text: from dnnv.properties import *
  import numpy as np
  
  N1 = Network("N1")
  N2 = Network("N2")
  
  x = Image(__path__.parent / "input_6.npy")
  
  epsilon = Parameter("epsilon", type=float)
  true_class = 9
  other_class = 6
  
  Forall(
      x_,
      Implies(
          ((x - epsilon) < x_ < (x + epsilon)) & (0 <= x_ <= 1),
          And(
              Implies(np.argmax(N1(x_)) == true_class, np.argmax(N2(x_)) != other_class),
              Implies(np.argmax(N2(x_)) == true_class, np.argmax(N1(x_)) != other_class),
          ),
      ),
  )
  