"""simple docstring"""







from typing import Union

import fire
import torch
from tqdm import tqdm



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


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








'''simple docstring'''

import functools





def 						UpperCamelCase				(							_lowerCamelCase					:					str						,       _lowerCamelCase					:					str       ):
    A__				=			len(_lowerCamelCase       )
    A__				=			len(_lowerCamelCase       )

    @functools.cache
    def min_distance(_lowerCamelCase					:					int						,       _lowerCamelCase					:					int       ) -> int:
        # if first word index is overflow - delete all from the second word
        if indexa >= len_worda:
            return len_worda - indexa
        # if second word index is overflow - delete all from the first word
        if indexa >= len_worda:
            return len_worda - indexa
        A__				=			int(worda[indexa] != worda[indexa]       )  # current letters not identical
        return min(
            1 + min_distance(indexa + 1						,       _lowerCamelCase       )						,       1 + min_distance(_lowerCamelCase						,       indexa + 1       )						,       diff + min_distance(indexa + 1						,       indexa + 1       )						,       )

    return min_distance(0						,       0       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()



