code: def test_trial_dataclass_can_store_and_contains_retrain_split():
      tc: TrialDataclass = TrialDataclass(trial_number=5)
      tc.store(TrialSplitDataclass(split_number=0))
      tc.store(TrialSplitDataclass(split_number=1))
      tc.store(TrialSplitDataclass(split_number=2))
      sl: ScopedLocation = ScopedLocation.default(
          round_number=0,
          trial_number=5,
          split_number=RETRAIN_TRIAL_SPLIT_ID,
      )
      tsc: TrialSplitDataclass = TrialSplitDataclass(
          split_number=RETRAIN_TRIAL_SPLIT_ID
      )
  
      tc.store(tsc)
  
      assert len(tc) == 3
      assert sl in tc
      assert tsc.get_id() == RETRAIN_TRIAL_SPLIT_ID
      assert tc.retrained_split == tsc
      assert tc[sl] == tc.retrained_split
  
file_path: Neuraxle/testing_neuraxle/metaopt/test_automl_dataclasses.py
imports: import copy
  from typing import List, Type
  import pytest
  from neuraxle.base import TrialStatus
  from neuraxle.hyperparams.space import HyperparameterSamples
  from neuraxle.metaopt.data.vanilla import DEFAULT_CLIENT, DEFAULT_PROJECT, NULL_CLIENT, NULL_PROJECT, NULL_ROUND, NULL_TRIAL, NULL_TRIAL_SPLIT, RETRAIN_TRIAL_SPLIT_ID, BaseDataclass, ClientDataclass, MetricResultsDataclass, ProjectDataclass, RootDataclass, RoundDataclass, ScopedLocation, TrialDataclass, TrialSplitDataclass, as_named_odict, dataclass_2_id_attr, from_json, to_json
label_desc: Use image node_id 7 for calling a global function with example usage: test_trial_dataclass_can_store_and_contains_retrain_split() without return types