





def 	_a						(   UpperCAmelCase					)    ->    int:







   """simple docstring"""
   if divisor % 5 == 0 or divisor % 2 == 0:
      return 0
   lowerCamelCase__       :						str        =							1
   lowerCamelCase__       :						Tuple        =							1
   while repunit:
      lowerCamelCase__       :						Optional[int]        =							(10 * repunit + 1) % divisor
      repunit_index += 1
   return repunit_index



def 	_a						(   UpperCAmelCase = 1000000					)    ->    int:







   """simple docstring"""
   lowerCamelCase__       :						List[Any]        =							limit - 1
   if divisor % 2 == 0:
      divisor += 1
   while least_divisible_repunit(UpperCAmelCase					) <= limit:
      divisor += 2
   return divisor


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










import math
import random



def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase = False					)    ->    float:







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


# Initial Value
_A :   Tuple  			=  0.02



def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase					)    ->    float:







   """simple docstring"""
   lowerCamelCase__       :						List[Any]        =							float(2 * (random.randint(1      ,  100					)) - 1					)

   for _ in range(UpperCAmelCase					):
      # Forward propagation
      lowerCamelCase__       :						Optional[int]        =							sigmoid_function(INITIAL_VALUE * weight					)
      # How much did we miss?
      lowerCamelCase__       :						int        =							(expected / 100) - layer_a
      # Error delta
      lowerCamelCase__       :						Union[str, Any]        =							layer_1_error * sigmoid_function(UpperCAmelCase      ,  UpperCAmelCase					)
      # Update weight
      weight += INITIAL_VALUE * layer_1_delta

   return layer_a * 100


if __name__ == "__main__":
       import doctest

       doctest.testmod()

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



