

def 						_snake_case(    SCREAMING_SNAKE_CASE__			:	int = 600851475143      )							->      int:





    '''simple docstring'''






    try:
        A__          =   int(SCREAMING_SNAKE_CASE__      )
    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.'      )
    A__          =   2
    A__          =   0
    if n == 2:
        return 2
    while n > 2:
        while n % i != 0:
            i += 1
        A__          =   i
        while n % i == 0:
            A__          =   n // i
        i += 1
    return int(SCREAMING_SNAKE_CASE__      )


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





"""simple docstring"""







import math
import random




def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_ = False   ):




					'''simple docstring'''


					if deriv:
										return value * (1 - value)
					return 1 / (1 + math.exp(-value   ))


# Initial Value
a__				:							Tuple						=     0.02




def    UpperCAmelCase__       (lowerCAmelCase_  ,						lowerCAmelCase_   ):




					'''simple docstring'''


					__SCREAMING_SNAKE_CASE						   =				float(2 * (random.randint(1  ,						100   )) - 1   )

					for _ in range(lowerCAmelCase_   ):
										# Forward propagation
										__SCREAMING_SNAKE_CASE						   =				sigmoid_function(INITIAL_VALUE * weight   )
										# How much did we miss?
										__SCREAMING_SNAKE_CASE						   =				(expected / 100) - layer_a
										# Error delta
										__SCREAMING_SNAKE_CASE						   =				layer_1_error * sigmoid_function(lowerCAmelCase_  ,						lowerCAmelCase_   )
										# Update weight
										weight += INITIAL_VALUE * layer_1_delta

					return layer_a * 100


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		a__				:							List[str]						=     int(input('''Expected value: '''))
		a__				:							str						=     int(input('''Number of propagations: '''))
		print(forward_propagation(expected, number_propagations))
