code: def clamp_candidates(
      X: Tensor, target_point: Tensor, clamp_tol: float, **tkwargs: Any
  ) -> Tensor:
      """Clamp generated candidates within the given ranges to the target point."""
      clamp_mask = (X - target_point).abs() < clamp_tol
      clamp_mask = clamp_mask
      X[clamp_mask] = (
          target_point.clone()
          .repeat(*X.shape[:-1], 1)
          .to(**tkwargs)[clamp_mask]
      )
      return X
  
imports: import functools
  from copy import deepcopy
  from functools import partial
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type
  import torch
  from ax.core.search_space import SearchSpaceDigest
  from ax.models.torch.botorch_modular.acquisition import Acquisition
  from ax.models.torch.botorch_modular.optimizer_argparse import optimizer_argparse
  from ax.models.torch.botorch_modular.surrogate import Surrogate
  from ax.models.torch_base import TorchOptConfig
  from ax.utils.common.constants import Keys
  from ax.utils.common.typeutils import not_none
  from botorch.acquisition.acquisition import AcquisitionFunction
  from botorch.acquisition.multi_objective.monte_carlo import qExpectedHypervolumeImprovement
  from botorch.acquisition.penalized import L0Approximation
  from botorch.models.deterministic import GenericDeterministicModel
  from botorch.models.model import ModelList
  from botorch.optim import Homotopy, HomotopyParameter, LogLinearHomotopySchedule, optimize_acqf_homotopy
  from botorch.utils.datasets import SupervisedDataset
  from botorch.utils.multi_objective.pareto import is_non_dominated
  from torch import Tensor
  from torch.quasirandom import SobolEngine
label_desc: Use image node_id 2 for calling a global function with example usage: clamp_candidates(X, target_point, clamp_tol) and returns: X