code: def test_split_fantasy_points(self):
      for dtype in (torch.float, torch.double):
          X = torch.randn(5, 3, device=self.device, dtype=dtype)
          # test error when passing inconsistent n_f
          with self.assertRaises(ValueError):
              _split_fantasy_points(X, n_f=6)
          # basic test
          X_actual, X_fantasies = _split_fantasy_points(X=X, n_f=2)
          self.assertEqual(X_actual.shape, torch.Size([3, 3]))
          self.assertEqual(X_fantasies.shape, torch.Size([2, 1, 3]))
          self.assertTrue(torch.equal(X_actual, X[:3, :]))
          self.assertTrue(
              torch.equal(X_fantasies, X[3:, :].unsqueeze(-2))
          )
          # batched test
          X = torch.randn(2, 5, 3, device=self.device, dtype=dtype)
          X_actual, X_fantasies = _split_fantasy_points(X=X, n_f=2)
          self.assertEqual(X_actual.shape, torch.Size([2, 3, 3]))
          self.assertEqual(X_fantasies.shape, torch.Size([2, 2, 1, 3]))
          self.assertTrue(torch.equal(X_actual, X[..., :3, :]))
          X_fantasies_exp = (
              X[..., 3:, :].unsqueeze(-2).permute(1, 0, 2, 3)
          )
          self.assertTrue(torch.equal(X_fantasies, X_fantasies_exp))
  
imports: from contextlib import ExitStack
  from unittest import mock
  import torch
  from botorch.acquisition.analytic import PosteriorMean, ScalarizedPosteriorMean
  from botorch.acquisition.cost_aware import GenericCostAwareUtility
  from botorch.acquisition.knowledge_gradient import _get_value_function, _split_fantasy_points, ProjectedAcquisitionFunction, qKnowledgeGradient, qMultiFidelityKnowledgeGradient
  from botorch.acquisition.monte_carlo import qExpectedImprovement, qSimpleRegret
  from botorch.acquisition.objective import GenericMCObjective, ScalarizedPosteriorTransform
  from botorch.acquisition.utils import project_to_sample_points
  from botorch.exceptions.errors import UnsupportedError
  from botorch.generation.gen import gen_candidates_scipy
  from botorch.models import SingleTaskGP
  from botorch.optim.optimize import optimize_acqf
  from botorch.optim.utils import _filter_kwargs
  from botorch.posteriors.gpytorch import GPyTorchPosterior
  from botorch.sampling.normal import IIDNormalSampler, SobolQMCNormalSampler
  from botorch.utils.test_helpers import DummyNonScalarizingPosteriorTransform
  from botorch.utils.testing import BotorchTestCase, MockModel, MockPosterior
  from gpytorch.distributions import MultitaskMultivariateNormal
label_desc: Use image node_id 2 for calling the TestKGUtils obj's underlying member method code with example usage: obj.test_split_fantasy_points() without return types