code: def test_column_wise_clamp_tensors(self):
      X, X_expected = self.X, self.X_expected
      with self.assertRaises(ValueError):
          X_clmp = columnwise_clamp(X, torch.ones(2), torch.zeros(2))
      with self.assertRaises(RuntimeError):
          X_clmp = columnwise_clamp(X, torch.zeros(3), torch.ones(3))
      X_clmp = columnwise_clamp(
          X, torch.tensor([-1, -1]), torch.tensor([0.5, 0.5])
      )
      self.assertTrue(torch.equal(X_clmp, X_expected))
      X_clmp = columnwise_clamp(
          X, torch.tensor([-3, -3]), torch.tensor([3, 3])
      )
      self.assertTrue(torch.equal(X_clmp, X))
  
imports: from __future__ import annotations
  import warnings
  import torch
  from botorch import settings
  from botorch.acquisition.fixed_feature import FixedFeatureAcquisitionFunction
  from botorch.acquisition.monte_carlo import qExpectedImprovement, qNoisyExpectedImprovement
  from botorch.acquisition.multi_objective.max_value_entropy_search import qMultiObjectiveMaxValueEntropy
  from botorch.acquisition.multi_objective.monte_carlo import qExpectedHypervolumeImprovement, qNoisyExpectedHypervolumeImprovement
  from botorch.exceptions import BotorchError
  from botorch.exceptions.warnings import BotorchWarning
  from botorch.models import ModelListGP, SingleTaskGP
  from botorch.models.transforms.input import Warp
  from botorch.optim.utils import columnwise_clamp, fix_features, get_X_baseline
  from botorch.sampling.normal import IIDNormalSampler
  from botorch.utils.multi_objective.box_decompositions.non_dominated import FastNondominatedPartitioning
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
label_desc: Use image node_id 4 for calling the TestColumnWiseClamp obj's underlying member method code with example usage: obj.test_column_wise_clamp_tensors() without return types