code: def test_multivariate_normal_prior_to_gpu(self):
      if torch.cuda.is_available():
          prior = MultivariateNormalPrior(
              torch.tensor([0.0, 1.0]), covariance_matrix=torch.eye(2)
          ).cuda()
          self.assertEqual(prior.loc.device.type, "cuda")
          self.assertEqual(prior.covariance_matrix.device.type, "cuda")
          self.assertEqual(prior.scale_tril.device.type, "cuda")
          self.assertEqual(prior.precision_matrix.device.type, "cuda")
  
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 1 for calling the TestMultivariateNormalPrior obj's underlying member method code with example usage: obj.test_multivariate_normal_prior_to_gpu() without return types