code: def test_marginal_variance(self):
      likelihood = MultitaskGaussianLikelihood(
          num_tasks=4, rank=0, has_global_noise=False
      )
      likelihood.task_noises = torch.tensor(
          [[0.1], [0.2], [0.3], [0.4]]
      )
  
      input = self._create_marginal_input()
      variance = likelihood(input).variance
      self.assertAllClose(
          variance, torch.tensor([1.1, 4.2, 9.3, 16.4]).repeat(5, 1)
      )
  
      likelihood = MultitaskGaussianLikelihood(
          num_tasks=4, rank=1, has_global_noise=True
      )
      likelihood.noise = torch.tensor(0.1)
      likelihood.task_noise_covar_factor.data = torch.tensor(
          [[1.0], [2.0], [3.0], [4.0]]
      )
  
      input = self._create_marginal_input()
      variance = likelihood(input).variance
      self.assertAllClose(
          variance, torch.tensor([2.1, 8.1, 18.1, 32.1]).repeat(5, 1)
      )
  
imports: import unittest
  import torch
  from linear_operator.operators import KroneckerProductLinearOperator, RootLinearOperator, ToeplitzLinearOperator
  from gpytorch.distributions import MultitaskMultivariateNormal
  from gpytorch.likelihoods import MultitaskGaussianLikelihood
  from gpytorch.test.base_likelihood_test_case import BaseLikelihoodTestCase
label_desc: Use image node_id 5 for calling the TestMultitaskGaussianLikelihood obj's underlying member method code with example usage: obj.test_marginal_variance() without return types