code: def test_lazy_sage_conv(project):
      x = torch.randn(4, 8)
      edge_index = torch.tensor([[0, 1, 2, 3], [0, 0, 1, 1]])
  
      if project:
          with pytest.raises(ValueError, match="does not support lazy"):
              SAGEConv(-1, 32, project=project)
      else:
          conv = SAGEConv(-1, 32, project=project)
          assert str(conv) == "SAGEConv(-1, 32, aggr=mean)"
  
          out = conv(x, edge_index)
          assert out.size() == (4, 32)
  
file_path: pytorch_geometric/test/nn/conv/test_sage_conv.py
imports: import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.nn import MLPAggregation, SAGEConv
  from torch_geometric.testing import assert_module, is_full_test, onlyLinux, withCUDA, withPackage
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: test_lazy_sage_conv(project) without return types