




from string import ascii_uppercase




def        __SCREAMING_SNAKE_CASE (	lowercase_       ,  lowercase_       ,  lowercase_ = False       ,  lowercase_ = ascii_uppercase   )							->						str:

    """simple docstring"""


    __UpperCamelCase			=    keyword.upper()
    __UpperCamelCase			=    plaintext.upper()
    __UpperCamelCase			=    set(lowercase_   )

    # create a list of unique characters in the keyword - their order matters
    # it determines how we will map plaintext characters to the ciphertext
    __UpperCamelCase			=    []
    for char in keyword:
        if char in alphabet_set and char not in unique_chars:
            unique_chars.append(lowercase_   )
    # the number of those unique characters will determine the number of rows
    __UpperCamelCase			=    len(lowercase_   )

    # create a shifted version of the alphabet
    __UpperCamelCase			=    unique_chars + [
        char for char in alphabet if char not in unique_chars
    ]

    # create a modified alphabet by splitting the shifted alphabet into rows
    __UpperCamelCase			=    [
        shifted_alphabet[k : k + num_unique_chars_in_keyword]
        for k in range(0       ,  26       ,  lowercase_   )
    ]

    # map the alphabet characters to the modified alphabet characters
    # going 'vertically' through the modified alphabet - consider columns first
    __UpperCamelCase			=    {}
    __UpperCamelCase			=    0
    for column in range(lowercase_   ):
        for row in modified_alphabet:
            # if current row (the last one) is too short, break out of loop
            if len(lowercase_   ) <= column:
                break

            # map current letter to letter in modified alphabet
            __UpperCamelCase			=    row[column]
            letter_index += 1

    if verbose:
        print(lowercase_   )
    # create the encrypted text by mapping the plaintext to the modified alphabet
    return "".join(mapping[char] if char in mapping else char for char in plaintext   )


if __name__ == "__main__":
 # example use
 print(mixed_keyword("college", "UNIVERSITY"))













import warnings

from ...utils import logging
from .image_processing_detr import DetrImageProcessor


_UpperCamelCase       :				Tuple           =			logging.get_logger(__name__)







class 		_lowerCAmelCase(		_a):

  """simple docstring"""







  def __init__(   self    ,							*UpperCAmelCase    ,							**UpperCAmelCase      )->   None:
     warnings.warn(
         '''The class DetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
         ''' Please use DetrImageProcessor instead.'''    ,							UpperCAmelCase    ,							)
     super().__init__(*UpperCAmelCase    ,							**UpperCAmelCase      )

