





"""simple docstring"""






from __future__ import annotations

import random
import string



class 						lowerCAmelCase       :






       def __init__( self     ,	a__ = None  ):
              _UpperCAmelCase			     =  passcode or self.__passcode_creator()
              _UpperCAmelCase			     =  self.__make_key_list()
              _UpperCAmelCase			     =  self.__make_shift_key()






       def __str__( self  ):
              return "".join(self.__passcode  )






       def 				__A			( self     ,	a__  ):
              for i in range(1     ,	len(a__  )     ,	2  ):
                     iterlist[i] *= -1
              return iterlist






       def 				__A			( self  ):
              _UpperCAmelCase			     =  string.ascii_letters + string.digits
              _UpperCAmelCase			     =  [random.choice(a__  ) for _ in range(random.randint(10     ,	20  )  )]
              return password






       def 				__A			( self  ):
              _UpperCAmelCase			     =  (
                  string.ascii_letters + string.digits + string.punctuation + ' \t\n'
              )

              _UpperCAmelCase			     =  []

              # creates points known as breakpoints to break the key_list_options at those
              # points and pivot each substring
              _UpperCAmelCase			     =  sorted(set(self.__passcode  )  )
              _UpperCAmelCase			     =  []

              # algorithm for creating a new shuffled list, keys_l, out of key_list_options
              for i in key_list_options:
                     temp_list.extend(a__  )

                     # checking breakpoints at which to pivot temporary sublist and add it into
                     # keys_l
                     if i in breakpoints or i == key_list_options[-1]:
                            keys_l.extend(temp_list[::-1]  )
                            temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
              return keys_l






       def 				__A			( self  ):
              _UpperCAmelCase			     =  sum(self.__neg_pos([ord(a__  ) for x in self.__passcode]  )  )
              return num if num > 0 else len(self.__passcode  )






       def 				__A			( self     ,	a__  ):
              _UpperCAmelCase			     =  ''

              # decoding shift like Caesar cipher algorithm implementing negative shift or
              # reverse shift or left shift
              for i in encoded_message:
                     _UpperCAmelCase			     =  self.__key_list.index(a__  )
                     decoded_message += self.__key_list[
                         (position - self.__shift_key) % -len(self.__key_list  )
                     ]

              return decoded_message






       def 				__A			( self     ,	a__  ):
              _UpperCAmelCase			     =  ''

              # encoding shift like Caesar cipher algorithm implementing positive shift or
              # forward shift or right shift
              for i in plaintext:
                     _UpperCAmelCase			     =  self.__key_list.index(a__  )
                     encoded_message += self.__key_list[
                         (position + self.__shift_key) % len(self.__key_list  )
                     ]

              return encoded_message


def    __lowerCamelCase     (							SCREAMING_SNAKE_CASE = "Hello, this is a modified Caesar cipher"				)		->							str:






       """simple docstring"""




       _UpperCAmelCase			     =  ShuffledShiftCipher()
       return cipa.decrypt(cipa.encrypt(SCREAMING_SNAKE_CASE				)				)


if __name__ == "__main__":
    import doctest

    doctest.testmod()













"""simple docstring"""






from typing import Callable, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_      =				logging.get_logger(__name__)

lowerCAmelCase_      =				{
    '''microsoft/prophetnet-large-uncased''': (
        '''https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json'''
    ),
}



class 						lowerCAmelCase       (   snake_case				):
       lowerCAmelCase__    			=	"""prophetnet"""
       lowerCAmelCase__    			=	["""past_key_values"""]
       lowerCAmelCase__    			=	{
           """num_attention_heads""": """num_encoder_attention_heads""",
       }






       def __init__( self     ,	a__ = 0.1     ,	a__ = "gelu"     ,	a__ = 3_05_22     ,	a__ = 10_24     ,	a__ = 40_96     ,	a__ = 12     ,	a__ = 16     ,	a__ = 40_96     ,	a__ = 12     ,	a__ = 16     ,	a__ = 0.1     ,	a__ = 0.1     ,	a__ = 5_12     ,	a__ = 0.02     ,	a__ = True     ,	a__ = True     ,	a__ = 0     ,	a__ = 2     ,	a__ = 32     ,	a__ = 1_28     ,	a__ = False     ,	a__ = 0.0     ,	a__ = True     ,	a__ = 0     ,	a__ = 1     ,	a__ = 2     ,	**a__     ,	):
              _UpperCAmelCase			     =  vocab_size
              _UpperCAmelCase			     =  hidden_size
              _UpperCAmelCase			     =  encoder_ffn_dim
              _UpperCAmelCase			     =  num_encoder_layers
              _UpperCAmelCase			     =  num_encoder_attention_heads
              _UpperCAmelCase			     =  decoder_ffn_dim
              _UpperCAmelCase			     =  num_decoder_layers
              _UpperCAmelCase			     =  num_decoder_attention_heads
              _UpperCAmelCase			     =  max_position_embeddings
              _UpperCAmelCase			     =  init_std  # Normal(0, this parameter)
              _UpperCAmelCase			     =  activation_function

              # parameters for prophetnet
              _UpperCAmelCase			     =  ngram
              _UpperCAmelCase			     =  num_buckets
              _UpperCAmelCase			     =  relative_max_distance
              _UpperCAmelCase			     =  disable_ngram_loss
              _UpperCAmelCase			     =  eps

              # 3 Types of Dropout
              _UpperCAmelCase			     =  attention_dropout
              _UpperCAmelCase			     =  activation_dropout
              _UpperCAmelCase			     =  dropout

              _UpperCAmelCase			     =  use_cache

              super().__init__(
                  pad_token_id=a__     ,	bos_token_id=a__     ,	eos_token_id=a__     ,	is_encoder_decoder=a__     ,	add_cross_attention=a__     ,	decoder_start_token_id=a__     ,	**a__     ,	)






       @property
       def 				__A			( self  ):
              return self.num_encoder_layers + self.num_decoder_layers






       @num_hidden_layers.setter
       def 				__A			( self     ,	a__  ):
              raise NotImplementedError(
                  'This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and'
                  ' `num_decoder_layers`.'  )






