
"""simple docstring"""


def      lowerCAmelCase_     (	snake_case_	:    List[str]							,					snake_case_	:    Tuple    )     ->int:
			return (input_a, input_a).count(0    ) % 2


def      lowerCAmelCase_     (	)     ->None:
			assert xor_gate(0							,					0    ) == 0
			assert xor_gate(0							,					1    ) == 1
			assert xor_gate(1							,					0    ) == 1
			assert xor_gate(1							,					1    ) == 0


if __name__ == "__main__":
							print(xor_gate(0, 0))
							print(xor_gate(0, 1))

"""simple docstring"""


from sklearn.neural_network import MLPClassifier

lowerCAmelCase			=		[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowerCAmelCase			=		[0, 1, 0, 0]


lowerCAmelCase			=		MLPClassifier(
    solver="""lbfgs""", alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


lowerCAmelCase			=		[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
lowerCAmelCase			=		clf.predict(test)






def      lowerCAmelCase_     (	snake_case_	:    Tuple    )     ->List[Any]:
			return list(snake_case_    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()