code: def test_sort_large(self, device, dtype):
      t0 = torch.randperm(8192, device=device).to(dtype)
      t = t0.view(1, 8192).expand(2**18 + 1, -1).contiguous()
      v, i = t.sort()
      del t
      iv, im = i.var_mean(dim=0)
      del i
      vv, vm = v.var_mean(dim=0)
      del v
      self.assertEqual(vv, torch.zeros_like(vv))
      self.assertEqual(iv, torch.zeros_like(iv))
      self.assertEqual(
          vm, torch.arange(255, dtype=dtype, device=device)
      )
      self.assertEqual(im, t0.sort().indices)
  
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 6 for calling the TestSortAndSelect obj's underlying member method code with example usage: obj.test_sort_large(device, dtype) without return types