docstr: Samples from the posteriors and concatenates the samples.
  
  Args:
      posterior: A `PosteriorList` to sample from.
  
  Returns:
      The samples drawn from the posterior.
docstr_tok: ["Samples","from","the","posteriors","and","concatenates","the","samples",".","Args",":","posterior",":","A","`","PosteriorList","`","to","sample","from",".","Returns",":","The","samples","drawn","from","the","posterior","."]
code: def forward(self, posterior: PosteriorList) -> Tensor:
      r"""Samples from the posteriors and concatenates the samples.
  
      Args:
          posterior: A `PosteriorList` to sample from.
  
      Returns:
          The samples drawn from the posterior.
      """
      samples_list = [
          s(posterior=p)
          for s, p in zip(self.samplers, posterior.posteriors)
      ]
      return posterior._reshape_and_cat(tensors=samples_list)
  
file_path: botorch/botorch/sampling/list_sampler.py
imports: from __future__ import annotations
  import torch
  from botorch.exceptions.errors import UnsupportedError
  from botorch.posteriors.posterior_list import PosteriorList
  from botorch.sampling.base import MCSampler
  from torch import Tensor
  from torch.nn import ModuleList
label_desc: Use image node_id 4 for calling the ListSampler obj's underlying member method code with example usage: obj.forward(posterior) and returns: posterior