code: def evaluate(
      self,
  ):
      return self.model.evaluate(
          x=self.inputs, y=self.inputs, batch_size=self.node_size
      )
  
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 4 for calling the SDNE obj's underlying member method code with example usage: obj.evaluate() and returns: self