code: def test_multitask_multivariate_normal_broadcasting(self):
      mean = torch.randn(5, 1, 3)
      _covar = torch.randn(6, 6)
      covar = _covar @ _covar.transpose(-1, -2)
      sample = MultitaskMultivariateNormal(mean, covar).rsample()
      self.assertEqual(sample.shape, torch.Size([5, 2, 3]))
  
      mean = torch.randn(5, 1)
      _covar = torch.randn(3, 10, 10)
      covar = _covar @ _covar.transpose(-1, -2)
      sample = MultitaskMultivariateNormal(mean, covar).rsample()
      self.assertEqual(sample.shape, torch.Size([3, 5, 2]))
  
      with self.assertRaises(RuntimeError):
          mean = torch.randn(5, 1)
          _covar = torch.randn(12, 12)
          covar = _covar @ _covar.transpose(-1, -2)
          MultitaskMultivariateNormal(mean, covar)
  
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 21 for calling the TestMultiTaskMultivariateNormal obj's underlying member method code with example usage: obj.test_multitask_multivariate_normal_broadcasting() without return types