code: def test_group_lasso_penalty(self):
      for dtype in (torch.float, torch.double):
          tkwargs = {"device": self.device, "dtype": dtype}
          init_point = torch.tensor([0.5, 0.5, 0.5], **tkwargs)
          groups = [[0, 2], [1]]
          group_lasso_module = GroupLassoPenalty(
              init_point=init_point, groups=groups
          )
  
          # testing a single point
          sample_point = torch.tensor([[1.0, 2.0, 3.0]], **tkwargs)
          real_value = group_lasso_regularizer(
              sample_point - init_point, groups
          )  # torch.tensor([5.105551242828369], **tkwargs)
          computed_value = group_lasso_module(sample_point)
          self.assertEqual(computed_value.item(), real_value.item())
  
          # testing unsupported input dim: X.shape[-2] > 1
          sample_point_2 = torch.tensor(
              [[1.0, 2.0, 3.0], [2.0, 3.0, 4.0]], **tkwargs
          )
          with self.assertRaises(NotImplementedError):
              group_lasso_module(sample_point_2)
  
imports: import torch
  from botorch.acquisition.analytic import ExpectedImprovement
  from botorch.acquisition.monte_carlo import qExpectedImprovement
  from botorch.acquisition.penalized import GaussianPenalty, group_lasso_regularizer, GroupLassoPenalty, L0Approximation, L0PenaltyApprox, L0PenaltyApproxObjective, L1Penalty, L1PenaltyObjective, L2Penalty, PenalizedAcquisitionFunction, PenalizedMCObjective
  from botorch.exceptions import UnsupportedError
  from botorch.sampling.normal import IIDNormalSampler
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
  from torch import Tensor
label_desc: Use image node_id 1 for calling the TestGroupLassoPenalty obj's underlying member method code with example usage: obj.test_group_lasso_penalty() without return types