code: def test_multivariate_normal_prior_log_prob_log_transform(
      self, cuda=False
  ):
      device = torch.device("cuda") if cuda else torch.device("cpu")
      mean = torch.tensor([0.0, 1.0], device=device)
      cov = torch.eye(2, device=device)
      prior = MultivariateNormalPrior(
          mean, covariance_matrix=cov, transform=torch.exp
      )
      dist = MultivariateNormal(mean, covariance_matrix=cov)
  
      t = torch.tensor([-1, 0.5], device=device)
      self.assertTrue(
          torch.equal(prior.log_prob(t), dist.log_prob(t.exp()))
      )
      t = torch.tensor([[-1, 0.5], [1.5, -2.0]], device=device)
      self.assertTrue(
          torch.equal(prior.log_prob(t), dist.log_prob(t.exp()))
      )
      with self.assertRaises(RuntimeError):
          prior.log_prob(torch.zeros(3, device=device))
  
file_path: gpytorch/test/priors/test_multivariate_normal_prior.py
imports: import unittest
  import torch
  from torch.distributions import MultivariateNormal
  from gpytorch.priors import MultivariateNormalPrior
  from gpytorch.test.utils import least_used_cuda_device
label_desc: Use image node_id 5 for calling the TestMultivariateNormalPrior obj's underlying member method code with example usage: obj.test_multivariate_normal_prior_log_prob_log_transform(cuda) without return types