code: def test_get_train_inputs(self):
      for model in self.models:
          model.train()
          X = (
              model.model.train_inputs[0]
              if isinstance(model, SingleTaskVariationalGP)
              else model.train_inputs[0]
          )
          Z = model.input_transform(X)
          train_inputs = get_train_inputs(model, transformed=False)
          self.assertIsInstance(train_inputs, tuple)
          self.assertEqual(len(train_inputs), 1)
  
          self.assertTrue(
              X.equal(get_train_inputs(model, transformed=False)[0])
          )
          self.assertTrue(
              Z.equal(get_train_inputs(model, transformed=True)[0])
          )
  
          model.eval()
          self.assertTrue(
              X.equal(get_train_inputs(model, transformed=False)[0])
          )
          self.assertTrue(
              Z.equal(get_train_inputs(model, transformed=True)[0])
          )
          with delattr_ctx(model, "input_transform"), patch.object(
              model, "_original_train_inputs", new=None
          ):
              self.assertTrue(
                  Z.equal(get_train_inputs(model, transformed=False)[0])
              )
              self.assertTrue(
                  Z.equal(get_train_inputs(model, transformed=True)[0])
              )
  
      with self.subTest("test_model_list"):
          model_list = ModelListGP(*self.models)
          input_list = get_train_inputs(model_list)
          self.assertIsInstance(input_list, list)
          self.assertEqual(len(input_list), len(self.models))
          for model, train_inputs in zip(model_list.models, input_list):
              for a, b in zip(train_inputs, get_train_inputs(model)):
                  self.assertTrue(a.equal(b))
  
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 4 for calling the TestGetters obj's underlying member method code with example usage: obj.test_get_train_inputs() without return types