class_docstr: Group lasso penalty class to be added to any arbitrary acquisition function
  to construct a PenalizedAcquisitionFunction.
docstr: X should be batch_shape x 1 x dim tensor. Evaluation for q-batch is not
  implemented yet.
docstr_tok: ["X","should","be","batch_shape","x","1","x","dim","tensor",".","Evaluation","for","q-batch","is","not","implemented","yet","."]
code: def forward(self, X: Tensor) -> Tensor:
      r"""
      X should be batch_shape x 1 x dim tensor. Evaluation for q-batch is not
      implemented yet.
      """
      if X.shape[-2] != 1:
          raise NotImplementedError(
              "group-lasso has not been implemented for q>1 yet."
          )
  
      regularization_term = group_lasso_regularizer(
          X=X.squeeze(-2) - self.init_point, groups=self.groups
      )
      return regularization_term
  
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 2 for calling the GroupLassoPenalty obj's underlying member method code with example usage: obj.forward(X) and returns: regularization_term