






def     lowerCamelCase__				(   __lowerCamelCase      :					str  ,		__lowerCamelCase      :					int = 13		):
  __UpperCAmelCase							:     Optional[Any]									=  """"""
  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__				(   ):
  __UpperCAmelCase							:     int									=  input("""Enter message: """		)

  __UpperCAmelCase							:     Any									=  dencrypt(__lowerCamelCase  ,		13		)
  print("""Encryption:"""  ,		__lowerCamelCase		)

  __UpperCAmelCase							:     List[Any]									=  dencrypt(__lowerCamelCase  ,		13		)
  print("""Decryption: """  ,		__lowerCamelCase		)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       main()










from sklearn.neural_network import MLPClassifier

a		:	int      					=			[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
a		:	List[str]      					=			[0, 1, 0, 0]


a		:	str      					=			MLPClassifier(
    solver="lbfgs", alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


a		:	Union[str, Any]      					=			[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
a		:	Optional[int]      					=			clf.predict(test)






def     lowerCamelCase__				(   __lowerCamelCase      :					Dict		):
  return list(__lowerCamelCase		)


if __name__ == "__main__":
       import doctest

       doctest.testmod()


