code: def test_benchmark_silverkite_template_with_real_data():
      # setting every list to 1 item to speed up test case
      forecast_horizons = [30]
      max_cvs = [3]
      fit_algorithms = ["linear"]
      metric = EvaluationMetricEnum.MeanSquaredError
      evaluation_metric = EvaluationMetricParam(
          cv_selection_metric=metric.name
      )
  
      # real data
      dl = DataLoader()
      data_path = dl.get_data_home(data_sub_dir="daily")
      data_name = "daily_female_births"
      df = dl.get_df(
          data_path=data_path, data_name="daily_female_births"
      )
      time_col = "Date"
      value_col = "Births"
      metadata = MetadataParam(
          time_col=time_col, value_col=value_col, freq="D"
      )
      result_silverkite_real = benchmark_silverkite_template(
          data_name=data_name,
          df=df,
          metadata=metadata,
          evaluation_metric=evaluation_metric,
          forecast_horizons=forecast_horizons,
          fit_algorithms=fit_algorithms,
          max_cvs=max_cvs,
      )
  
      result_silverkite_real = result_silverkite_real[0]
      assert result_silverkite_real["data_name"] == data_name
      assert (
          result_silverkite_real["forecast_model_name"]
          == "silverkite_linear"
      )
      assert result_silverkite_real["train_period"] == df.shape[0]
      assert result_silverkite_real["forecast_horizon"] == 30
      assert result_silverkite_real["cv_folds"] == 3
  
file_path: greykite/greykite/tests/framework/benchmark/test_benchmark_template.py
imports: import os
  from greykite.common.data_loader import DataLoader
  from greykite.common.evaluation import EvaluationMetricEnum
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.framework.benchmark.benchmark_template import benchmark_silverkite_template
  from greykite.framework.benchmark.benchmark_template import get_default_benchmark_parameters
  from greykite.framework.benchmark.benchmark_template import get_default_benchmark_real_datasets
  from greykite.framework.benchmark.benchmark_template import get_default_benchmark_silverkite_parameters
  from greykite.framework.benchmark.benchmark_template import get_default_benchmark_simulated_datasets
  from greykite.framework.templates.autogen.forecast_config import EvaluationMetricParam
  from greykite.framework.templates.autogen.forecast_config import MetadataParam
label_desc: Use image node_id 2 for calling a global function with example usage: test_benchmark_silverkite_template_with_real_data() without return types