code: def forward(self, x):
      mean_x = self.mean_module(x)
      covar_x = self.covar_module(x)
      return MultitaskMultivariateNormal(mean_x, covar_x)
  
file_path: gpytorch/test/examples/test_derivative_gp_fantasy.py
imports: import unittest
  from math import pi
  import torch
  import gpytorch
  from gpytorch.distributions import MultitaskMultivariateNormal
  from gpytorch.kernels import ScaleKernel, RBFKernelGrad
  from gpytorch.likelihoods import MultitaskGaussianLikelihood
  from gpytorch.means import ConstantMeanGrad
  from gpytorch.test.base_test_case import BaseTestCase
label_desc: Use image node_id 2 for calling the GPWithDerivatives obj's underlying member method code with example usage: obj.forward(x) and returns: MultitaskMultivariateNormal