



from string import ascii_uppercase





def 						a__     (						_UpperCamelCase     :	str	,_UpperCamelCase     :	str	,_UpperCamelCase     :	bool = False	,_UpperCamelCase     :	str = ascii_uppercase							):
   __lowerCamelCase  							=      keyword.upper()
   __lowerCamelCase  							=      plaintext.upper()
   __lowerCamelCase  							=      set(_UpperCamelCase							)

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

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

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

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

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

   if verbose:
      print(_UpperCamelCase							)
   # 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"""))











from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


a_								=   logging.get_logger(__name__)

a_								=   {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

a_								=   {
    """vocab_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/vocab.json"""},
    """merges_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/merges.txt"""},
    """tokenizer_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/tokenizer.json"""},
}

a_								=   {
    """openai-gpt""": 512,
}



class 	__lowerCAmelCase       (		lowerCAmelCase__				):
 lowerCAmelCase__       =					VOCAB_FILES_NAMES
 lowerCAmelCase__       =					PRETRAINED_VOCAB_FILES_MAP
 lowerCAmelCase__       =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCAmelCase__       =					["""input_ids""", """attention_mask"""]
 lowerCAmelCase__       =					OpenAIGPTTokenizer




 def __init__(  self		,			__UpperCAmelCase=None		,			__UpperCAmelCase=None		,			__UpperCAmelCase=None		,			__UpperCAmelCase="<unk>"		,			**__UpperCAmelCase			):



    '''simple docstring'''
    super().__init__(__UpperCAmelCase		,			__UpperCAmelCase		,			tokenizer_file=__UpperCAmelCase		,			unk_token=__UpperCAmelCase		,			**__UpperCAmelCase			)




 @property
 def     lowerCamelCase (  self			):



    '''simple docstring'''
    return True




 def     lowerCamelCase (  self		,			__UpperCAmelCase		,			__UpperCAmelCase = None			):



    '''simple docstring'''
    __lowerCamelCase  							=      self._tokenizer.model.save(__UpperCAmelCase		,			name=__UpperCAmelCase			)
    return tuple(__UpperCAmelCase			)






