






"""simple docstring"""
def        lowerCamelCase_  (						_lowerCamelCase			,   _lowerCamelCase = 13				):
 lowerCamelCase__     :			List[str]     				=						''
 for c in s:
  if "A" <= c <= "Z":
   out += chr(ord('A'				) + (ord(_lowerCamelCase				) - ord('A'				) + n) % 26				)
  elif "a" <= c <= "z":
   out += chr(ord('a'				) + (ord(_lowerCamelCase				) - ord('a'				) + n) % 26				)
  else:
   out += c
 return out






def        lowerCamelCase_  (						):
 lowerCamelCase__     :			List[Any]     				=						input('Enter message: '				)

 lowerCamelCase__     :			Dict     				=						dencrypt(_lowerCamelCase			,   13				)
 print('Encryption:'			,   _lowerCamelCase				)

 lowerCamelCase__     :			Optional[int]     				=						dencrypt(_lowerCamelCase			,   13				)
 print('Decryption: '			,   _lowerCamelCase				)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      main()









"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A_			: Dict				=			{"configuration_qdqbert": ["QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "QDQBertConfig"]}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A_			: Tuple				=			[
          "QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "QDQBertForMaskedLM",
          "QDQBertForMultipleChoice",
          "QDQBertForNextSentencePrediction",
          "QDQBertForQuestionAnswering",
          "QDQBertForSequenceClassification",
          "QDQBertForTokenClassification",
          "QDQBertLayer",
          "QDQBertLMHeadModel",
          "QDQBertModel",
          "QDQBertPreTrainedModel",
          "load_tf_weights_in_qdqbert",
      ]


if TYPE_CHECKING:
      from .configuration_qdqbert import QDQBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, QDQBertConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_qdqbert import (
                QDQBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                QDQBertForMaskedLM,
                QDQBertForMultipleChoice,
                QDQBertForNextSentencePrediction,
                QDQBertForQuestionAnswering,
                QDQBertForSequenceClassification,
                QDQBertForTokenClassification,
                QDQBertLayer,
                QDQBertLMHeadModel,
                QDQBertModel,
                QDQBertPreTrainedModel,
                load_tf_weights_in_qdqbert,
            )


else:
      import sys

      A_			: Tuple				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

