code: def test_dense_to_sparse_bipartite():
      edge_index, edge_attr = dense_to_sparse(torch.rand(2, 10, 5))
      assert edge_index[0].max() == 19
      assert edge_index[1].max() == 9
  
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 2 for calling a global function with example usage: test_dense_to_sparse_bipartite() without return types