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
  import warnings
  from math import exp, pi
  from unittest.mock import MagicMock, patch
  import linear_operator
  import torch
  from torch import optim
  import gpytorch
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.kernels import InducingPointKernel, RBFKernel, ScaleKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.means import ConstantMean
  from gpytorch.priors import SmoothedBoxPrior
  from gpytorch.test.base_test_case import BaseTestCase
  from gpytorch.test.utils import least_used_cuda_device
  from gpytorch.utils.warnings import NumericalWarning
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