code: def __init__(
      self,
      node_encoder,
      dims,
      fanouts,
      metapath,
      feature_idx,
      feature_dim,
      node_type,
      edge_type,
      max_id,
      num_negs=5,
  ):
      super(GraphAutoEncoder, self).__init__(
          node_type, edge_type, max_id, num_negs
      )
      if node_encoder == "gcn":
          self.gnn = GNN(
              "gcn",
              "full",
              dims,
              None,
              metapath,
              feature_idx,
              feature_dim,
          )
      else:
          self.gnn = GNN(
              "sage",
              "sage",
              dims,
              fanouts,
              metapath,
              feature_idx,
              feature_dim,
          )
  
      self.dim = dims[-1]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
  from tf_euler.python.utils.encoders import ShallowEncoder
  from tf_euler.python.mp_utils.base_gnn import BaseGNNNet
  from tf_euler.python.mp_utils.base_gae import BaseGraphAutoEncoder
label_desc: Use image node_id 1 to create a new GraphAutoEncoder object from inherited base classes: BaseGraphAutoEncoder with example: obj = GraphAutoEncoder(node_encoder, dims, fanouts, metapath, feature_idx, feature_dim, node_type, edge_type, max_id, num_negs)