

def 					lowerCAmelCase__							(	)			->      Optional[Any]:




				'''simple docstring'''





				A__        =			[]
				A__        =			1

				while len(SCREAMING_SNAKE_CASE_      ) < 1e6:
								constant.append(str(SCREAMING_SNAKE_CASE_      )      )
								i += 1

				A__        =			"".join(SCREAMING_SNAKE_CASE_      )

				return (
				    int(constant[0]      )
				    * int(constant[9]      )
				    * int(constant[9_9]      )
				    * int(constant[9_9_9]      )
				    * int(constant[9_9_9_9]      )
				    * int(constant[9_9_9_9_9]      )
				    * int(constant[9_9_9_9_9_9]      )
				)


if __name__ == "__main__":
	print(solution())




from typing import Union

import fire
import torch
from tqdm import tqdm



def 					lowerCAmelCase__							(	SCREAMING_SNAKE_CASE_:							str	,       SCREAMING_SNAKE_CASE_:							str = "cpu"	,       SCREAMING_SNAKE_CASE_:							Union[str, None] = None      )			->      None:




				'''simple docstring'''





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


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

