code: def forward(self, x):
      mean = self.mean_module(x)
      covar = self.covar_module(x)
      return MultivariateNormal(mean, covar)
  
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 2 for calling the FITC obj's underlying member method code with example usage: obj.forward(x) and returns: MultivariateNormal