code: def encode(self, x, adj):
      hidden1 = self.gc1(x, adj)
      return self.gc2(hidden1, adj), self.gc3(hidden1, adj)
  
file_path: graph4nlp/graph4nlp/pytorch/test/link_prediction/model.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from layers import GraphConvolution
  from ...modules.prediction.classification.link_prediction.ConcatFeedForwardNNLayer import ConcatFeedForwardNNLayer
  from ...modules.prediction.classification.link_prediction.ElementSumLayer import ElementSumLayer
  from ...modules.prediction.classification.link_prediction.StackedElementProdLayer import StackedElementProdLayer
label_desc: Use image node_id 2 for calling the GCNModelVAE obj's underlying member method code with example usage: obj.encode(x, adj) and returns: self,  self