code: def get_embeddings(self):
      self._embeddings = {}
      embeddings = self.emb_model.predict(
          self.A.todense(), batch_size=self.node_size
      )
      look_back = self.idx2node
      for i, embedding in enumerate(embeddings):
          self._embeddings[look_back[i]] = embedding
  
      return self._embeddings
  
imports: import time
  import numpy
  import scipy.sparse
  import tensorflow
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.callbacks import History
  from tensorflow.python.keras.layers import Dense, Input
  from tensorflow.python.keras.models import Model
  from tensorflow.python.keras.regularizers import l1_l2
  from ..utils import preprocess_nxgraph
label_desc: Use image node_id 5 for calling the SDNE obj's underlying member method code with example usage: obj.get_embeddings() and returns: self