code: def __init__(self, *args, **kwargs):
      super(GCNConv, self).__init__(*args, **kwargs)
      self.edge_weight = None
      self.weight = nn.Parameter(
          self.lin.weight.data.T.clone().detach()
      )
  
imports: import torch
  import torch.nn
  from functools import partial
  from typing import Union, List
  import torch.nn.functional
  from torch_geometric.data import Batch
  from torch_geometric.nn.conv.gcn_conv import gcn_norm
  from torch_geometric.nn.conv import GCNConv
  from torch_geometric.nn.glob import global_mean_pool, global_add_pool, global_max_pool
  from torch import Tensor
  from torch_sparse import SparseTensor, fill_diag
  from torch_geometric.typing import Adj, OptTensor, Size
  from torch_geometric.utils import add_self_loops
  from dig.xgraph.models import GNNPool
  from collections import OrderedDict
label_desc: Use image node_id 1 to create a new GCNConv object from inherited base classes: GCNConv with example: obj = GCNConv()