code: def _not_found_error(
      posterior: Posterior, sample_shape: torch.Size, **kwargs: Any
  ) -> None:
      raise NotImplementedError(
          f"A registered `MCSampler` for posterior {posterior} is not found. You can "
          "implement and register one using `@GetSampler.register`."
      )
  
imports: from typing import Any, Type, Union
  import torch
  from botorch.logging import logger
  from botorch.posteriors.deterministic import DeterministicPosterior
  from botorch.posteriors.ensemble import EnsemblePosterior
  from botorch.posteriors.gpytorch import GPyTorchPosterior
  from botorch.posteriors.posterior import Posterior
  from botorch.posteriors.posterior_list import PosteriorList
  from botorch.posteriors.torch import TorchPosterior
  from botorch.posteriors.transformed import TransformedPosterior
  from botorch.sampling.base import MCSampler
  from botorch.sampling.deterministic import DeterministicSampler
  from botorch.sampling.index_sampler import IndexSampler
  from botorch.sampling.list_sampler import ListSampler
  from botorch.sampling.normal import IIDNormalSampler, NormalMCSampler, SobolQMCNormalSampler
  from botorch.utils.dispatcher import Dispatcher
  from gpytorch.distributions import MultivariateNormal
  from torch.distributions import Distribution
  from torch.quasirandom import SobolEngine
label_desc: Use image node_id 8 for calling a global function with example usage: _not_found_error(posterior, sample_shape) without return types