code: def _make_deterministic_posterior(self, shape, dtype):
      mean = torch.rand(*shape, 1, dtype=dtype, device=self.device)
      return DeterministicPosterior(values=mean)
  
imports: from itertools import product
  import torch
  from botorch.posteriors import GPyTorchPosterior, Posterior, PosteriorList
  from botorch.posteriors.deterministic import DeterministicPosterior
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.distributions import MultivariateNormal
  from linear_operator.operators import to_linear_operator
label_desc: Use image node_id 2 for calling the TestPosteriorList obj's underlying member method code with example usage: obj._make_deterministic_posterior(shape, dtype) and returns: DeterministicPosterior