class_docstr: Fake vectorizer which converts document just to a vector of ones 
code: def get_feature_names(self):
      # type: () -> List[str]
      return [
          self._featname(idx, token)
          for idx, token in enumerate(self.text_.tokens)
      ]
  
file_path: eli5/eli5/lime/_vectorizer.py
imports: from __future__ import absolute_import
  from typing import Tuple, Callable, Dict, Optional, List
  import numpy
  from sklearn.base import BaseEstimator, TransformerMixin
  from eli5.base import DocWeightedSpans, FeatureWeights
  from eli5.sklearn.text import _get_feature_weights_dict
  from .textutils import TokenizedText
label_desc: Use image node_id 6 for calling the SingleDocumentVectorizer obj's underlying member method code with example usage: obj.get_feature_names() and returns: unknown