"""simple docstring"""






import math



def     a_		(   lowerCamelCase			):

				if 1 < number < 4:
								# 2 and 3 are primes
								return True
				elif number < 2 or number % 2 == 0 or number % 3 == 0:
								# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
								return False

				# All primes number are in format of 6k +/- 1
				for i in range(5   ,     int(math.sqrt(lowerCamelCase			) + 1			)   ,     6			):
								if number % i == 0 or number % (i + 2) == 0:
												return False
				return True



def     a_		(   lowerCamelCase = 6_0_0_8_5_1_4_7_5_1_4_3			):

				try:
								UpperCAmelCase__			 =				int(lowerCamelCase			)
				except (TypeError, ValueError):
								raise TypeError('Parameter n must be int or castable to int.'			)
				if n <= 0:
								raise ValueError('Parameter n must be greater than or equal to one.'			)
				UpperCAmelCase__			 =				0
				if is_prime(lowerCamelCase			):
								return n
				while n % 2 == 0:
								n //= 2
				if is_prime(lowerCamelCase			):
								return n
				for i in range(3   ,     int(math.sqrt(lowerCamelCase			)			) + 1   ,     2			):
								if n % i == 0:
												if is_prime(n // i			):
																UpperCAmelCase__			 =				n // i
																break
												elif is_prime(lowerCamelCase			):
																UpperCAmelCase__			 =				i
				return max_number


if __name__ == "__main__":
						print(F"""{solution() = }""")




"""simple docstring"""






from sklearn.neural_network import MLPClassifier

lowerCAmelCase__    :    Any			=      [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowerCAmelCase__    :    Optional[int]			=      [0, 1, 0, 0]


lowerCAmelCase__    :    Dict			=      MLPClassifier(
    solver='lbfgs', alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


lowerCAmelCase__    :    Optional[int]			=      [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
lowerCAmelCase__    :    Union[str, Any]			=      clf.predict(test)



def     a_		(   lowerCamelCase			):
				return list(lowerCamelCase			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()



