code: def test_kernel_with_permute(self):
      def f(a):
          return a.permute([2, 1, 0])
  
      device, size = "cpu", (3, 4, 5)
      x = torch.rand(size, device=device)
  
      graph_str = """
  graph(%a.1 : Float(3, 4, 5, strides=[20, 5, 1], requires_grad=0, device=cpu)):
    %1 : int = prim::Constant[value=2]()
    %2 : int = prim::Constant[value=1]()
    %3 : int = prim::Constant[value=0]()
    %4 : int[] = prim::ListConstruct(%1, %2, %3)
    %5 : Float(5, 4, 3, strides=[12, 3, 1], requires_grad=0, device=cpu) = aten::permute(%a.1, %4)
    return (%5)
          """
      graph = torch._C.parse_ir(graph_str)
  
      kernel = te.TensorExprKernel(graph)
      res1 = kernel.run((x,))
      res2 = kernel.fallback((x,))
      correct = f(x)
      np.testing.assert_allclose(
          res1.numpy(), correct.numpy(), atol=2e-3
      )
      np.testing.assert_allclose(
          res2.numpy(), correct.numpy(), atol=2e-3
      )
  
imports: import torch
  import numpy
  import torch._C._te
  from torch.testing._internal.common_utils import run_tests
  from torch.testing._internal.jit_utils import JitTestCase
  import unittest
label_desc: Use image node_id 13 for calling the TestTensorExprPyBind obj's underlying member method code with example usage: obj.test_kernel_with_permute() and returns: a