def METHOD_NAME(data_loader):
    """Test orchestration."""
    data = data_loader(return_X_y=False)
    dataset = RAMDataset(dataset=data, name="data")
    task = TSCTask(target="class_val")
    # create strategies
    # clf = TimeSeriesForestClassifier(n_estimators=1, random_state=1)
    clf = make_reduction_pipeline(
        RandomForestClassifier(n_estimators=2, random_state=1)
    )
    strategy = TSCStrategy(clf)
    # result backend
    results = RAMResults()
    orchestrator = Orchestrator(
        datasets=[dataset],
        tasks=[task],
        strategies=[strategy],
        cv=SingleSplit(random_state=1),
        results=results,
    )
    orchestrator.fit_predict(save_fitted_strategies=False)
    result = next(results.load_predictions(cv_fold=0, train_or_test="test"))  # get
    # only first item of iterator
    actual = result.y_pred
    # expected output
    task = TSCTask(target="class_val")
    cv = SingleSplit(random_state=1)
    train_idx, test_idx = next(cv.split(data))
    train = data.iloc[train_idx, :]
    test = data.iloc[test_idx, :]
    strategy.fit(task, train)
    expected = strategy.predict(test)
    # compare results
    np.testing.assert_array_equal(actual, expected)