code: def to_edge_index(
      adj: Union[Tensor, SparseTensor]
  ) -> Tuple[Tensor, Tensor]:
      r"""Converts a :class:`torch.sparse.Tensor` or a
      :class:`torch_sparse.SparseTensor` to edge indices and edge attributes.
  
      Args:
          adj (torch.sparse.Tensor or SparseTensor): The adjacency matrix.
  
      :rtype: (:class:`torch.Tensor`, :class:`torch.Tensor`)
  
      Example:
          >>> edge_index = torch.tensor([[0, 1, 1, 2, 2, 3],
          ...                            [1, 0, 2, 1, 3, 2]])
          >>> adj = to_torch_coo_tensor(edge_index)
          >>> to_edge_index(adj)
          (tensor([[0, 1, 1, 2, 2, 3],
                  [1, 0, 2, 1, 3, 2]]),
          tensor([1., 1., 1., 1., 1., 1.]))
      """
      if isinstance(adj, SparseTensor):
          row, col, value = adj.coo()
          if value is None:
              value = torch.ones(row.size(0), device=row.device)
          return torch.stack([row, col], dim=0).long(), value
  
      if adj.layout == torch.sparse_coo:
          adj = adj._coalesced_(True)
          return adj.indices().detach().long(), adj.values()
  
      if adj.layout == torch.sparse_csr:
          row = ptr2index(adj.crow_indices().detach())
          col = adj.col_indices().detach()
          return torch.stack([row, col], dim=0).long(), adj.values()
  
      if (
          torch_geometric.typing.WITH_PT112
          and adj.layout == torch.sparse_csc
      ):
          col = ptr2index(adj.ccol_indices().detach())
          row = adj.row_indices().detach()
          return torch.stack([row, col], dim=0).long(), adj.values()
  
      raise ValueError(
          f"Unexpected sparse tensor layout (got '{adj.layout}')"
      )
  
imports: import typing
  import warnings
  from typing import Any, List, Optional, Tuple, Union
  import torch
  from torch import Tensor
  import torch_geometric.typing
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import coalesce, cumsum
label_desc: Use image node_id 8 for calling a global function with example usage: to_edge_index(adj) and returns: torch,  value, adj,  adj, torch,  adj, torch,  adj