code: def vectors(self):
      vectors = {}
      look_back = self.g.look_back_list
      for i, embedding in enumerate(self._X):
          vectors[look_back[i]] = embedding
      return vectors
  
file_path: OpenNE/src/openne/lle.py
imports: from time import time
  import networkx
  import numpy
  import scipy.io
  import scipy.sparse
  import scipy.sparse.linalg
  from .None import graph
  from sklearn.preprocessing import normalize
label_desc: Use image node_id 3 for calling the LLE obj's underlying member method code with example usage: obj.vectors() and returns: vectors