class_docstr: A dummy deterministic model that uses transforms.
code: def forward(self, X):
      # just a non-linear objective that is sure to break without transforms
      return (X - 1.0).pow(2).sum(dim=-1, keepdim=True) - 5.0
  
imports: import warnings
  import torch
  from botorch.acquisition.objective import ScalarizedPosteriorTransform
  from botorch.exceptions.errors import UnsupportedError
  from botorch.models.deterministic import AffineDeterministicModel, DeterministicModel, FixedSingleSampleModel, GenericDeterministicModel, PosteriorMeanModel
  from botorch.models.gp_regression import SingleTaskGP
  from botorch.models.transforms.input import Normalize
  from botorch.models.transforms.outcome import Standardize
  from botorch.posteriors.ensemble import EnsemblePosterior
  from botorch.utils.testing import BotorchTestCase
label_desc: Use image node_id 2 for calling the DummyDeterministicModel obj's underlying member method code with example usage: obj.forward(X) and returns: unknown