class_docstr: Abstract base class for botorch posteriors.
  
  :meta private:
class_docstr_tok: ["Abstract","base","class","for","botorch","posteriors",".",":","meta","private",":"]
docstr: The base shape of the base samples expected in `rsample`.
  
  Informs the sampler to produce base samples of shape
  `sample_shape x base_sample_shape`.
docstr_tok: ["The","base","shape","of","the","base","samples","expected","in","`","rsample","`",".","Informs","the","sampler","to","produce","base","samples","of","shape","`","sample_shape","x","base_sample_shape","`","."]
code: def base_sample_shape(self) -> torch.Size:
      r"""The base shape of the base samples expected in `rsample`.
  
      Informs the sampler to produce base samples of shape
      `sample_shape x base_sample_shape`.
      """
      raise NotImplementedError(
          f"{self.__class__.__name__} does not implement `base_sample_shape`."
      )
  
file_path: botorch/botorch/posteriors/posterior.py
imports: from __future__ import annotations
  import warnings
  from abc import ABC, abstractmethod, abstractproperty
  from typing import Optional, Tuple
  import torch
  from torch import Tensor
label_desc: Use image node_id 10 for calling the Posterior obj's underlying member method code with example usage: obj.base_sample_shape() without return types