code: def test_add_remaining_self_loops_without_initial_loops():
      edge_index = torch.tensor([[0, 1], [1, 0]])
      edge_weight = torch.tensor([0.5, 0.5])
  
      expected = [[0, 1, 0, 1], [1, 0, 0, 1]]
  
      out = add_remaining_self_loops(edge_index, edge_weight)
      assert out[0].tolist() == expected
      assert out[1].tolist() == [0.5, 0.5, 1, 1]
  
      out = add_remaining_self_loops(
          edge_index, edge_weight, fill_value=5
      )
      assert out[0].tolist() == expected
      assert out[1].tolist() == [0.5, 0.5, 5.0, 5.0]
  
      out = add_remaining_self_loops(
          edge_index, edge_weight, fill_value=torch.tensor(2.0)
      )
      assert out[0].tolist() == expected
      assert out[1].tolist() == [0.5, 0.5, 2.0, 2.0]
  
      # Test string `fill_value`:
      out = add_remaining_self_loops(
          edge_index, edge_weight, fill_value="add"
      )
      assert out[0].tolist() == expected
      assert out[1].tolist() == [0.5, 0.5, 0.5, 0.5]
  
file_path: pytorch_geometric/test/utils/test_loop.py
imports: import torch
  from torch_geometric import EdgeIndex
  from torch_geometric.utils import add_remaining_self_loops, add_self_loops, contains_self_loops, get_self_loop_attr, remove_self_loops, segregate_self_loops, to_torch_coo_tensor
label_desc: Use image node_id 7 for calling a global function with example usage: test_add_remaining_self_loops_without_initial_loops() without return types