def METHOD_NAME(model, dataset, request):
    model = request.getfixturevalue(model)
    dataset = request.getfixturevalue(dataset)
    actual_dataset = Dataset(df=dataset.df.head(100),
                             target=dataset.target,
                             column_types=dataset.column_types)
    reference_dataset = Dataset(df=dataset.df.tail(100),
                                target=dataset.target,
                                column_types=dataset.column_types)
    result_actual = test_f1(model, actual_dataset, debug=True).execute()
    result_reference = test_f1(model, reference_dataset, debug=True).execute()
    benchmark_failed = pd.concat([result_actual.output_df.df,
                                  result_reference.output_df.df], ignore_index=True)
    benchmark_failed_len = len(benchmark_failed)
    result = test_diff_f1(model, actual_dataset, reference_dataset, debug=True, threshold=0.01).execute()
    assert len(result.output_df.df) == benchmark_failed_len
    result = test_diff_accuracy(model, actual_dataset, reference_dataset, debug=True, threshold=0.01).execute()
    assert len(result.output_df.df) == benchmark_failed_len
    result = test_diff_recall(model, actual_dataset, reference_dataset, debug=True, threshold=0.01).execute()
    assert len(result.output_df.df) == benchmark_failed_len
    result = test_diff_precision(model, actual_dataset, reference_dataset, debug=True, threshold=0.01).execute()
    assert len(result.output_df.df) == benchmark_failed_len