code: def test_topk_4d(self, device):
      small = 128
      large = 8192
      for size in (small, large):
          x = torch.ones(2, size, 2, 2, device=device)
          x[:, 1, :, :] *= 2.0
          x[:, 10, :, :] *= 1.5
          val, ind = torch.topk(x, k=2, dim=1)
          expected_ind = torch.ones(
              2, 2, 2, 2, dtype=torch.long, device=device
          )
          expected_ind[:, 1, :, :] = 10
          expected_val = torch.ones(2, 2, 2, 2, device=device)
          expected_val[:, 0, :, :] *= 2.0
          expected_val[:, 1, :, :] *= 1.5
          self.assertEqual(val, expected_val, atol=0, rtol=0)
          self.assertEqual(ind, expected_ind, atol=0, rtol=0)
  
imports: import torch
  import numpy
  import random
  from torch import nan
  from itertools import permutations, product
  from torch.testing import make_tensor
  from torch.testing._internal.common_dtype import all_types, all_types_and, floating_types_and, integral_types
  from torch.testing._internal.common_utils import TestCase, run_tests, slowTest, skipIfTorchDynamo
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, dtypes, onlyNativeDeviceTypes, onlyCUDA, dtypesIfCUDA, dtypesIfCPU, onlyCPU, largeTensorTest
label_desc: Use image node_id 26 for calling the TestSortAndSelect obj's underlying member method code with example usage: obj.test_topk_4d(device) without return types