code: def forward(self, x: Tensor, edge_index: Tensor) -> Tensor:
      for i in range(len(self.lins)):
          x = self.convs[str(i)](x, edge_index) + self.lins[str(i)](x)
      return x
  
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 Net6 obj's underlying member method code with example usage: obj.forward(x, edge_index) and returns: x