

import warnings

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


a_      =     logging.get_logger(__name__)






class _UpperCamelCase				(				__A ):
			'''simple docstring'''







			def __init__(      self				:			List[str]   ,   *a				:			Optional[int]   ,   **a				:			Dict						)				->							None:

				"""simple docstring"""

				warnings.warn(
				    "The class LayoutLMv2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
				    " Please use LayoutLMv2ImageProcessor instead."   ,   a   ,   )
				super().__init__(*a   ,   **a						)



from math import log

from scipy.constants import Boltzmann, physical_constants

A			:						Any        =  3_0_0  # TEMPERATURE (unit = K)






def 					UpperCamelCase   (      __magic_name__	:				float       ,       __magic_name__	:				float       ,       __magic_name__	:				float       ,       )  ->    float:
		"""simple docstring"""




		if donor_conc <= 0:
				raise ValueError("""Donor concentration should be positive"""	)
		elif acceptor_conc <= 0:
				raise ValueError("""Acceptor concentration should be positive"""	)
		elif intrinsic_conc <= 0:
				raise ValueError("""Intrinsic concentration should be positive"""	)
		elif donor_conc <= intrinsic_conc:
				raise ValueError(
				    """Donor concentration should be greater than intrinsic concentration"""	)
		elif acceptor_conc <= intrinsic_conc:
				raise ValueError(
				    """Acceptor concentration should be greater than intrinsic concentration"""	)
		else:
				return (
				    Boltzmann
				    * T
				    * log((donor_conc * acceptor_conc) / intrinsic_conc**2	)
				    / physical_constants["electron volt"][0]
				)


if __name__ == "__main__":
	import doctest

	doctest.testmod()

