code: def test_to_numpy_bool(self, device) -> None:
      x = torch.tensor([True, False], dtype=torch.bool)
      self.assertEqual(x.dtype, torch.bool)
  
      y = x.numpy()
      self.assertEqual(y.dtype, np.bool_)
      for i in range(len(x)):
          self.assertEqual(x[i], y[i])
  
      x = torch.tensor([True], dtype=torch.bool)
      self.assertEqual(x.dtype, torch.bool)
  
      y = x.numpy()
      self.assertEqual(y.dtype, np.bool_)
      self.assertEqual(x[0], y[0])
  
imports: import torch
  import numpy
  from itertools import product
  from torch.testing._internal.common_utils import skipIfTorchDynamo, TestCase, run_tests
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, dtypes, skipMeta
  from torch.testing._internal.common_dtype import all_types_and_complex_and
label_desc: Use image node_id 4 for calling the TestNumPyInterop obj's underlying member method code with example usage: obj.test_to_numpy_bool(device) without return types