code: def coalesce(index, value, m, n, op="add"):
      """Row-wise sorts :obj:`value` and removes duplicate entries. Duplicate
      entries are removed by scattering them together. For scattering, any
      operation of `"torch_scatter"<https://github.com/rusty1s/pytorch_scatter>`_
      can be used.
  
      Args:
          index (:class:`LongTensor`): The index tensor of sparse matrix.
          value (:class:`Tensor`): The value tensor of sparse matrix.
          m (int): The first dimension of sparse matrix.
          n (int): The second dimension of sparse matrix.
          op (string, optional): The scatter operation to use. (default:
              :obj:`"add"`)
  
      :rtype: (:class:`LongTensor`, :class:`Tensor`)
      """
  
      storage = SparseStorage(
          row=index[0],
          col=index[1],
          value=value,
          sparse_sizes=(m, n),
          is_sorted=False,
      )
      storage = storage.coalesce(reduce=op)
      return (
          torch.stack([storage.row(), storage.col()], dim=0),
          storage.value(),
      )
  
label_desc: Use image node_id 1 for calling a global function with example usage: coalesce(index, value, m, n, op) and returns: torch,  storage