How to use the fuzzywuzzy.utils.intr function in fuzzywuzzy

def ratio(s1, s2):
    s1, s2 = utils.make_type_consistent(s1, s2)

    m = SequenceMatcher(None, s1, s2)
    return utils.intr(100 * m.ratio())

# should we look at partials?
    try_partial = True
    partial_scale = .9

    base = fuzz.ratio(p1, p2)
    len_ratio = float(max(len(p1), len(p2))-1) / min(len(p1), len(p2))

    # if strings are similar length, don't use partials
    if len_ratio < 1.3:
        try_partial = False

    if try_partial:
        partial = fuzz.partial_ratio(p1, p2) * partial_scale
        return utils.intr(max(base, partial))
    else:
        return utils.intr(base)

if len_ratio > 8:
        partial_scale = .6

    if try_partial:
        partial = partial_ratio(p1, p2) * partial_scale
        ptsor = partial_token_sort_ratio(p1, p2, full_process=False) \
            * unbase_scale * partial_scale
        ptser = partial_token_set_ratio(p1, p2, full_process=False) \
            * unbase_scale * partial_scale

        return utils.intr(max(base, partial, ptsor, ptser))
    else:
        tsor = token_sort_ratio(p1, p2, full_process=False) * unbase_scale
        tser = token_set_ratio(p1, p2, full_process=False) * unbase_scale

        return utils.intr(max(base, tsor, tser))

#   block = (1,3,3)
    #   best score === ratio("abcd", "Xbcd")
    scores = []
    for block in blocks:
        long_start = block[1] - block[0] if (block[1] - block[0]) > 0 else 0
        long_end = long_start + len(shorter)
        long_substr = longer[long_start:long_end]

        m2 = SequenceMatcher(None, shorter, long_substr)
        r = m2.ratio()
        if r > .995:
            return 100
        else:
            scores.append(r)

    return utils.intr(100 * max(scores))

# if strings are similar length, don't use partials
    if len_ratio < 1.5:
        try_partial = False

    # if one string is much much shorter than the other
    if len_ratio > 8:
        partial_scale = .6

    if try_partial:
        partial = partial_ratio(p1, p2) * partial_scale
        ptsor = partial_token_sort_ratio(p1, p2, full_process=False) \
            * unbase_scale * partial_scale
        ptser = partial_token_set_ratio(p1, p2, full_process=False) \
            * unbase_scale * partial_scale

        return utils.intr(max(base, partial, ptsor, ptser))
    else:
        tsor = token_sort_ratio(p1, p2, full_process=False) * unbase_scale
        tser = token_set_ratio(p1, p2, full_process=False) * unbase_scale

        return utils.intr(max(base, tsor, tser))