code: def df():
      df = generate_df_for_tests(
          freq="H",
          periods=24 * 7 * 8,
          train_start_date=datetime.datetime(2018, 1, 1),
          conti_year_origin=2018,
      )["df"]
      df["regressor"] = np.arange(len(df))
      return df
  
imports: import datetime
  import numpy
  import pytest
  from testfixtures import LogCapture
  from greykite.common.constants import LOGGER_NAME
  from greykite.common.constants import PREDICTED_COL
  from greykite.common.constants import PREDICTED_LOWER_COL
  from greykite.common.constants import PREDICTED_UPPER_COL
  from greykite.common.constants import TIME_COL
  from greykite.common.constants import VALUE_COL
  from greykite.common.testing_utils import generate_df_for_tests
  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 MetadataParam
  from greykite.framework.templates.autogen.forecast_config import ModelComponentsParam
  from greykite.framework.templates.forecaster import Forecaster
  from greykite.framework.templates.multistage_forecast_template import MultistageForecastTemplate
  from greykite.framework.templates.multistage_forecast_template_config import SILVERKITE_TWO_STAGE
  from greykite.framework.templates.multistage_forecast_template_config import MultistageForecastTemplateConfig
  from greykite.framework.templates.simple_silverkite_template import SimpleSilverkiteTemplate
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
  from greykite.sklearn.uncertainty.uncertainty_methods import UncertaintyMethodEnum
label_desc: Use image node_id 1 for calling a global function with example usage: df() and returns: df