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 unittest
  from math import exp, pi
  import torch
  from torch import optim
  import gpytorch
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.kernels import RBFKernel, ScaleKernel
  from gpytorch.likelihoods import FixedNoiseGaussianLikelihood
  from gpytorch.likelihoods.noise_models import FixedGaussianNoise
  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
label_desc: Use image node_id 2 for calling the ExactGPModel obj's underlying member method code with example usage: obj.forward(x) and returns: MultivariateNormal