code: def test_tolist(self, device):
      list0D = []
      tensor0D = torch.tensor(list0D)
      self.assertEqual(tensor0D.tolist(), list0D)
  
      table1D = [1.0, 2.0, 3.0]
      tensor1D = torch.tensor(table1D)
      storage = torch.Storage(table1D)
      self.assertEqual(tensor1D.tolist(), table1D)
      self.assertEqual(storage.tolist(), table1D)
      self.assertEqual(tensor1D.tolist(), table1D)
      self.assertEqual(storage.tolist(), table1D)
  
      table2D = [[1, 2], [3, 4]]
      tensor2D = torch.tensor(table2D)
      self.assertEqual(tensor2D.tolist(), table2D)
  
      tensor3D = torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
      tensorNonContig = tensor3D.select(1, 1)
      self.assertFalse(tensorNonContig.is_contiguous())
      self.assertEqual(tensorNonContig.tolist(), [[3, 4], [7, 8]])
  
imports: import torch
  import numpy
  from itertools import product, combinations, permutations, chain
  from functools import partial
  import random
  import warnings
  import unittest
  from torch import nan
  from torch.testing import make_tensor
  from torch.testing._internal.common_utils import TestCase, run_tests, skipIfTorchDynamo, torch_to_numpy_dtype_dict, IS_JETSON
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, onlyCUDA, dtypes, onlyNativeDeviceTypes, dtypesIfCUDA, largeTensorTest
  from torch.testing._internal.common_dtype import all_types_and_complex_and, all_types, all_types_and
label_desc: Use image node_id 2 for calling the TestShapeOps obj's underlying member method code with example usage: obj.test_tolist(device) without return types