code: def test_sort_1d_parallel(self, device, dtype):
      low = 0 if dtype == torch.uint8 else -128
      tensor = torch.randint(
          low=low, high=127, size=(100000,), device=device, dtype=dtype
      )
      vals, _ = torch.sort(tensor, stable=True)
      self.assertEqual(True, torch.all(vals[:-1] <= vals[1:]))
  
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 12 for calling the TestSortAndSelect obj's underlying member method code with example usage: obj.test_sort_1d_parallel(device, dtype) without return types