code: def test_from_independent_mvns(self, cuda=False):
      device = torch.device("cuda") if cuda else torch.device("cpu")
      for dtype in (torch.float, torch.double):
          # Test non-batch mode mvns
          n_tasks = 2
          n = 4
          mvns = [
              MultivariateNormal(
                  mean=torch.randn(4, device=device, dtype=dtype),
                  covariance_matrix=DiagLinearOperator(
                      torch.randn(n, device=device, dtype=dtype).abs_()
                  ),
              )
              for i in range(n_tasks)
          ]
          mvn = MultitaskMultivariateNormal.from_independent_mvns(
              mvns=mvns
          )
          expected_mean_shape = [n, n_tasks]
          expected_covar_shape = [n * n_tasks] * 2
          self.assertEqual(list(mvn.mean.shape), expected_mean_shape)
          self.assertEqual(
              list(mvn.covariance_matrix.shape), expected_covar_shape
          )
  
          # Test batch mode mvns
          b = 3
          mvns = [
              MultivariateNormal(
                  mean=torch.randn(b, n, device=device, dtype=dtype),
                  covariance_matrix=DiagLinearOperator(
                      torch.randn(
                          b, n, device=device, dtype=dtype
                      ).abs_()
                  ),
              )
              for i in range(n_tasks)
          ]
          mvn = MultitaskMultivariateNormal.from_independent_mvns(
              mvns=mvns
          )
          self.assertEqual(
              list(mvn.mean.shape), [b] + expected_mean_shape
          )
          self.assertEqual(
              list(mvn.covariance_matrix.shape),
              [b] + expected_covar_shape,
          )
  
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 19 for calling the TestMultiTaskMultivariateNormal obj's underlying member method code with example usage: obj.test_from_independent_mvns(cuda) without return types