code: def test_outcome_untransformer(self):
      for untransformer in (
          OutcomeUntransformer(
              transform=Standardize(m=1), num_outputs=1
          ),
          OutcomeUntransformer(
              transform=Standardize(m=2), num_outputs=2
          ),
      ):
          with torch.random.fork_rng():
              torch.random.manual_seed(0)
              y = torch.rand(
                  untransformer.num_outputs, 4, device=self.device
              )
          x = untransformer.transform(y.T)[0].T
          self.assertTrue(y.allclose(untransformer(x)))
  
imports: from __future__ import annotations
  from unittest.mock import patch
  import torch
  from botorch.models import SingleTaskGP, SingleTaskVariationalGP
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.models.transforms.input import Normalize
  from botorch.models.transforms.outcome import Standardize
  from botorch.sampling.pathwise.utils import get_input_transform, get_output_transform, get_train_inputs, get_train_targets, InverseLengthscaleTransform, OutcomeUntransformer
  from botorch.utils.context_managers import delattr_ctx
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.kernels import MaternKernel, ScaleKernel
label_desc: Use image node_id 2 for calling the TestTransforms obj's underlying member method code with example usage: obj.test_outcome_untransformer() without return types