



'''simple docstring'''
from sklearn.neural_network import MLPClassifier

__SCREAMING_SNAKE_CASE :      Optional[int]             =[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
__SCREAMING_SNAKE_CASE :      Union[str, Any]             =[0, 1, 0, 0]


__SCREAMING_SNAKE_CASE :      Tuple             =MLPClassifier(
    solver='lbfgs', alpha=1e-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


__SCREAMING_SNAKE_CASE :      Tuple             =[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
__SCREAMING_SNAKE_CASE :      List[Any]             =clf.predict(test)



def 		_SCREAMING_SNAKE_CASE							(				lowerCamelCase__   :      Union[str, Any]				):


			'''simple docstring'''







			return list(lowerCamelCase__				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()










'''simple docstring'''
from .hash_table import HashTable
from .number_theory.prime_numbers import is_prime, next_prime


class   SCREAMING_SNAKE_CASE__				(   snake_case_					):
	"""simple docstring"""


	def __init__(		self					,   *A					,   **A			) ->							Dict:
				super().__init__(*A					,   **A			)


	def      a__ (		self					,   A					,   A			) ->							Dict:
				A:      int														=   (
				    next_prime(value % self.size_table			)
				    if not is_prime(value % self.size_table			)
				    else value % self.size_table
				)  # gt = bigger than
				return next_prime_gt - (data % next_prime_gt)


	def      a__ (		self					,   A					,   A					,   A			) ->							int:
				return (increment * self.__hash_function_a(A					,   A			)) % self.size_table





	def      a__ (		self					,   A					,   A=None			) ->							str:
				A:      Tuple														=   1
				A:      str														=   self.hash_function(A			)

				while self.values[new_key] is not None and self.values[new_key] != key:
							A:      int														=   (
							    self.__hash_double_function(A					,   A					,   A			)
							    if self.balanced_factor() >= self.lim_charge
							    else None
							)
							if new_key is None:
										break
							else:
										i += 1

				return new_key





