code: def test_permute(device):
      row, col = tensor(
          [[0, 0, 1, 2, 2], [0, 1, 0, 1, 2]], torch.long, device
      )
      value = tensor([1, 2, 3, 4, 5], torch.float, device)
      adj = SparseTensor(row=row, col=col, value=value)
  
      row, col, value = adj.permute(torch.tensor([1, 0, 2])).coo()
      assert row.tolist() == [0, 1, 1, 2, 2]
      assert col.tolist() == [1, 0, 1, 0, 2]
      assert value.tolist() == [3, 2, 1, 4, 5]
  
imports: import pytest
  import torch
  from torch_sparse.tensor import SparseTensor
  from torch_sparse.testing import devices, tensor
label_desc: Use image node_id 1 for calling a global function with example usage: test_permute(device) without return types