code: def forward(self, x0: Tensor, edge_index: Tensor) -> Tensor:
      x1 = self.conv1(x0, edge_index).relu_()
      x2 = self.conv2(x1, edge_index).relu_()
      return self.lin1(torch.cat([x0, x1, x2], dim=-1))
  
imports: from typing import Tuple
  import pytest
  import torch
  from torch import Tensor
  from torch.nn import Linear, ReLU, Sequential
  import torch_geometric.typing
  from torch_geometric.nn import GINEConv, MessagePassing, RGCNConv, SAGEConv, to_hetero_with_bases
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 2 for calling the Net4 obj's underlying member method code with example usage: obj.forward(x0, edge_index) and returns: self