code: def __init__(self, g, in_channels, out_channels):
      super().__init__()
      self.g = g
      self.weight = Parameter(torch.empty(in_channels, out_channels))
      self.bias = Parameter(torch.empty(out_channels))
      self.reset_parameters()
  
imports: import dgl.function
  import torch
  import torch.nn.functional
  from torch.nn import Parameter
  from torch_geometric.nn.inits import glorot, zeros
label_desc: Use image node_id 1 to create a new GCNConv object from inherited base classes: torch.nn with example: obj = GCNConv(g, in_channels, out_channels)