code: def test_normalize_indices(self):
      self.assertIsNone(normalize_indices(None, 3))
      indices = [0, 2]
      nlzd_indices = normalize_indices(indices, 3)
      self.assertEqual(nlzd_indices, indices)
      nlzd_indices = normalize_indices(indices, 4)
      self.assertEqual(nlzd_indices, indices)
      indices = [0, -1]
      nlzd_indices = normalize_indices(indices, 3)
      self.assertEqual(nlzd_indices, [0, 2])
      with self.assertRaises(ValueError):
          nlzd_indices = normalize_indices([3], 3)
      with self.assertRaises(ValueError):
          nlzd_indices = normalize_indices([-4], 3)
  
imports: from typing import Any
  import torch
  from botorch.models import GenericDeterministicModel, HigherOrderGP, ModelList, PairwiseGP, SaasFullyBayesianSingleTaskGP, SingleTaskGP
  from botorch.models.fully_bayesian_multitask import SaasFullyBayesianMultiTaskGP
  from botorch.models.gp_regression_fidelity import SingleTaskMultiFidelityGP
  from botorch.models.gp_regression_mixed import MixedSingleTaskGP
  from botorch.models.model import Model
  from botorch.models.multitask import MultiTaskGP
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
  from botorch.utils.transforms import _verify_output_shape, concatenate_pending_points, is_ensemble, is_fully_bayesian, match_batch_shape, normalize, normalize_indices, standardize, t_batch_mode_transform, unnormalize
  from torch import Tensor
label_desc: Use image node_id 1 for calling the TorchNormalizeIndices obj's underlying member method code with example usage: obj.test_normalize_indices() without return types