code: def test_to_torch_coo_tensor():
      edge_index = torch.tensor(
          [
              [0, 1, 1, 2, 2, 3],
              [1, 0, 2, 1, 3, 2],
          ]
      )
      edge_attr = torch.randn(edge_index.size(1), 8)
  
      adj = to_torch_coo_tensor(edge_index, is_coalesced=False)
      assert adj.is_coalesced()
      assert adj.size() == (4, 4)
      assert adj.layout == torch.sparse_coo
      assert torch.allclose(adj.indices(), edge_index)
  
      adj = to_torch_coo_tensor(edge_index, is_coalesced=True)
      assert adj.is_coalesced()
      assert adj.size() == (4, 4)
      assert adj.layout == torch.sparse_coo
      assert torch.allclose(adj.indices(), edge_index)
  
      adj = to_torch_coo_tensor(edge_index, size=6)
      assert adj.size() == (6, 6)
      assert adj.layout == torch.sparse_coo
      assert torch.allclose(adj.indices(), edge_index)
  
      adj = to_torch_coo_tensor(edge_index, edge_attr)
      assert adj.size() == (4, 4, 8)
      assert adj.layout == torch.sparse_coo
      assert torch.allclose(adj.indices(), edge_index)
      assert torch.allclose(adj.values(), edge_attr)
  
      if is_full_test():
          jit = torch.jit.script(to_torch_coo_tensor)
          adj = jit(edge_index, edge_attr)
          assert adj.size() == (4, 4, 8)
          assert adj.layout == torch.sparse_coo
          assert torch.allclose(adj.indices(), edge_index)
          assert torch.allclose(adj.values(), edge_attr)
  
file_path: pytorch_geometric/test/utils/test_sparse.py
imports: import os.path
  import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric.profile import benchmark
  from torch_geometric.testing import is_full_test, withCUDA, withPackage
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import dense_to_sparse, is_sparse, is_torch_sparse_tensor, to_edge_index, to_torch_coo_tensor, to_torch_csc_tensor, to_torch_csr_tensor, to_torch_sparse_tensor
  from torch_geometric.utils.sparse import cat
label_desc: Use image node_id 5 for calling a global function with example usage: test_to_torch_coo_tensor() without return types