
"""simple docstring"""






def 		_snake_case			(      lowercase__						:    list						)    ->							list:


			'''simple docstring'''





			if len(lowercase__						) <= 1:
						return data
			else:
						return [
						    *quick_sort([e for e in data[1:] if e <= data[0]]						),
						    data[0],
						    *quick_sort([e for e in data[1:] if e > data[0]]						),
						]


if __name__ == "__main__":
				import doctest

				doctest.testmod()








"""simple docstring"""

from sklearn.neural_network import MLPClassifier

UpperCamelCase      :							Any          =					[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
UpperCamelCase      :							Any          =					[0, 1, 0, 0]


UpperCamelCase      :							Optional[Any]          =					MLPClassifier(
    solver="lbfgs", alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


UpperCamelCase      :							List[Any]          =					[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
UpperCamelCase      :							Optional[Any]          =					clf.predict(test)






def 				A		(							snake_case :int						) ->      int:
 return list(snake_case						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()



