





def 	lowerCAmelCase_					(			__a = 100						)	->						int:







  """simple docstring"""





  lowerCamelCase__: List[Any]         =(n * (n + 1) // 2) ** 2
  lowerCamelCase__: Dict         =n * (n + 1) * (2 * n + 1) // 6
  return sum_cubes - sum_squares


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









"""simple docstring"""





from typing import Union

import fire
import torch
from tqdm import tqdm



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


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



