在spaCy中合并(使用retokenize)自定义名词块时，如何平均向量？

import spacy

nlp = spacy.load('en_core_web_sm')

from spacy.tokens import Doc

def merge_custom_noun_chunks(doc):
    with doc.retokenize() as retokenizer:
        for chunk in doc.noun_chunks:
            if chunk.text == "custom_noun_chunk":
                retokenizer.merge(chunk)
    return doc

doc = nlp("This is a custom_noun_chunk.")
doc = merge_custom_noun_chunks(doc)

import numpy as np

def get_average_vector(doc):
    vectors = [token.vector for token in doc]
    average_vector = np.mean(vectors, axis=0)
    return average_vector

average_vector = get_average_vector(doc)