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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _normalized_levenshtein_distance(s1, s2, acceptable_differences):
 """ This function calculates the levenshtein distance but allows for elements in the lists to be different by any number in the set acceptable_differences. :param s1: A list. :param s2: Another list. :param acceptable_differences: A set of numbers. If (s2[i]-s1[i]) is in the set then they are considered equal. :returns: """

    if len(s1) > len(s2):
        s1, s2 = s2, s1
        acceptable_differences = set(-i for i in acceptable_differences)
    distances = range(len(s1) + 1)
    for index2, num2 in enumerate(s2):
        new_distances = [index2 + 1]
        for index1, num1 in enumerate(s1):
            if num2 - num1 in acceptable_differences:
                new_distances.append(distances[index1])
            else:
                new_distances.append(1 + min((distances[index1],
                                             distances[index1+1],
                                             new_distances[-1])))
        distances = new_distances
    return distances[-1]