code: def test_sign():
      x = torch.ones(5, 3)
      edge_index = torch.tensor(
          [
              [0, 1, 2, 3, 3, 4],
              [1, 0, 3, 2, 4, 3],
          ]
      )
      data = Data(x=x, edge_index=edge_index)
  
      transform = SIGN(K=2)
      assert str(transform) == "SIGN(K=2)"
  
      expected_x1 = torch.tensor(
          [
              [1, 1, 1],
              [1, 1, 1],
              [0.7071, 0.7071, 0.7071],
              [1.4142, 1.4142, 1.4142],
              [0.7071, 0.7071, 0.7071],
          ]
      )
      expected_x2 = torch.ones(5, 3)
  
      out = transform(data)
      assert len(out) == 4
      assert torch.equal(out.edge_index, edge_index)
      assert torch.allclose(out.x, x)
      assert torch.allclose(out.x1, expected_x1, atol=1e-4)
      assert torch.allclose(out.x2, expected_x2)
  
imports: import torch
  from torch_geometric.data import Data
  from torch_geometric.testing import withPackage
  from torch_geometric.transforms import SIGN
label_desc: Use image node_id 1 for calling a global function with example usage: test_sign() without return types