


from typing import Union

import fire
import torch
from tqdm import tqdm







def  SCREAMING_SNAKE_CASE_		(    __A				:    Union[str, Any]						,					__A				:    Union[str, Any] = "cpu"						,					__A				:    List[str] = None       )			->	Optional[int]:

       """simple docstring"""

       a_      :	Any							=						torch.load(__A						,					map_location=__A       )
       for k, v in tqdm(state_dict.items()       ):
              if not isinstance(__A						,					torch.Tensor       ):
                     raise TypeError('FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin'       )
              a_      :	Optional[int]							=						v.half()
       if save_path is None:  # overwrite src_path
              a_      :	int							=						src_path
       torch.save(__A						,					__A       )


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





def  SCREAMING_SNAKE_CASE_		(    __A				:    int       )			->	bool:

       """simple docstring"""

       a_      :	List[Any]							=						n ** (1 / 3)
       return (val * val * val) == n


if __name__ == "__main__":
   print(perfect_cube(27))
   print(perfect_cube(4))


