code: def predict(self, data, top_k):
      target_idxes = self.choice(
          self.tokens, p=self.tfidf_scores, size=top_k
      )
      target_words = [self.tokens[i] for i in target_idxes]
      return target_words
  
file_path: nlpaug/nlpaug/model/word_stats/tfidf.py
imports: import os
  import math
  import numpy
  from nlpaug.model.word_stats import WordStatistics
label_desc: Use image node_id 8 for calling the TfIdf obj's underlying member method code with example usage: obj.predict(data, top_k) and returns: target_words