class_docstr: Differentiable relaxation of the L0 norm penalty objective class.
  An instance of this class can be added to any arbitrary objective to
  construct a PenalizedMCObjective.
docstr: Initializing L0 penalty with differentiable relaxation.
  
  Args:
      target_point: A tensor corresponding to the target point.
      a: A hyperparameter that controls the differentiable relaxation.
docstr_tok: ["Initializing","L0","penalty","with","differentiable","relaxation",".","Args",":","target_point",":","A","tensor","corresponding","to","the","target","point",".","a",":","A","hyperparameter","that","controls","the","differentiable","relaxation","."]
code: def __init__(
      self, target_point: Tensor, a: float = 1.0, **tkwargs: Any
  ) -> None:
      r"""Initializing L0 penalty with differentiable relaxation.
  
      Args:
          target_point: A tensor corresponding to the target point.
          a: A hyperparameter that controls the differentiable relaxation.
      """
      super().__init__(target_point=target_point, a=a, **tkwargs)
  
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 L0PenaltyApproxObjective object from inherited base classes: L0Approximation with example: obj = L0PenaltyApproxObjective(target_point, a)