def solve(self, cipher):
        N, A = cipher
        A.sort()

        diff = 1 << 31
        lst = []
        for i in xrange(N - 1):
            b = A[i + 1]
            a = A[i]
            if abs(a - b) < diff:
                diff = abs(a - b)
                lst = [a, b]
            elif abs(a - b) == diff:
                lst.append(a)
                lst.append(b)

        return " ".join(map(str, lst))
Predict without normalisation. This can be used for the first few chunks to find good parameters.
dataset/ETHPy150Open algorhythms/HackerRankAlgorithms/Closest Numbers.py/Solution.solve--crossover with--dataset/ETHPy150Open benanne/kaggle-galaxies/custom.py/SoftplusDivGalaxyOutputLayer.predictions_no_normalisation