The code below gives an error TypeError: unhashable type: 'list'. Fix it from gensim import similarities cos_sim = similarities.MatrixSimilarity(tfidf[bows])

def tokenize(text):
    return tokens_re.findall(text)

def preprocess(text):
    tokens = tokenize(text)
    tokens = [token for token in tokens if not token in stop_words]
    tokens = [wordnet_lemmatizer.lemmatize(token) for token in tokens]
    return tokens