




from __future__ import annotations

def  UpperCAmelCase_							(				__UpperCAmelCase						:     float      ,      __UpperCAmelCase						:     float      ,      __UpperCAmelCase						:     float							) ->			dict[str, float]:
      if (voltage, current, resistance).count(0							) != 1:
            raise ValueError('One and only one argument must be 0'							)
      if resistance < 0:
            raise ValueError('Resistance cannot be negative'							)
      if voltage == 0:
            return {"voltage": float(current * resistance							)}
      elif current == 0:
            return {"current": voltage / resistance}
      elif resistance == 0:
            return {"resistance": voltage / current}
      else:
            raise ValueError('Exactly one argument must be 0'							)


if __name__ == "__main__":
   import doctest

   doctest.testmod()





import warnings

from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor


lowerCamelCase__			:       Dict         =							logging.get_logger(__name__)





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 def __init__(							self  :		List[Any]    ,    *_lowerCAmelCase  :		List[str]    ,    **_lowerCAmelCase  :		Optional[int]						):
       warnings.warn(
           'The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
           ' Please use LayoutLMv2ImageProcessor instead.'    ,    _lowerCAmelCase    ,    )
       super().__init__(*_lowerCAmelCase    ,    **_lowerCAmelCase						)