class_docstr: A sampler that simply calls `posterior.rsample`, intended to be used with
  `DeterministicModel` & `DeterministicPosterior`.
  
  [DEPRECATED] - Use `IndexSampler` in conjunction with `EnsemblePosterior`
  instead of `DeterministicSampler` with `DeterministicPosterior`.
  
  This is effectively signals that `StochasticSampler` is safe to use with
  deterministic models since their output is deterministic by definition.
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docstr: This is a no-op since there are no base samples to update.
  
  Args:
      posterior: The posterior for which the base samples are constructed.
      base_sampler: The base sampler to retrieve the base samples from.
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code: def _update_base_samples(
      self,
      posterior: DeterministicPosterior,
      base_sampler: DeterministicSampler,
  ) -> None:
      r"""This is a no-op since there are no base samples to update.
  
      Args:
          posterior: The posterior for which the base samples are constructed.
          base_sampler: The base sampler to retrieve the base samples from.
      """
      return
  
imports: from __future__ import annotations
  from botorch.posteriors.deterministic import DeterministicPosterior
  from botorch.sampling.stochastic_samplers import StochasticSampler
label_desc: Use image node_id 1 for calling the DeterministicSampler obj's underlying member method code with example usage: obj._update_base_samples(posterior, base_sampler) without return types