





from typing import Union

import fire
import torch
from tqdm import tqdm


def 					A__	(       SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_ = "cpu"							,       SCREAMING_SNAKE_CASE_ = None		):
		lowerCamelCase   : Dict								=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'''		)
				lowerCamelCase   : Union[str, Any]								=v.half()
		if save_path is None:  # overwrite src_path
				lowerCamelCase   : Union[str, Any]								=src_path
		torch.save(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_		)


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








from __future__ import annotations


def 					A__	(       SCREAMING_SNAKE_CASE_		)   ->     bool:
		if len(SCREAMING_SNAKE_CASE_		) < 2:
				raise ValueError('''Monogons and Digons are not polygons in the Euclidean space'''		)
		if any(i <= 0 for i in nums		):
				raise ValueError('''All values must be greater than 0'''		)
		lowerCamelCase   : List[Any]								=nums.copy()
		copy_nums.sort()
		return copy_nums[-1] < sum(copy_nums[:-1]		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()

