
def     a__			(    snake_case   ,	snake_case = 13    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					str			=						''''''
  for c in s:
    if "A" <= c <= "Z":
      out += chr(ord('''A'''    ) + (ord(__A    ) - ord('''A'''    ) + n) % 26    )
    elif "a" <= c <= "z":
      out += chr(ord('''a'''    ) + (ord(__A    ) - ord('''a'''    ) + n) % 26    )
    else:
      out += c
  return out


def     a__			(    ):





  """simple docstring"""
  __SCREAMING_SNAKE_CASE     :					Optional[Any]			=						input('''Enter message: '''    )

  __SCREAMING_SNAKE_CASE     :					List[Any]			=						dencrypt(__A   ,	13    )
  print('''Encryption:'''   ,	__A    )

  __SCREAMING_SNAKE_CASE     :					List[Any]			=						dencrypt(__A   ,	13    )
  print('''Decryption: '''   ,	__A    )


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   main()


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase_											=	{
    """configuration_led""": ["""LED_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LEDConfig"""],
    """tokenization_led""": ["""LEDTokenizer"""],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	["""LEDTokenizerFast"""]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	[
       """LED_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """LEDForConditionalGeneration""",
       """LEDForQuestionAnswering""",
       """LEDForSequenceClassification""",
       """LEDModel""",
       """LEDPreTrainedModel""",
   ]


try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowercase_											=	["""TFLEDForConditionalGeneration""", """TFLEDModel""", """TFLEDPreTrainedModel"""]


if TYPE_CHECKING:
   from .configuration_led import LED_PRETRAINED_CONFIG_ARCHIVE_MAP, LEDConfig
   from .tokenization_led import LEDTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_led_fast import LEDTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_led import (
          LED_PRETRAINED_MODEL_ARCHIVE_LIST,
          LEDForConditionalGeneration,
          LEDForQuestionAnswering,
          LEDForSequenceClassification,
          LEDModel,
          LEDPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_led import TFLEDForConditionalGeneration, TFLEDModel, TFLEDPreTrainedModel

else:
   import sys

   lowercase_											=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
