_argument('-d', action="store_true")
parser.add_argument('-a', action="store_true")
args = parser.parse_args()
if args.a: args.b = args.c = args.d = True
Alternatively, you could do it with a custom action, but I think it is overkill:
import argparse
class AllAction(argparse.Action):
def __call__(self, parser, args, values, option_string = None):
# print '{n} {v} {o}'.format(n = args, v = values, o = option_string)
for param in ['a', 'b', 'c', 'd']:
setattr(args, param, True)
parser = argparse.ArgumentParser()
parser.add_argument('-b', action="store_true")
parser.add_argument('-c', action="store_true")
parser.add_argument('-d', action="store_true")
parser.add_argument('-a', action = AllAction, nargs = '?')
args = parser.parse_args()
print(args)