code: def get_default_benchmark_simulated_datasets():
      """Default parameter sets to generate simulated data for benchmarking.
      The training periods and forecast horizon are chosen to complement default real datasets.
      Every tuple has the following structure:
      (data_name, frequency, training_periods, forecast_horizon)"""
      simulation_parameters = [
          # daily data
          ("daily_simulated", "D", 3 * 30, [30]),
          ("daily_simulated", "D", 2 * 365, [365]),
          # hourly data
          ("hourly_simulated", "H", 7 * 24, [24]),
          ("hourly_simulated", "H", 30 * 24, [7 * 24]),
          ("hourly_simulated", "H", 365 * 24, [6 * 30 * 24]),
          ("hourly_simulated", "H", 4 * 365 * 24, [365 * 24]),
      ]
  
      return simulation_parameters
  
file_path: greykite/greykite/framework/benchmark/benchmark_template.py
imports: import itertools
  import os
  import timeit
  from pathlib import Path
  from greykite.common.evaluation import EvaluationMetricEnum
  from greykite.framework.templates.autogen.forecast_config import EvaluationPeriodParam
  from greykite.framework.templates.autogen.forecast_config import ForecastConfig
  from greykite.framework.templates.autogen.forecast_config import ModelComponentsParam
  from greykite.framework.templates.forecaster import Forecaster
  from greykite.framework.templates.model_templates import ModelTemplateEnum
label_desc: Use image node_id 5 for calling a global function with example usage: get_default_benchmark_simulated_datasets() and returns: simulation_parameters