
"""simple docstring"""

def 							A						(    )				->     int:
 return [
     a * b * (1_0_0_0 - a - b)
     for a in range(1    , 9_9_9		)
     for b in range(snake_case    , 9_9_9		)
     if (a * a + b * b == (1_0_0_0 - a - b) ** 2)
 ][0]


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)



