"""simple docstring"""







from sklearn.neural_network import MLPClassifier

_a	:	str=					[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
_a	:	List[Any]=					[0, 1, 0, 0]


_a	:	int=					MLPClassifier(
    solver="lbfgs", alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


_a	:	int=					[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
_a	:	Optional[int]=					clf.predict(test)
def     __UpperCAmelCase							(       UpperCAmelCase_       :							Union[str, Any]    )				->     Optional[int]:

	'''simple docstring'''





	return list(UpperCAmelCase_    )


if __name__ == "__main__":
	import doctest

	doctest.testmod()






"""simple docstring"""







from typing import TypeVar

from .arrow_dataset import Dataset, _split_by_node_map_style_dataset
from .iterable_dataset import IterableDataset, _split_by_node_iterable_dataset


_a	:	List[Any]=					TypeVar("DatasetType", Dataset, IterableDataset)
def     __UpperCAmelCase							(       UpperCAmelCase_       :							DatasetType     ,				UpperCAmelCase_       :							int     ,				UpperCAmelCase_       :							int    )				->     DatasetType:

	'''simple docstring'''





	if isinstance(UpperCAmelCase_     ,				UpperCAmelCase_    ):
		return _split_by_node_map_style_dataset(UpperCAmelCase_     ,				rank=UpperCAmelCase_     ,				world_size=UpperCAmelCase_    )
	else:
		return _split_by_node_iterable_dataset(UpperCAmelCase_     ,				rank=UpperCAmelCase_     ,				world_size=UpperCAmelCase_    )





