code: def test_adv_indexing_list(self):
      # indexing with list is equivalent to indexing with tensor
      def func1(x):
          return x[[0, 1, 5]]
  
      def func2(x):
          return x[[0, 1], [0, 1]]
  
      def func3(x):
          return x[[[0, 1], [0, 1]], [[0, 1], [0, 1]]]
  
      def func4(x):
          ls = [0]
          ls.append(1)
          ls.append(2)
          return x[ls]
  
      def func5(x):
          ls = [0.1, 1.2, 2.3]
          return x[ls]
  
      input = torch.rand((6, 2))
      self.checkScript(func1, (input,))
      self.checkScript(func2, (input,))
      self.checkScript(func3, (input,))
      self.checkScript(func4, (input,))
      self.checkScript(func5, (input,))
  
imports: import os
  import sys
  import tempfile
  import random
  from textwrap import dedent
  import torch
  from torch.testing._internal.jit_utils import JitTestCase, execWrapper
label_desc: Use image node_id 13 for calling the TestPythonBuiltinOP obj's underlying member method code with example usage: obj.test_adv_indexing_list() and returns: x, x, x, x, x