code: def __init__(self, in_dim, out_dim):
      super(MVGRL, self).__init__()
  
      self.encoder1 = GraphConv(
          in_dim, out_dim, norm="both", bias=True, activation=nn.PReLU()
      )
      self.encoder2 = GraphConv(
          in_dim, out_dim, norm="none", bias=True, activation=nn.PReLU()
      )
      self.pooling = AvgPooling()
  
      self.disc = Discriminator(out_dim)
      self.act_fn = nn.Sigmoid()
  
file_path: dgl/examples/pytorch/mvgrl/node/model.py
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from dgl.nn.pytorch.glob import AvgPooling
label_desc: Use image node_id 1 to create a new MVGRL object from inherited base classes: nn with example: obj = MVGRL(in_dim, out_dim)