如何使用spacy文档相似度函数将数据集中的一个文档与所有其他文档进行比较？

import spacy
from spacy import displacy
from spacy.matcher import PhraseMatcher

nlp = spacy.load('en_core_web_sm')

matcher = PhraseMatcher(nlp.vocab)
other_documents = [...]  # 其他文档的列表

for doc in other_documents:
    doc = nlp(doc)
    sentences = [sent.text for sent in doc.sents]
    patterns = [nlp(sent) for sent in sentences]
    matcher.add("Sentences", None, *patterns)

document_to_compare = "要比较的文档"
document_to_compare = nlp(document_to_compare)

sentences_to_compare = [sent.text for sent in document_to_compare.sents]
similar_sentences = []

for sentence in sentences_to_compare:
    pattern = nlp(sentence)
    matches = matcher(pattern)
    similarities = []

    for match_id, start, end in matches:
        span = document_to_compare[start:end]
        similarity = span.similarity(pattern)
        similarities.append((span.text, similarity))

    similarities.sort(key=lambda x: x[1], reverse=True)
    similar_sentences.append(similarities[0][0])

for i, sentence in enumerate(sentences_to_compare):
    print(f"句子 {i+1}:")
    print("原始句子:", sentence)
    print("相似句子:", similar_sentences[i])
    print()