evaluate.py 文件源码

def closest_docs_by_index(corpus_vectors, query_vectors, n_docs):
    docs = []
    sim = pw.cosine_similarity(corpus_vectors, query_vectors)
    order = np.argsort(sim, axis=0)[::-1]
    for i in range(len(query_vectors)):
        docs.append(order[:, i][0:n_docs])
    return np.array(docs)