

import warnings

from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor


lowerCAmelCase__	   = logging.get_logger(__name__)

class 					a__						(					snake_case			):
			"""simple docstring"""







			def __init__(    self      ,      *lowercase      ,      **lowercase       )  ->						None:
							'''simple docstring'''






							warnings.warn(
							    "The class VideoMAEFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
							    " Please use VideoMAEImageProcessor instead."      ,      lowercase      ,      )
							super().__init__(*lowercase      ,      **lowercase       )




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)

