code: def test_get_training_data(self) -> None:
      class FakeStrategy(ModelBasedEarlyStoppingStrategy):
          def should_stop_trials_early(
              self,
              trial_indices: Set[int],
              experiment: Experiment,
              **kwargs: Dict[str, Any],
          ) -> Dict[int, Optional[str]]:
              return {}
  
      experiment = get_test_map_data_experiment(
          num_trials=3, num_fetches=2, num_complete=3
      )
      training_data = FakeStrategy().get_training_data(
          experiment,
          # pyre-fixme[6]: For 2nd param expected `MapData` but got `Data`.
          map_data=experiment.lookup_data(),
      )
      # check that there is a map dimension in the training data
      X = training_data.X
      self.assertEqual(X.shape[-1], 3)
      # check that the default Ax transform is applied, i.e., that the
      # parameters are normalized to [0, 1]
      self.assertTrue(np.all((X[:, :2] >= 0.0) & (X[:, :2] <= 1.0)))
  
imports: from typing import Any, Dict, Optional, Set
  import numpy
  import pandas
  from ax.core.base_trial import TrialStatus
  from ax.core.experiment import Experiment
  from ax.core.map_data import MapData
  from ax.early_stopping.strategies import BaseEarlyStoppingStrategy, ModelBasedEarlyStoppingStrategy, PercentileEarlyStoppingStrategy, ThresholdEarlyStoppingStrategy
  from ax.early_stopping.strategies.logical import AndEarlyStoppingStrategy, OrEarlyStoppingStrategy
  from ax.early_stopping.utils import align_partial_results
  from ax.exceptions.core import UnsupportedError
  from ax.utils.common.testutils import TestCase
  from ax.utils.common.typeutils import checked_cast
  from ax.utils.testing.core_stubs import get_branin_arms, get_branin_experiment, get_branin_experiment_with_timestamp_map_metric, get_experiment_with_multi_objective, get_test_map_data_experiment
  from pyre_extensions import none_throws
label_desc: Use image node_id 1 for calling the TestModelBasedEarlyStoppingStrategy obj's underlying member method code with example usage: obj.test_get_training_data() and returns: dict