code: def tfidf(self, doc):
      doc_rep = self._vectorizer.transform([doc])
      features = self._vectorizer.get_feature_names_out()
      return [
          (features[index], doc_rep[0, index])
          for index in doc_rep.nonzero()[1]
      ]
  
imports: from sematch.utility import FileIO
  from nltk.stem import WordNetLemmatizer
  from nltk.corpus import wordnet
  import nltk
  from collections import Counter
  import itertools
  import string
  import re
label_desc: Use image node_id 3 for calling the TFIDF obj's underlying member method code with example usage: obj.tfidf(doc) and returns: unknown