code: def test_to_dense_adj_with_empty_edge_index():
      edge_index = torch.tensor([[], []], dtype=torch.long)
      batch = torch.tensor([0, 0, 1, 1, 1])
  
      adj = to_dense_adj(edge_index)
      assert adj.size() == (1, 0, 0)
  
      adj = to_dense_adj(edge_index, max_num_nodes=10)
      assert adj.size() == (1, 10, 10) and adj.sum() == 0
  
      adj = to_dense_adj(edge_index, batch)
      assert adj.size() == (2, 3, 3) and adj.sum() == 0
  
      adj = to_dense_adj(edge_index, batch, max_num_nodes=10)
      assert adj.size() == (2, 10, 10) and adj.sum() == 0
  
imports: import torch
  from torch_geometric.testing import is_full_test
  from torch_geometric.utils import to_dense_adj
label_desc: Use image node_id 2 for calling a global function with example usage: test_to_dense_adj_with_empty_edge_index() without return types