

def  _snake_case		(snake_case_					:     str    ,       snake_case_					:     int = 13  )							->		str:
  __UpperCAmelCase	:  Tuple		=     ''
  for c in s:
    if "A" <= c <= "Z":
      out += chr(ord('A'  ) + (ord(snake_case_  ) - ord('A'  ) + n) % 26  )
    elif "a" <= c <= "z":
      out += chr(ord('a'  ) + (ord(snake_case_  ) - ord('a'  ) + n) % 26  )
    else:
      out += c
  return out





def  _snake_case		()							->		None:
  __UpperCAmelCase	:  str		=     input('Enter message: '  )

  __UpperCAmelCase	:  List[str]		=     dencrypt(snake_case_    ,       13  )
  print('Encryption:'    ,       snake_case_  )

  __UpperCAmelCase	:  Tuple		=     dencrypt(snake_case_    ,       13  )
  print('Decryption: '    ,       snake_case_  )


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()










from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


UpperCAmelCase__			:   Optional[int]      			=    {
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__			:   List[Any]      			=    ['ErnieMTokenizer']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__			:   Dict      			=    [
					    'ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'ErnieMForMultipleChoice',
					    'ErnieMForQuestionAnswering',
					    'ErnieMForSequenceClassification',
					    'ErnieMForTokenClassification',
					    'ErnieMModel',
					    'ErnieMPreTrainedModel',
					    'ErnieMForInformationExtraction',
					]


if TYPE_CHECKING:
					from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_ernie_m import ErnieMTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_ernie_m import (
										    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ErnieMForInformationExtraction,
										    ErnieMForMultipleChoice,
										    ErnieMForQuestionAnswering,
										    ErnieMForSequenceClassification,
										    ErnieMForTokenClassification,
										    ErnieMModel,
										    ErnieMPreTrainedModel,
										)


else:
					import sys

					UpperCAmelCase__			:   Union[str, Any]      			=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
