code: def __init__(self, in_feats, out_feats, bias=True):
      super(GraphConvLayer, self).__init__()
      self.mlp = nn.Linear(in_feats * 2, out_feats, bias=bias)
  
file_path: dgl/examples/pytorch/hilander/models/graphconv.py
imports: import dgl.function
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.nn.pytorch import GATConv
  from torch.nn import init
label_desc: Use image node_id 1 to create a new GraphConvLayer object from inherited base classes: nn with example: obj = GraphConvLayer(in_feats, out_feats, bias)