code: def _prepareTrials(self, scheduler, base_pgf):
      t1, t2, t3, t4 = super()._prepareTrials(scheduler, base_pgf)
      t1.run_metadata.last_result = {
          "metric": 1,
          "training_iteration": 3,
      }
      t2.run_metadata.last_result = {
          "metric": 0.9,
          "training_iteration": 3,
      }
      t3.run_metadata.last_result = {
          "metric": 0.8,
          "training_iteration": 3,
      }
      t4.run_metadata.last_result = {
          "metric": 0.7,
          "training_iteration": 3,
      }
      return t1, t2, t3, t4
  
imports: import shutil
  import tempfile
  import unittest
  from ray.tune import PlacementGroupFactory
  from ray.tune.execution.tune_controller import TuneController
  from ray.tune.schedulers.trial_scheduler import TrialScheduler
  from ray.tune.experiment import Trial
  from ray.tune.schedulers.resource_changing_scheduler import ResourceChangingScheduler, DistributeResources, DistributeResourcesToTopJob
  from ray.tune.tests.execution.utils import create_execution_test_objects
  from ray.train.tests.util import mock_storage_context
label_desc: Use image node_id 1 for calling the TestTopJobResourceAllocation obj's underlying member method code with example usage: obj._prepareTrials(scheduler, base_pgf) and returns: t1,  t2,  t3,  t4