code: def test_to_torch_coo_tensor_save_load(tmp_path):
      edge_index = torch.tensor(
          [
              [0, 1, 1, 2, 2, 3],
              [1, 0, 2, 1, 3, 2],
          ]
      )
      adj = to_torch_coo_tensor(edge_index, is_coalesced=False)
      assert adj.is_coalesced()
  
      path = osp.join(tmp_path, "adj.t")
      torch.save(adj, path)
      adj = torch.load(path)
      assert adj.is_coalesced()
  
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 8 for calling a global function with example usage: test_to_torch_coo_tensor_save_load(tmp_path) without return types