code: def forward(self, x):
      mean_x = self.mean_module(x)
      covar_x = self.covar_module(x)
      return MultivariateNormal(mean_x, covar_x)
  
imports: import os
  import random
  import unittest
  from math import pi
  import torch
  from torch import optim
  import gpytorch
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.kernels import GridInterpolationKernel, RBFKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.means import ConstantMean
  from gpytorch.priors import SmoothedBoxPrior
label_desc: Use image node_id 2 for calling the GPRegressionModel obj's underlying member method code with example usage: obj.forward(x) and returns: MultivariateNormal