code: def test_get_customized_covar_module(self) -> None:
      ard_num_dims = 3
      batch_shape = torch.Size([2])
      covar_module = _get_customized_covar_module(
          covar_module_prior_dict={},
          ard_num_dims=ard_num_dims,
          aug_batch_shape=batch_shape,
          task_feature=None,
      )
      self.assertIsInstance(covar_module, Module)
      self.assertIsInstance(covar_module, ScaleKernel)
      self.assertIsInstance(covar_module.outputscale_prior, GammaPrior)
      prior = checked_cast(GammaPrior, covar_module.outputscale_prior)
      self.assertEqual(prior.concentration, 2.0)
      self.assertEqual(prior.rate, 0.15)
      self.assertIsInstance(covar_module.base_kernel, MaternKernel)
      base_kernel = checked_cast(MaternKernel, covar_module.base_kernel)
      self.assertIsInstance(base_kernel.lengthscale_prior, GammaPrior)
      self.assertEqual(
          checked_cast(
              GammaPrior, base_kernel.lengthscale_prior
          ).concentration,
          3.0,
      )
      self.assertEqual(
          checked_cast(GammaPrior, base_kernel.lengthscale_prior).rate,
          6.0,
      )
      self.assertEqual(base_kernel.ard_num_dims, ard_num_dims)
      self.assertEqual(base_kernel.batch_shape, batch_shape)
  
      covar_module = _get_customized_covar_module(
          covar_module_prior_dict={
              "lengthscale_prior": GammaPrior(12.0, 2.0),
              "outputscale_prior": GammaPrior(2.0, 12.0),
          },
          ard_num_dims=ard_num_dims,
          aug_batch_shape=batch_shape,
          task_feature=3,
      )
      self.assertIsInstance(covar_module, Module)
      self.assertIsInstance(covar_module, ScaleKernel)
      self.assertIsInstance(covar_module.outputscale_prior, GammaPrior)
      prior = checked_cast(GammaPrior, covar_module.outputscale_prior)
      self.assertEqual(prior.concentration, 2.0)
      self.assertEqual(prior.rate, 12.0)
      self.assertIsInstance(covar_module.base_kernel, MaternKernel)
      base_kernel = checked_cast(MaternKernel, covar_module.base_kernel)
      self.assertIsInstance(base_kernel.lengthscale_prior, GammaPrior)
      self.assertEqual(
          checked_cast(
              GammaPrior, base_kernel.lengthscale_prior
          ).concentration,
          12.0,
      )
      self.assertEqual(
          checked_cast(GammaPrior, base_kernel.lengthscale_prior).rate,
          2.0,
      )
      self.assertEqual(base_kernel.ard_num_dims, ard_num_dims - 1)
      self.assertEqual(base_kernel.batch_shape, batch_shape)
  
imports: from copy import deepcopy
  from unittest import mock
  from unittest.mock import Mock
  import torch
  from ax.models.torch.botorch_defaults import _get_acquisition_func, _get_customized_covar_module, _get_model, get_and_fit_model, get_warping_transform, NO_FEASIBLE_POINTS_MESSAGE
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import checked_cast, not_none
  from ax.utils.testing.mock import fast_botorch_optimize
  from botorch.acquisition.logei import qLogExpectedImprovement, qLogNoisyExpectedImprovement
  from botorch.acquisition.monte_carlo import qExpectedImprovement, qNoisyExpectedImprovement, qProbabilityOfImprovement, qSimpleRegret
  from botorch.acquisition.objective import ConstrainedMCObjective
  from botorch.acquisition.penalized import L1PenaltyObjective, PenalizedMCObjective
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.gp_regression import SingleTaskGP
  from botorch.models.gp_regression_fidelity import SingleTaskMultiFidelityGP
  from botorch.models.multitask import MultiTaskGP
  from botorch.models.transforms.input import Warp
  from botorch.utils.constraints import get_outcome_constraint_transforms
  from gpytorch.kernels import MaternKernel, ScaleKernel
  from gpytorch.likelihoods.gaussian_likelihood import FixedNoiseGaussianLikelihood, GaussianLikelihood
  from gpytorch.module import Module
  from gpytorch.priors import GammaPrior
  from gpytorch.priors.lkj_prior import LKJCovariancePrior
  from gpytorch.priors.prior import Prior
label_desc: Use image node_id 5 for calling the BotorchDefaultsTest obj's underlying member method code with example usage: obj.test_get_customized_covar_module() without return types