code: def test_arrayify(self):
      for dtype in (torch.float, torch.double, torch.int, torch.long):
          t = torch.tensor([[1, 2], [3, 4]], device=self.device).type(
              dtype
          )
          t_np = _arrayify(t)
          self.assertIsInstance(t_np, np.ndarray)
          self.assertTrue(t_np.dtype == np.float64)
  
imports: from itertools import product
  from typing import Callable
  import numpy
  import torch
  from botorch.exceptions.errors import CandidateGenerationError, UnsupportedError
  from botorch.optim.parameter_constraints import _arrayify, _generate_unfixed_lin_constraints, _generate_unfixed_nonlin_constraints, _make_linear_constraints, _make_nonlinear_constraints, eval_lin_constraint, lin_constraint_jac, make_scipy_bounds, make_scipy_linear_constraints, make_scipy_nonlinear_inequality_constraints, nonlinear_constraint_is_feasible
  from botorch.utils.testing import BotorchTestCase
  from scipy.optimize import Bounds
label_desc: Use image node_id 1 for calling the TestParameterConstraints obj's underlying member method code with example usage: obj.test_arrayify() without return types