code: def __init__(self, in_dim, out_dim, num_layers, norm):
      super(GCN, self).__init__()
  
      self.num_layers = num_layers
      self.layers = nn.ModuleList()
  
      self.layers.append(
          GraphConv(
              in_dim,
              out_dim,
              bias=False,
              norm=norm,
              activation=nn.PReLU(),
          )
      )
      self.pooling = SumPooling()
  
      for _ in range(num_layers - 1):
          self.layers.append(
              GraphConv(
                  out_dim,
                  out_dim,
                  bias=False,
                  norm=norm,
                  activation=nn.PReLU(),
              )
          )
  
file_path: dgl/examples/pytorch/mvgrl/graph/model.py
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from dgl.nn.pytorch.glob import SumPooling
  from utils import local_global_loss_
label_desc: Use image node_id 1 to create a new GCN object from inherited base classes: nn with example: obj = GCN(in_dim, out_dim, num_layers, norm)