code: def test_to_graph_format() -> None:
      edge_index = torch.tensor([[1, 0, 2, 3], [0, 0, 1, 1]])
  
      csr, csc, perm = FusedGATConv.to_graph_format(
          edge_index, size=(4, 4)
      )
  
      assert csr[0].dtype == torch.int
      assert torch.equal(
          csr[0], torch.tensor([0, 1, 2, 3, 4], dtype=torch.int)
      )
      assert csr[1].dtype == torch.int
      assert torch.equal(
          csr[1], torch.tensor([0, 0, 1, 1], dtype=torch.int)
      )
      assert csc[0].dtype == torch.int
      assert torch.equal(
          csc[0], torch.tensor([0, 1, 2, 3], dtype=torch.int)
      )
      assert csc[1].dtype == torch.int
      assert torch.equal(
          csc[1], torch.tensor([0, 2, 4, 4, 4], dtype=torch.int)
      )
      assert perm.dtype == torch.int
      assert torch.equal(
          perm, torch.tensor([0, 1, 2, 3], dtype=torch.int)
      )
  
imports: import torch
  from torch_geometric.nn import FusedGATConv
  from torch_geometric.testing import onlyCUDA, withPackage
label_desc: Use image node_id 1 for calling a global function with example usage: test_to_graph_format() without return types