class_docstr: Abstract base class for acquisition functions.
  
  Please note that if your acquisition requires a backwards call,
  you will need to wrap the backwards call inside of an enable_grad
  context to be able to optimize the acquisition. See #1164.
  
  :meta private:
docstr: Constructor for the AcquisitionFunction base class.
  
  Args:
      model: A fitted model.
docstr_tok: ["Constructor","for","the","AcquisitionFunction","base","class",".","Args",":","model",":","A","fitted","model","."]
code: def __init__(self, model: Model) -> None:
      r"""Constructor for the AcquisitionFunction base class.
  
      Args:
          model: A fitted model.
      """
      super().__init__()
      self.model: Model = model
  
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 to create a new AcquisitionFunction object from inherited base classes: Module, ABC with example: obj = AcquisitionFunction(model)