code: def generic_obj(samples: Tensor, X=None) -> Tensor:
      return torch.log(torch.sum(samples**2, dim=-1))
  
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 a global function with example usage: generic_obj(samples, X) and returns: torch