code: def 				__lowercase	(						lowerCamelCase__ ,				lowerCamelCase__ = 13					)				->Dict:
  
    '''simple docstring'''
  
  
  
  
    a__     		=     ""
    for c in s:
      if "A" <= c <= "Z":
        out += chr(ord("A"					) + (ord(lowercase__					) - ord("A"					) + n) % 26					)
      elif "a" <= c <= "z":
        out += chr(ord("a"					) + (ord(lowercase__					) - ord("a"					) + n) % 26					)
      else:
        out += c
    return out
  def 				__lowercase	(						)				->Tuple:
  
    '''simple docstring'''
  
  
  
  
    a__     		=     input("Enter message: "					)
  
    a__     		=     dencrypt(lowercase__ ,				13					)
    print("Encryption:" ,				lowercase__					)
  
    a__     		=     dencrypt(lowercase__ ,				13					)
    print("Decryption: " ,				lowercase__					)
  
  
  if __name__ == "__main__":
       import doctest
  
       doctest.testmod()
       main()
  
  
style_context: from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_sentencepiece_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  _SCREAMING_SNAKE_CASE   						=    {
      """configuration_open_llama""": ["""OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OpenLlamaConfig"""],
  }
  
  try:
       if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    ["""LlamaTokenizer"""]
  
  try:
       if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    ["""LlamaTokenizerFast"""]
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       _SCREAMING_SNAKE_CASE   						=    [
           """OpenLlamaForCausalLM""",
           """OpenLlamaModel""",
           """OpenLlamaPreTrainedModel""",
           """OpenLlamaForSequenceClassification""",
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_open_llama import OPEN_LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, OpenLlamaConfig
  
       try:
            if not is_sentencepiece_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from transformers import LlamaTokenizer
  
       try:
            if not is_tokenizers_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from transformers import LlamaTokenizerFast
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_open_llama import (
                OpenLlamaForCausalLM,
                OpenLlamaForSequenceClassification,
                OpenLlamaModel,
                OpenLlamaPreTrainedModel,
            )
  
  
  else:
       import sys
  
       _SCREAMING_SNAKE_CASE   						=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  