Pickle Tfidfvectorizer以及自定义标记器

Question

我正在使用服装标记器传递给TfidfVectorizer.该标记化器依赖于外部类TermExtractor,它位于另一个文件中.

我基本上想要基于某些术语构建TfidVectorizer,而不是所有单个单词/令牌.

这是代码:

from sklearn.feature_extraction.text import TfidfVectorizer
from TermExtractor import TermExtractor

extractor = TermExtractor()

def tokenize_terms(text):
    terms = extractor.extract(text)
    tokens = []
    for t in terms:
        tokens.append('_'.join(t))
    return tokens


def main(): 
    vectorizer = TfidfVectorizer(lowercase=True, min_df=2, norm='l2', smooth_idf=True, stop_words=stop_words, tokenizer=tokenize_terms)
    vectorizer.fit(corpus)
    pickle.dump(vectorizer, open("models/terms_vectorizer", "wb"))

运行正常,但每当我想重新使用这个TfidfVectorizer并用pickle加载它时,我收到一个错误:

vectorizer = pickle.load(open("models/terms_vectorizer", "rb"))

Traceback (most recent call last):
  File "./train-nps-comments-classifier.py", line 427, in <module>
    main()
  File "./train-nps-comments-classifier.py", line 325, in main
    vectorizer = pickle.load(open("models/terms_vectorizer", "rb"))
  File "/usr/lib/python2.7/pickle.py", line 1378, in load
    return Unpickler(file).load()
  File "/usr/lib/python2.7/pickle.py", line 858, in load
    dispatch[key](self)
  File "/usr/lib/python2.7/pickle.py", line 1090, in load_global
    klass = self.find_class(module, name)
  File "/usr/lib/python2.7/pickle.py", line 1126, in find_class
    klass = getattr(mod, name)
AttributeError: 'module' object has no attribute 'tokenize_terms'

当有依赖类时,Python pickle如何工作？

Answer 1

只要弄清楚，我需要在加载腌制的 TfidVectorizer 的同一代码中添加方法 tokenize_terms()，导入 TermExtractor，并创建一个提取器：

extractor = TermExtractor()