code: def test_multitask_from_repeat(self):
      mean = torch.randn(2, 3)
      variance = torch.randn(2, 3).clamp_min(1e-6)
      mvn = MultivariateNormal(mean, DiagLinearOperator(variance))
      mmvn = MultitaskMultivariateNormal.from_repeated_mvn(
          mvn, num_tasks=4
      )
      self.assertTrue(isinstance(mmvn, MultitaskMultivariateNormal))
      self.assertEqual(mmvn.batch_shape, torch.Size([2]))
      self.assertEqual(mmvn.event_shape, torch.Size([3, 4]))
      self.assertEqual(
          mmvn.covariance_matrix.shape, torch.Size([2, 12, 12])
      )
      for i in range(4):
          self.assertEqual(mmvn.mean[..., i], mean)
          self.assertEqual(mmvn.variance[..., i], variance)
  
imports: import math
  import os
  import random
  import unittest
  import torch
  from linear_operator.operators import DiagLinearOperator, KroneckerProductLinearOperator
  from gpytorch.distributions import MultitaskMultivariateNormal, MultivariateNormal
  from gpytorch.test.base_test_case import BaseTestCase
  from gpytorch.test.utils import least_used_cuda_device
label_desc: Use image node_id 18 for calling the TestMultiTaskMultivariateNormal obj's underlying member method code with example usage: obj.test_multitask_from_repeat() without return types