code: def test_ctor_with_numpy_scalar_ctor(self, device) -> None:
      dtypes = [
          np.double,
          np.float64,
          np.float16,
          np.int64,
          np.int32,
          np.int16,
          np.uint8,
          np.bool_,
      ]
      for dtype in dtypes:
          self.assertEqual(dtype(42), torch.tensor(dtype(42)).item())
  
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 9 for calling the TestNumPyInterop obj's underlying member method code with example usage: obj.test_ctor_with_numpy_scalar_ctor(device) without return types