code: def test_setters(self):
      likelihood = MultitaskGaussianLikelihood(num_tasks=3, rank=0)
  
      a = torch.randn(3, 2)
      mat = a.matmul(a.transpose(-1, -2))
  
      # test rank 0 setters
      likelihood.noise = 0.5
      self.assertAlmostEqual(0.5, likelihood.noise.item())
  
      likelihood.task_noises = torch.tensor([0.04, 0.04, 0.04])
      for i in range(3):
          self.assertAlmostEqual(0.04, likelihood.task_noises[i].item())
  
      with self.assertRaises(AttributeError) as context:
          likelihood.task_noise_covar = mat
      self.assertTrue("task noises" in str(context.exception))
  
      # test low rank setters
      likelihood = MultitaskGaussianLikelihood(num_tasks=3, rank=2)
      likelihood.noise = 0.5
      self.assertAlmostEqual(0.5, likelihood.noise.item())
  
      likelihood.task_noise_covar = mat
      self.assertAllClose(mat, likelihood.task_noise_covar)
  
      with self.assertRaises(AttributeError) as context:
          likelihood.task_noises = torch.tensor([0.04, 0.04, 0.04])
      self.assertTrue("task noises" in str(context.exception))
  
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 6 for calling the TestMultitaskGaussianLikelihood obj's underlying member method code with example usage: obj.test_setters() without return types