
from typing import Union

import fire
import torch
from tqdm import tqdm






def 	a_		(	__lowercase       :     str	, __lowercase       :     str = "cpu"	, __lowercase       :     Union[str, None] = None			)			->  None:
			_snake_case          =      torch.load(__lowercase	, map_location=__lowercase			)
			for k, v in tqdm(state_dict.items()			):
						if not isinstance(__lowercase	, torch.Tensor			):
									raise TypeError('FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin'			)
						_snake_case          =      v.half()
			if save_path is None:  # overwrite src_path
						_snake_case          =      src_path
			torch.save(__lowercase	, __lowercase			)


if __name__ == "__main__":
					fire.Fire(convert)

import random




class        SCREAMING_SNAKE_CASE__					:





	'''simple docstring'''



	@staticmethod
	def 			A							(  lowercase     :   str     ):


				'''simple docstring'''


				_snake_case          =      [ord(lowercase     ) for i in text]
				_snake_case          =      []
				_snake_case          =      []
				for i in plain:
							_snake_case          =      random.randint(1      ,  300     )
							_snake_case          =      (i + k) * k
							cipher.append(lowercase     )
							key.append(lowercase     )
				return cipher, key





	@staticmethod
	def 			A							(  lowercase     :   list[int]      ,  lowercase     :   list[int]     ):


				'''simple docstring'''


				_snake_case          =      []
				for i in range(len(lowercase     )     ):
							_snake_case          =      int((cipher[i] - (key[i]) ** 2) / key[i]     )
							plain.append(chr(lowercase     )     )
				return "".join(lowercase     )


if __name__ == "__main__":
			_lowerCamelCase   ,					_lowerCamelCase	:    Optional[int]          =      Onepad().encrypt('''Hello''')
			print(c, k)
			print(Onepad().decrypt(c, k))