code: def _get_test_posterior(
      device, n=3, dtype=torch.float, batched=False
  ):
      mean = torch.zeros(n, device=device, dtype=dtype)
      cov = torch.eye(n, device=device, dtype=dtype)
      if batched:
          cov = cov.repeat(3, 1, 1)
      mvn = MultivariateNormal(mean, cov)
      return GPyTorchPosterior(mvn)
  
file_path: botorch/test/sampling/test_pairwise_sampler.py
imports: import torch
  from botorch.posteriors import GPyTorchPosterior
  from botorch.sampling.pairwise_samplers import PairwiseIIDNormalSampler, PairwiseSobolQMCNormalSampler
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.distributions import MultivariateNormal
label_desc: Use image node_id 1 for calling a global function with example usage: _get_test_posterior(device, n, dtype, batched) and returns: GPyTorchPosterior