code: def get_embeddings(self):
      self.last_vectors = self.vectors
      self.vectors = {}
      if self.order == 3:
          vectors1 = self.model1.get_embeddings()
          vectors2 = self.model2.get_embeddings()
          for node in vectors1.keys():
              self.vectors[node] = np.append(
                  vectors1[node], vectors2[node]
              )
      else:
          self.vectors = self.model.get_embeddings()
  
imports: from __future__ import print_function
  import random
  import math
  import numpy
  from sklearn.linear_model import LogisticRegression
  import tensorflow
  from .classify import Classifier, read_node_label
label_desc: Use image node_id 2 for calling the LINE obj's underlying member method code with example usage: obj.get_embeddings() without return types