


import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


SCREAMING_SNAKE_CASE			: List[str]				   =					["small", "medium", "large"]

SCREAMING_SNAKE_CASE			: Any				   =					"lm_head.decoder.weight"
SCREAMING_SNAKE_CASE			: Optional[Any]				   =					"lm_head.weight"



def 							UpperCamelCase_( lowerCamelCase_				,					lowerCamelCase_					)       ->		int:
    _lowercase			:				Union[str, Any] 						=						torch.load(lowerCamelCase_					)
    _lowercase			:				List[str] 						=						d.pop(lowerCamelCase_					)
    os.makedirs(lowerCamelCase_				,					exist_ok=lowerCamelCase_					)
    torch.save(lowerCamelCase_				,					os.path.join(lowerCamelCase_				,					lowerCamelCase_					)					)


if __name__ == "__main__":
 SCREAMING_SNAKE_CASE			: Optional[int]				   =					argparse.ArgumentParser()
 parser.add_argument("--dialogpt_path", default=".", type=str)
 SCREAMING_SNAKE_CASE			: str				   =					parser.parse_args()
 for MODEL in DIALOGPT_MODELS:
  SCREAMING_SNAKE_CASE			: Dict				   =					os.path.join(args.dialogpt_path, F"{MODEL}_ft.pkl")
  SCREAMING_SNAKE_CASE			: Union[str, Any]				   =					F"./DialoGPT-{MODEL}"
  convert_dialogpt_checkpoint(
      checkpoint_path,
      pytorch_dump_folder_path,
  )








def 		lowerCamelCase__       (						_A				):







	'''simple docstring'''





	snake_case_						       =	1
	for i in range(1	,      num + 1				):
		fact *= i
	return fact


def 		lowerCamelCase__       (						_A				):







	'''simple docstring'''





	snake_case_						       =	0
	while number > 0:
		snake_case_						       =	number % 10
		sum_of_digits += last_digit
		snake_case_						       =	number // 10  # Removing the last_digit from the given number
	return sum_of_digits


def 		lowerCamelCase__       (						_A = 100				):







	'''simple docstring'''





	snake_case_						       =	factorial(_A				)
	snake_case_						       =	split_and_add(_A				)
	return result


if __name__ == "__main__":
		print(solution(int(input("Enter the Number: ").strip())))
