





from typing import Union

import fire
import torch
from tqdm import tqdm

def    __snake_case  (    _lowerCAmelCase       :       List[str] , _lowerCAmelCase       :       str = "cpu" , _lowerCAmelCase       :       Tuple = None		)       ->  List[Any]:
   A_    : str								=	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"		)
      A_    : int								=	v.half()
   if save_path is None:  # overwrite src_path
      A_    : str								=	src_path
   torch.save(lowerCamelCase_ , lowerCamelCase_		)


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








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A__	:			Optional[int]			   = {}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A__	:			Optional[int]			   = ['GPTSw3Tokenizer']


if TYPE_CHECKING:
							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_gpt_swa import GPTSwaTokenizer

else:
							import sys

							A__	:			Optional[int]			   = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




