code: def test_FixedSingleSampleModel(self):
      torch.manual_seed(123)
      train_X = torch.rand(2, 3)
      train_Y = torch.rand(2, 2)
      model = SingleTaskGP(train_X=train_X, train_Y=train_Y)
      fss_model = FixedSingleSampleModel(model=model)
  
      # test without specifying w and dim
      test_X = torch.rand(2, 3)
      w = fss_model.w
      post = model.posterior(test_X)
      original_output = post.mean + post.variance.sqrt() * w
      fss_output = fss_model(test_X)
      self.assertTrue(torch.equal(original_output, fss_output))
  
      self.assertTrue(hasattr(fss_model, "num_outputs"))
  
      # test specifying w
      w = torch.randn(4)
      fss_model = FixedSingleSampleModel(model=model, w=w)
      self.assertTrue(fss_model.w.shape == w.shape)
      # test dim
      dim = 5
      fss_model = FixedSingleSampleModel(model=model, w=w, dim=dim)
      # dim should be ignored
      self.assertTrue(fss_model.w.shape == w.shape)
      # test dim when no w is provided
      fss_model = FixedSingleSampleModel(model=model, dim=dim)
      # dim should be ignored
      self.assertTrue(fss_model.w.shape == torch.Size([dim]))
  
      # check w dtype conversion
      train_X_double = torch.rand(2, 3, dtype=torch.double)
      train_Y_double = torch.rand(2, 2, dtype=torch.double)
      model_double = SingleTaskGP(
          train_X=train_X_double, train_Y=train_Y_double
      )
      fss_model_double = FixedSingleSampleModel(model=model_double)
      test_X_float = torch.rand(2, 3, dtype=torch.float)
  
      # the following line should execute fine
      fss_model_double.posterior(test_X_float)
  
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 7 for calling the TestDeterministicModels obj's underlying member method code with example usage: obj.test_FixedSingleSampleModel() without return types