
"""simple docstring"""


from unittest.mock import patch

import datasets
from datasets import Dataset


def      lowerCAmelCase_     (	)     ->List[Any]:
			lowerCamelCase__			:  Any  =Dataset.from_dict({'col_1': [3, 2, 0, 1]}    )

			with patch('tqdm.auto.tqdm'    ) as mock_tqdm:
						datasets.disable_progress_bar()
						dset.map(lambda snake_case_    : {"col_2": x["col_1"] + 1}    )
						mock_tqdm.assert_not_called()

						mock_tqdm.reset_mock()

						datasets.enable_progress_bar()
						dset.map(lambda snake_case_    : {"col_2": x["col_1"] + 1}    )
						mock_tqdm.assert_called()

"""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()