



def 						UpperCAmelCase__   (   UpperCAmelCase__			:str			,       UpperCAmelCase__			:str       ):






 '''simple docstring'''

 if not isinstance(UpperCAmelCase__			,       UpperCAmelCase__       ):
  raise TypeError("plaintext must be a string"       )
 if not isinstance(UpperCAmelCase__			,       UpperCAmelCase__       ):
  raise TypeError("key must be a string"       )

 if not plaintext:
  raise ValueError("plaintext is empty"       )
 if not key:
  raise ValueError("key is empty"       )

 key += plaintext
 a							=		plaintext.lower()
 a							=		key.lower()
 a							=		0
 a							=		0
 a							=		""
 while plaintext_iterator < len(UpperCAmelCase__       ):
  if (
      ord(plaintext[plaintext_iterator]       ) < 97
      or ord(plaintext[plaintext_iterator]       ) > 1_22
  ):
   ciphertext += plaintext[plaintext_iterator]
   plaintext_iterator += 1
  elif ord(key[key_iterator]       ) < 97 or ord(key[key_iterator]       ) > 1_22:
   key_iterator += 1
  else:
   ciphertext += chr(
       (
           (ord(plaintext[plaintext_iterator]       ) - 97 + ord(key[key_iterator]       ))
           - 97
       )
       % 26
       + 97       )
   key_iterator += 1
   plaintext_iterator += 1
 return ciphertext


def 						UpperCAmelCase__   (   UpperCAmelCase__			:str			,       UpperCAmelCase__			:str       ):






 '''simple docstring'''

 if not isinstance(UpperCAmelCase__			,       UpperCAmelCase__       ):
  raise TypeError("ciphertext must be a string"       )
 if not isinstance(UpperCAmelCase__			,       UpperCAmelCase__       ):
  raise TypeError("key must be a string"       )

 if not ciphertext:
  raise ValueError("ciphertext is empty"       )
 if not key:
  raise ValueError("key is empty"       )

 a							=		key.lower()
 a							=		0
 a							=		0
 a							=		""
 while ciphertext_iterator < len(UpperCAmelCase__       ):
  if (
      ord(ciphertext[ciphertext_iterator]       ) < 97
      or ord(ciphertext[ciphertext_iterator]       ) > 1_22
  ):
   plaintext += ciphertext[ciphertext_iterator]
  else:
   plaintext += chr(
       (ord(ciphertext[ciphertext_iterator]       ) - ord(key[key_iterator]       )) % 26
       + 97       )
   key += chr(
       (ord(ciphertext[ciphertext_iterator]       ) - ord(key[key_iterator]       )) % 26
       + 97       )
   key_iterator += 1
  ciphertext_iterator += 1
 return plaintext


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     A_		:  Union[str, Any]										=  int(input('''Type 1 to encrypt or 2 to decrypt:'''))
     if operation == 1:
          A_		:  int										=  input('''Typeplaintext to be encrypted:\n''')
          A_		:  Dict										=  input('''Type the key:\n''')
          print(encrypt(plaintext, key))
     elif operation == 2:
          A_		:  Tuple										=  input('''Type the ciphertext to be decrypted:\n''')
          A_		:  Dict										=  input('''Type the key:\n''')
          print(decrypt(ciphertext, key))
     decrypt('''jsqqs avvwo''', '''coffee''')





"""simple docstring"""






from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
   from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


__snake_case												=							logging.get_logger(__name__)

__snake_case												=							{
    '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/config.json''',
    '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/config.json''',
    '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json''',
    '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json''',
    '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json''',
    '''microsoft/deberta-xlarge-mnli''': '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json''',
}


class      __lowerCamelCase	(       a__					):

     '''simple docstring'''
     A_							:						List[Any]     =		'deberta'


     def __init__(   self     ,					__UpperCAmelCase=50265     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=3072     ,					__UpperCAmelCase="gelu"     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase=0.02     ,					__UpperCAmelCase=1e-7     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=-1     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=None     ,					__UpperCAmelCase=0     ,					__UpperCAmelCase="gelu"     ,					**__UpperCAmelCase     ,					)							->				Any:
          super().__init__(**__UpperCAmelCase				)

          _a     						=					hidden_size
          _a     						=					num_hidden_layers
          _a     						=					num_attention_heads
          _a     						=					intermediate_size
          _a     						=					hidden_act
          _a     						=					hidden_dropout_prob
          _a     						=					attention_probs_dropout_prob
          _a     						=					max_position_embeddings
          _a     						=					type_vocab_size
          _a     						=					initializer_range
          _a     						=					relative_attention
          _a     						=					max_relative_positions
          _a     						=					pad_token_id
          _a     						=					position_biased_input

          # Backwards compatibility
          if type(__UpperCAmelCase				) == str:
               _a     						=					[x.strip() for x in pos_att_type.lower().split('''|'''				)]

          _a     						=					pos_att_type
          _a     						=					vocab_size
          _a     						=					layer_norm_eps

          _a     						=					kwargs.get('''pooler_hidden_size'''     ,					__UpperCAmelCase				)
          _a     						=					pooler_dropout
          _a     						=					pooler_hidden_act







class      __lowerCamelCase	(       a__					):

     '''simple docstring'''


     @property
     def 				_UpperCAmelCase   (   self				)							->				Mapping[str, Mapping[int, str]]:
          if self.task == "multiple-choice":
               _a     						=					{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
          else:
               _a     						=					{0: '''batch''', 1: '''sequence'''}
          if self._config.type_vocab_size > 0:
               return OrderedDict(
                   [('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis), ('''token_type_ids''', dynamic_axis)]				)
          else:
               return OrderedDict([('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis)]				)


     @property
     def 				_UpperCAmelCase   (   self				)							->				int:
          return 12





     def 				_UpperCAmelCase   (   self     ,					__UpperCAmelCase     ,					__UpperCAmelCase = -1     ,					__UpperCAmelCase = -1     ,					__UpperCAmelCase = -1     ,					__UpperCAmelCase = False     ,					__UpperCAmelCase = None     ,					__UpperCAmelCase = 3     ,					__UpperCAmelCase = 40     ,					__UpperCAmelCase = 40     ,					__UpperCAmelCase = None     ,					)							->				Mapping[str, Any]:
          _a     						=					super().generate_dummy_inputs(preprocessor=__UpperCAmelCase     ,					framework=__UpperCAmelCase				)
          if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
               del dummy_inputs["token_type_ids"]
          return dummy_inputs