

"""simple docstring"""




def   __SCREAMING_SNAKE_CASE		(		lowercase__ ):
					"""simple docstring"""
					if not isinstance(lowercase__     ,				lowercase__ ):
										raise ValueError("Input series is not valid, valid series - [2, 4, 8]" )
					if len(lowercase__ ) == 0:
										raise ValueError("Input list must be a non empty list" )
					if len(lowercase__ ) == 1:
										return True
					try:
										A     =   series[1] / series[0]
										for index in range(len(lowercase__ ) - 1 ):
															if series[index + 1] / series[index] != common_ratio:
																				return False
					except ZeroDivisionError:
										return False
					return True
def   __SCREAMING_SNAKE_CASE		(		lowercase__ ):
					"""simple docstring"""
					if not isinstance(lowercase__     ,				lowercase__ ):
										raise ValueError("Input series is not valid, valid series - [2, 4, 8]" )
					if len(lowercase__ ) == 0:
										raise ValueError("Input list must be a non empty list" )
					A     =   1
					for value in series:
										answer *= value
					return pow(lowercase__     ,				1 / len(lowercase__ ) )


if __name__ == "__main__":
	import doctest

	doctest.testmod()






"""simple docstring"""






from sklearn.neural_network import MLPClassifier

lowerCAmelCase__    :    Any			=      [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowerCAmelCase__    :    Optional[int]			=      [0, 1, 0, 0]


lowerCAmelCase__    :    Dict			=      MLPClassifier(
    solver='lbfgs', alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


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



def     a_		(   lowerCamelCase			):
				return list(lowerCamelCase			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()



