class_docstr: Generic cost-aware utility wrapping a callable.
class_docstr_tok: ["Generic","cost-aware","utility","wrapping","a","callable","."]
docstr: Generic cost-aware utility wrapping a callable.
  
  Args:
      cost: A callable mapping a `batch_shape x q x d'`-dim candidate set
          to a `batch_shape`-dim tensor of costs
docstr_tok: ["Generic","cost-aware","utility","wrapping","a","callable",".","Args",":","cost",":","A","callable","mapping","a","`","batch_shape","x","q","x","d","'","`","-dim","candidate","set","to","a","`","batch_shape","`","-dim","tensor","of","costs"]
code: def __init__(self, cost: Callable[[Tensor, Tensor], Tensor]) -> None:
      r"""Generic cost-aware utility wrapping a callable.
  
      Args:
          cost: A callable mapping a `batch_shape x q x d'`-dim candidate set
              to a `batch_shape`-dim tensor of costs
      """
      super().__init__()
      self._cost_callable: Callable[[Tensor, Tensor], Tensor] = cost
  
imports: from __future__ import annotations
  import warnings
  from abc import ABC, abstractmethod
  from typing import Any, Callable, Optional, Union
  import torch
  from botorch import settings
  from botorch.acquisition.objective import GenericMCObjective, IdentityMCObjective, MCAcquisitionObjective
  from botorch.exceptions.warnings import CostAwareWarning
  from botorch.models.deterministic import DeterministicModel
  from botorch.models.gpytorch import GPyTorchModel
  from botorch.sampling.base import MCSampler
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 1 to create a new GenericCostAwareUtility object from inherited base classes: CostAwareUtility with example: obj = GenericCostAwareUtility(cost)