code: def __init__(
      self,
      graph,
      hidden_size=[32, 16],
      alpha=1e-6,
      beta=5.0,
      nu1=1e-5,
      nu2=1e-4,
  ):
      self.graph = graph
      # self.g.remove_edges_from(self.g.selfloop_edges())
      self.idx2node, self.node2idx = preprocess_nxgraph(self.graph)
  
      self.node_size = self.graph.number_of_nodes()
      self.hidden_size = hidden_size
      self.alpha = alpha
      self.beta = beta
      self.nu1 = nu1
      self.nu2 = nu2
  
      self.A, self.L = _create_A_L(
          self.graph, self.node2idx
      )  # Adj Matrix,L Matrix
      self.reset_model()
      self.inputs = [self.A, self.L]
      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 1 to create a new SDNE object from inherited base classes: object with example: obj = SDNE(graph, hidden_size, alpha, beta, nu1, nu2)