code: def setUp(self) -> None:
      super().setUp()
      self.mlls = {}
      with torch.random.fork_rng():
          torch.manual_seed(0)
          train_X = torch.linspace(0, 1, 10).unsqueeze(-1)
          train_Y = torch.sin((2 * math.pi) * train_X)
          train_Y = train_Y + 0.1 * torch.randn_like(train_Y)
  
      model = SingleTaskGP(
          train_X=train_X,
          train_Y=train_Y,
          input_transform=Normalize(d=1),
          outcome_transform=Standardize(m=1),
      )
      self.mlls[SingleTaskGP, 1] = ExactMarginalLogLikelihood(
          model.likelihood, model
      )
  
imports: import math
  from unittest.mock import MagicMock, patch
  from warnings import catch_warnings
  import torch
  from botorch.exceptions.warnings import OptimizationWarning
  from botorch.models import SingleTaskGP
  from botorch.models.transforms.input import Normalize
  from botorch.models.transforms.outcome import Standardize
  from botorch.optim import core, fit
  from botorch.optim.core import OptimizationResult
  from botorch.settings import debug
  from botorch.utils.context_managers import module_rollback_ctx, TensorCheckpoint
  from botorch.utils.testing import BotorchTestCase
  from gpytorch.mlls.exact_marginal_log_likelihood import ExactMarginalLogLikelihood
  from scipy.optimize import OptimizeResult
label_desc: Use image node_id 1 for calling the TestFitGPyTorchMLLScipy obj's underlying member method code with example usage: obj.setUp() without return types