




'''simple docstring'''



def 			_UpperCamelCase (_lowerCamelCase							:     str   ,	_lowerCamelCase							:     str	)->   int:




     '''simple docstring'''





     if len(_lowerCamelCase	) < len(_lowerCamelCase	):
          return levenshtein_distance(_lowerCamelCase   ,	_lowerCamelCase	)

     if len(_lowerCamelCase	) == 0:
          return len(_lowerCamelCase	)

     __snake_case    					=  list(range(len(_lowerCamelCase	) + 1	)	)

     for i, ca in enumerate(_lowerCamelCase	):
          __snake_case    					=  [i + 1]

          for j, ca in enumerate(_lowerCamelCase	):
               # Calculate insertions, deletions and substitutions
               __snake_case    					=  previous_row[j + 1] + 1
               __snake_case    					=  current_row[j] + 1
               __snake_case    					=  previous_row[j] + (ca != ca)

               # Get the minimum to append to the current row
               current_row.append(min(_lowerCamelCase   ,	_lowerCamelCase   ,	_lowerCamelCase	)	)

          # Store the previous row
          __snake_case    					=  current_row

     # Returns the last element (distance)
     return previous_row[-1]


if __name__ == "__main__":
     UpperCAmelCase_       :  List[Any]      =		input('''Enter the first word:\n''').strip()
     UpperCAmelCase_       :  List[str]      =		input('''Enter the second word:\n''').strip()

     UpperCAmelCase_       :  Tuple      =		levenshtein_distance(first_word, second_word)
     print(F"""Levenshtein distance between {first_word} and {second_word} is {result}""")












'''simple docstring'''



import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


UpperCAmelCase_       :  int      =		logging.get_logger(__name__)





class     lowerCAmelCase   ( __lowerCAmelCase):


       def __init__(   self    ,  *__SCREAMING_SNAKE_CASE    ,  **__SCREAMING_SNAKE_CASE  )      ->  None:



            '''simple docstring'''




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






