How to use the sense2vec.util.cosine_similarity function in sense2vec

for key, freq in vocab.items():
        try:
            term, sense = split_key(key)
        except ValueError:
            continue
        term = term.split("_")[-1]
        by_word[term.lower()].append((freq, key))
    too_similar = []
    for values in by_word.values():
        if len(values) >= 2:
            values.sort(reverse=True)
            freq1, key1 = values[0]
            vector1 = vectors[key1]
            for freq2, key2 in values[1:]:
                vector2 = vectors[key2]
                sim = cosine_similarity(vector1, vector2)
                if sim >= (1 - min_distance):
                    too_similar.append(key2)
    return too_similar