code: def test_forward(self):
      ga_covar = self.ga_kernel(self.X_in)
      ga_mean = delazify(self.ga_mean(self.X_in))
      ga_covar_diag = self.ga_kernel(self.X_in).diag()
  
      self.assertIsInstance(ga_covar, LazyEvaluatedKernelTensor)
      ga_covar = delazify(ga_covar)
      self.fitc.eval()
  
      with torch.no_grad(), gpytorch.settings.fast_pred_var():
          fitc_output = self.fitc(self.X_in)
          fitc_mean = fitc_output.mean
          fitc_covar = fitc_output.covariance_matrix
  
      torch.testing.assert_allclose(fitc_mean, ga_mean)
      torch.testing.assert_allclose(ga_covar, fitc_covar)
      torch.testing.assert_allclose(ga_covar_diag, fitc_output.variance)
  
      with self.assertRaises(RuntimeError):
          delazify(self.ga_kernel(self.X_in, self.X_out))
  
      self.ga_kernel.eval()
      ga_covar_train_test = delazify(
          self.ga_kernel(self.X_in, self.X_out)
      )
  
      self.assertTrue(
          ga_covar_train_test.shape == (len(self.X_in), len(self.X_out))
      )
  
imports: import copy
  import unittest.mock
  import gpytorch
  import numpy
  import torch
  from gpytorch.constraints.constraints import Interval
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.kernels import MaternKernel, ScaleKernel
  from gpytorch.kernels.inducing_point_kernel import InducingPointKernel
  from gpytorch.lazy import LazyEvaluatedKernelTensor, delazify
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.means.zero_mean import ZeroMean
  from gpytorch.models.exact_gp import ExactGP
  from smac.model.gaussian_process.kernels._boing import FITCKernel, FITCMean
  from smac.model.utils import check_subspace_points
label_desc: Use image node_id 3 for calling the TestFITCKernel obj's underlying member method code with example usage: obj.test_forward() without return types