





import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


lowerCAmelCase_   =   logging.get_logger(__name__)

class      A    (lowerCamelCase__				):



      def __init__(					self     ,  *lowercase_     ,  **lowercase_					)      ->   List[Any]:



             '''simple docstring'''

             warnings.warn(
                 '''The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
                 ''' use ViTImageProcessor instead.'''     ,  SCREAMING_SNAKE_CASE_     ,  )
             super().__init__(*SCREAMING_SNAKE_CASE_     ,  **SCREAMING_SNAKE_CASE_					)













import numpy as np




def 						A_			(  lowercase_  )			->						Optional[Any]:
       _snake_case      :							Union[str, Any]     				=						np.exp(lowercase_  )

       # Add up the all the exponentials
       _snake_case      :							List[str]     				=						np.sum(lowercase_  )

       # Divide every exponent by the sum of all exponents
       _snake_case      :							Optional[int]     				=						exponent_vector / sum_of_exponents

       return softmax_vector


if __name__ == "__main__":
   print(softmax((0,)))






