'Set vacancy probabilities uniformly to
1 / cardinality of vacancy difference values'

def set_uniform_probabilities(self, sentence_aligned_corpus):

    max_m = longest_target_sentence_length(sentence_aligned_corpus)
    if ((max_m > 0) and ((1 / (2 * max_m)) < IBMModel.MIN_PROB)):
        warnings.warn((('A    target    sentence    is    too    long    (' + str(max_m)) + '    words).    Results    may    be    less    accurate.'))
    for max_v in range(1, (max_m + 1)):
        for dv in range(1, (max_m + 1)):
            initial_prob = (1 / (2 * max_v))
            self.head_vacancy_table[dv][max_v] = defaultdict((lambda : initial_prob))
            self.head_vacancy_table[(- (dv - 1))][max_v] = defaultdict((lambda : initial_prob))
            self.non_head_vacancy_table[dv][max_v] = defaultdict((lambda : initial_prob))
            self.non_head_vacancy_table[(- (dv - 1))][max_v] = defaultdict((lambda : initial_prob))
