
"""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    ):
			return list(snake_case_    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()

"""simple docstring"""


import unittest
import warnings

from datasets.utils import experimental






@experimental
def      lowerCAmelCase_     (	)     ->Optional[Any]:
			return "success"

class 					A_			(  unittest.TestCase     ):



							"""simple docstring"""






							def    UpperCAmelCase__							(						self						:int ):





										"""simple docstring"""

										with warnings.catch_warnings(record=lowerCamelCase_ ) as w:
													warnings.simplefilter('always' )
													self.assertEqual(dummy_function()  ,							'success' )
										self.assertEqual(len(lowerCamelCase_ )  ,							1 )