



'''simple docstring'''




from math import factorial


def        lowerCAmelCase_     (			_lowerCamelCase:     int ,   _lowerCamelCase:     int ,   _lowerCamelCase:     float      ):
		if successes > trials:
				raise ValueError("""successes must be lower or equal to trials"""      )
		if trials < 0 or successes < 0:
				raise ValueError("""the function is defined for non-negative integers"""      )
		if not isinstance(_A ,   _A      ) or not isinstance(_A ,   _A      ):
				raise ValueError("""the function is defined for non-negative integers"""      )
		if not 0 < prob < 1:
				raise ValueError("""prob has to be in range of 1 - 0"""      )
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	(prob**successes) * ((1 - prob) ** (trials - successes))
		# Calculate the binomial coefficient: n! / k!(n-k)!
		__SCREAMING_SNAKE_CASE :	Tuple					 =	float(factorial(_A      )      )
		coefficient /= factorial(_A      ) * factorial(trials - successes      )
		return probability * coefficient


if __name__ == "__main__":
						from doctest import testmod

						testmod()
						print('''Probability of 2 successes out of 4 trails''')
						print('''with probability of 0.75 is:''', end=''' ''')
						print(binomial_distribution(2, 4, 0.7_5))








'''simple docstring'''




import warnings

from ...utils import logging
from .image_processing_deit import DeiTImageProcessor


UpperCamelCase__ :			List[str]												=				logging.get_logger(__name__)






class 		_UpperCamelCase						(							lowerCamelCase__					):


			'''simple docstring'''

			def __init__(							self  :				Union[str, Any]							,  *lowerCAmelCase__  :				str							,  **lowerCAmelCase__  :				Any		):





					"""simple docstring"""






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