code: def test_csc_input(sparse_graph_1):
      data = sparse_graph_1
  
      g = SparseGraph(
          size=data.size,
          src_ids=data.src_ids_sorted_by_dst,
          cdst_ids=data.cdst_ids,
          values=data.values_csc,
          formats=["coo", "csc", "csr"],
      )
      src_ids, dst_ids, values = g.coo()
  
      new = torch.sparse_coo_tensor(
          torch.vstack((src_ids, dst_ids)), values
      ).cuda()
      old = torch.sparse_csc_tensor(
          data.cdst_ids, data.src_ids_sorted_by_dst, data.values_csc
      ).cuda()
      torch.allclose(new.to_dense(), old.to_dense())
  
      csrc_ids, dst_ids, values = g.csr()
  
      new = torch.sparse_csr_tensor(csrc_ids, dst_ids, values).cuda()
      torch.allclose(new.to_dense(), old.to_dense())
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_csc_input(sparse_graph_1) without return types