code: def test_MultivariateNormalQMCEngineNonPD(self):
      for dtype in (torch.float, torch.double):
          mean = torch.zeros(3, device=self.device, dtype=dtype)
          cov = torch.tensor(
              [[1, 0, 1], [0, 1, 1], [1, 1, 2]],
              device=self.device,
              dtype=dtype,
          )
          # try with non-pd but psd cov; should work
          engine = MultivariateNormalQMCEngine(mean=mean, cov=cov)
          self.assertTrue(engine._corr_matrix is not None)
  
imports: import itertools
  import math
  import numpy
  import torch
  from botorch.sampling.qmc import MultivariateNormalQMCEngine, NormalQMCEngine
  from botorch.utils.testing import BotorchTestCase
  from scipy.stats import shapiro
label_desc: Use image node_id 3 for calling the MultivariateNormalQMCTests obj's underlying member method code with example usage: obj.test_MultivariateNormalQMCEngineNonPD() without return types