class_docstr: L2 penalty class to be added to any arbitrary acquisition function
  to construct a PenalizedAcquisitionFunction.
docstr: Initializing L2 regularization.
  
  Args:
      init_point: The "1 x dim" reference point against which
          we want to regularize.
docstr_tok: ["Initializing","L2","regularization",".","Args",":","init_point",":","The","``","1","x","dim","''","reference","point","against","which","we","want","to","regularize","."]
code: def __init__(self, init_point: Tensor):
      r"""Initializing L2 regularization.
  
      Args:
          init_point: The "1 x dim" reference point against which
              we want to regularize.
      """
      super().__init__()
      self.init_point = init_point
  
imports: from __future__ import annotations
  import math
  from typing import Any, Callable, List, Optional
  import torch
  from botorch.acquisition.acquisition import AcquisitionFunction
  from botorch.acquisition.analytic import AnalyticAcquisitionFunction
  from botorch.acquisition.objective import GenericMCObjective
  from botorch.exceptions import UnsupportedError
  from torch import Tensor
label_desc: Use image node_id 1 to create a new L2Penalty object from inherited base classes: torch.nn with example: obj = L2Penalty(init_point)