class_docstr: A generic transformation of a posterior (implicitly represented).
class_docstr_tok: ["A","generic","transformation","of","a","posterior","(","implicitly","represented",")","."]
docstr: The shape of a base sample used for constructing posterior samples.
docstr_tok: ["The","shape","of","a","base","sample","used","for","constructing","posterior","samples","."]
code: def base_sample_shape(self) -> torch.Size:
      r"""The shape of a base sample used for constructing posterior samples."""
      return self._posterior.base_sample_shape
  
file_path: botorch/botorch/posteriors/transformed.py
imports: from __future__ import annotations
  from typing import Callable, Optional, Tuple
  import torch
  from botorch.posteriors.posterior import Posterior
  from torch import Tensor
label_desc: Use image node_id 2 for calling the TransformedPosterior obj's underlying member method code with example usage: obj.base_sample_shape() and returns: self