

'''simple docstring'''

import argparse
import os

import torch

from transformers.utils import WEIGHTS_NAME


a  :     int    			=					["small", "medium", "large"]

a  :     Union[str, Any]    			=					"lm_head.decoder.weight"
a  :     List[Any]    			=					"lm_head.weight"





def  lowercase   (	__magic_name__					,       __magic_name__				):



					'''simple docstring'''







					UpperCAmelCase						:				List[str]     =  torch.load(A__				)
					UpperCAmelCase						:				Union[str, Any]     =  d.pop(A__				)
					os.makedirs(A__					,       exist_ok=A__				)
					torch.save(A__					,       os.path.join(A__					,       A__				)				)


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


'''simple docstring'''
import math






def      UpperCamelCase_				(      A__ = 1_00						):
	a_      				=						sum(i * i for i in range(1  ,      n + 1						)						)
	a_      				=						int(math.pow(sum(range(1  ,      n + 1						)						)  ,      2						)						)
	return square_of_sum - sum_of_squares


if __name__ == "__main__":
		print(F"""{solution() = }""")
