code: def __init__(self):
      super().__init__()
      self.conv1 = SAGEConv((-1, -1), 32)
      self.conv2 = SAGEConv((-1, -1), 32)
  
file_path: pytorch_geometric/test/explain/conftest.py
imports: from typing import Optional
  import pytest
  import torch
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.explain import Explanation
  from torch_geometric.explain.config import MaskType
  from torch_geometric.nn import SAGEConv, to_hetero
  from torch_geometric.testing import get_random_edge_index
label_desc: Use image node_id 1 to create a new GraphSAGE object from inherited base classes: torch.nn with example: obj = GraphSAGE()