code: def forward(
      self,
      x: Tensor,
      x_0: Tensor,
      edge_index: Adj,
      edge_weight: OptTensor = None,
  ) -> Tensor:
      x = self.propagation(x, edge_index, edge_weight=edge_weight)
      out = self.transformation(x, x_0[: x.size(0)])
      return out
  
imports: from typing import Optional
  from torch_geometric.typing import Adj, OptTensor
  import torch.nn.functional
  from torch.nn import ModuleList, Linear, BatchNorm1d
  from torch_geometric.nn import GCN2Conv
  import torch
  from torch import Tensor
  from torch_sparse import SparseTensor
  from ..models import ScalableGNN
label_desc: Use image node_id 4 for calling the GCN2Conv obj's underlying member method code with example usage: obj.forward(x, x_0, edge_index, edge_weight) and returns: out