code: def test_varitional_inference(self):
      # test taht variational inference is actually called
      # https://github.com/cornellius-gp/gpytorch/blob/master/test/kernels/test_inducing_point_kernel.py#L45
      _wrapped_ps = unittest.mock.MagicMock(
          wraps=gpytorch.variational.TrilNaturalVariationalDistribution
      )
      with unittest.mock.patch(
          "gpytorch.variational.TrilNaturalVariationalDistribution",
          new=_wrapped_ps,
      ) as rf_mock:
          self.gp_model._train(self.X_all, self.Y_all, do_optimize=True)
          self.assertTrue(rf_mock.called)
  
imports: from typing import Tuple
  import unittest.mock
  import gpytorch
  import numpy
  import pyro
  import torch
  from gpytorch.constraints.constraints import Interval
  from gpytorch.likelihoods.gaussian_likelihood import GaussianLikelihood
  from gpytorch.priors import HorseshoePrior
  from smac.configspace import ConfigurationSpace, UniformFloatHyperparameter
  from smac.model.gaussian_process.augmented_local_gaussian_process import AugmentedLocalGaussianProcess, GloballyAugmentedLocalGaussianProcess
  from smac.model.gaussian_process.gpytorch_gaussian_process import ExactGaussianProcessModel
  from ._test_boing_kernel import generate_kernel, generate_test_data
  from ._test_gp_gpytorch import TestGPGPyTorch
label_desc: Use image node_id 9 for calling the TestLGPGA obj's underlying member method code with example usage: obj.test_varitional_inference() without return types