code: def transpose(index, value, m, n, coalesced=True):
      """Transposes dimensions 0 and 1 of a sparse tensor.
  
      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.
          coalesced (bool, optional): If set to :obj:`False`, will not coalesce
              the output. (default: :obj:`True`)
      :rtype: (:class:`LongTensor`, :class:`Tensor`)
      """
  
      row, col = index
      row, col = col, row
  
      if coalesced:
          sparse_sizes = (n, m)
          storage = SparseStorage(
              row=row,
              col=col,
              value=value,
              sparse_sizes=sparse_sizes,
              is_sorted=False,
          )
          storage = storage.coalesce()
          row, col, value = (
              storage.row(),
              storage.col(),
              storage.value(),
          )
  
      return torch.stack([row, col], dim=0), value
  
imports: import torch
  from torch_sparse.storage import SparseStorage
  from torch_sparse.tensor import SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: transpose(index, value, m, n, coalesced) and returns: torch,  value