为什么我的代码无法在其他代码中使用？

Question

我有一个脚本来计算BLEU得分，另一个脚本则根据单词的POS标签执行相同的操作。当我将它们合并为一个代码时，创建的POS标记文件为空，并且代码崩溃导致出现此错误：

sentences=cube(sentences) TypeError: 'NoneType' object is not callable

由于文件为空，所以我不确定为什么。

我尝试过将POS文件创建成一个函数。仍然不起作用。

from nltk.translate.bleu_score import sentence_bleu
from nltk.translate.bleu_score import SmoothingFunction
import argparse
import sys
import csv
from cube.api import Cube

cube=Cube(verbose=True)
cube.load("en")

def argparser():
    Argparser = argparse.ArgumentParser()
    Argparser.add_argument('--reference', type=str, default='summaries.txt', help='Reference File')
    Argparser.add_argument('--candidate', type=str, default='candidates.txt', help='Candidate file')

    args = Argparser.parse_args()
    return args

args = argparser()

reference = open(args.reference, 'r').readlines()
candidate = open(args.candidate, 'r').readlines()


with open('pos_r.txt', 'w') as out1, open('pos_h.txt', 'w')as out2:
    for sentences in reference:
        sentences=cube(sentences)
        for sentence in sentences:
            for entry in sentence:
                    out1.write(entry.upos+"\t"+entry.attrs)
                out1.write('')
    for sentences in candidate:
        sentences=cube(sentences)
        for sentence in sentences:
            for entry in sentence:
                out2.write(entry.upos+"\t"+entry.attrs)
                out2.write('')


with open('results.txt','w')as out:
### BLEU
    cc=SmoothingFunction()

    if len(reference) != len(candidate):
     raise ValueError('The number of sentences in both files do not match.')

    score = 0.

    for i in range(len(reference)):
     score += sentence_bleu([reference[i].strip().split()], candidate[i].strip().split(),smoothing_function=cc.method5)

    score /= len(reference)
    out.write('BLEU score is ' +  '{:.3}'.format(score))

### POSBLEU
    with open('pos_r.txt', 'r') as f1, open('pos_h.txt', 'r')as f2:
        f1=f1.readlines()
        f2=f2.readlines()
        if len(f1) != len(f2):
            raise ValueError('The number of sentences in both files do not match.')

        score = 0.

        for i in range(len(f1)):
            score += sentence_bleu([f1[i].strip().split()], f2[i].strip().split(),smoothing_function=cc.method5)

        score /= len(f1)
        out.write('POSBLEU score is ' +  '{:.3}'.format(score))