class_docstr: Abstract base class for acquisition functions using one-shot optimization
  
  :meta private:
docstr: Get augmented q batch size for one-shot optimization.
  
  Args:
      q: The number of candidates to consider jointly.
  
  Returns:
      The augmented size for one-shot optimization (including variables
      parameterizing the fantasy solutions).
docstr_tok: ["Get","augmented","q","batch","size","for","one-shot","optimization",".","Args",":","q",":","The","number","of","candidates","to","consider","jointly",".","Returns",":","The","augmented","size","for","one-shot","optimization","(","including","variables","parameterizing","the","fantasy","solutions",")","."]
code: def get_augmented_q_batch_size(self, q: int) -> int:
      r"""Get augmented q batch size for one-shot optimization.
  
      Args:
          q: The number of candidates to consider jointly.
  
      Returns:
          The augmented size for one-shot optimization (including variables
          parameterizing the fantasy solutions).
      """
      pass
  
imports: from __future__ import annotations
  import warnings
  from abc import ABC, abstractmethod
  from typing import Optional
  import torch
  from botorch.exceptions import BotorchWarning
  from botorch.models.model import Model, ModelDict
  from botorch.posteriors.posterior import Posterior
  from botorch.sampling.base import MCSampler
  from botorch.sampling.get_sampler import get_sampler
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 1 for calling the OneShotAcquisitionFunction obj's underlying member method code with example usage: obj.get_augmented_q_batch_size(q) without return types