code: def __init__(self):
      super().__init__()
      self.lin1 = Linear(16, 16)
      self.conv1 = SAGEConv(16, 32)
      self.lin2 = Linear(32, 32)
  
imports: from typing import Optional
  import pytest
  import torch
  from torch import Tensor, nn
  import torch_geometric.typing
  from torch_geometric.nn import Linear, SAGEConv, summary, to_hetero
  from torch_geometric.nn.models import GCN
  from torch_geometric.testing import withPackage
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 1 to create a new GraphSAGE object from inherited base classes: torch.nn with example: obj = GraphSAGE()