


"""simple docstring"""

def 							A						(    snake_case				:Tuple = 6_0_0_8_5_1_4_7_5_1_4_3		)				->     Optional[int]:

 try:
  __UpperCamelCase      =	int(snake_case		)
 except (TypeError, ValueError):
  raise TypeError('Parameter n must be int or castable to int.'		)
 if n <= 0:
  raise ValueError('Parameter n must be greater than or equal to one.'		)
 __UpperCamelCase      =	1
 __UpperCamelCase      =	2
 while i * i <= n:
  while n % i == 0:
   __UpperCamelCase      =	i
   n //= i
  i += 1
 if n > 1:
  __UpperCamelCase      =	n
 return int(snake_case		)


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





"""simple docstring"""

from typing import Union

import fire
import torch
from tqdm import tqdm






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


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



