class_docstr: Fake vectorizer which converts document just to a vector of ones 
code: def transform(self, X):
      # assert X[0] == self.doc_
      return np.ones(len(self.text_.tokens)).reshape((1, -1))
  
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 3 for calling the SingleDocumentVectorizer obj's underlying member method code with example usage: obj.transform(X) and returns: np