code: def test_as_ndarray_dtypes(self) -> None:
      for torch_dtype, np_dtype in torch_to_numpy_dtype_dict.items():
          tens = torch.tensor(0, dtype=torch_dtype, device="cpu")
          self.assertEqual(torch_dtype, tens.dtype)
          self.assertEqual(tens.numpy().dtype, np_dtype)
          self.assertEqual(as_ndarray(tens, np_dtype).dtype, np_dtype)
  
file_path: botorch/test/optim/utils/test_numpy_utils.py
imports: from __future__ import annotations
  from unittest.mock import MagicMock
  import numpy
  import torch
  from botorch.optim.closures.core import as_ndarray, get_tensors_as_ndarray_1d, set_tensors_from_ndarray_1d
  from botorch.optim.utils import get_bounds_as_ndarray
  from botorch.optim.utils.numpy_utils import torch_to_numpy_dtype_dict
  from botorch.utils.testing import BotorchTestCase
  from torch.nn import Parameter
label_desc: Use image node_id 3 for calling the TestNumpyUtils obj's underlying member method code with example usage: obj.test_as_ndarray_dtypes() without return types