code: def test_auto_config():
      df = DataLoader().load_peyton_manning()
      df[cst.TIME_COL] = pd.to_datetime(df[cst.TIME_COL])
      model = SimpleSilverkiteEstimator(
          forecast_horizon=7,
          auto_holiday=True,
          holidays_to_model_separately=["custom_event"],
          holiday_lookup_countries="auto",
          holiday_pre_num_days=0,
          holiday_post_num_days=0,
          daily_event_df_dict=dict(
              custom_event=pd.DataFrame(
                  {
                      EVENT_DF_DATE_COL: pd.to_datetime(
                          ["2010-03-03", "2011-03-03", "2012-03-03"]
                      ),
                      EVENT_DF_LABEL_COL: "threethree",
                  }
              )
          ),
          auto_holiday_params=dict(n_clusters=5),
          auto_growth=True,
          growth_term="quadratic",
          changepoints_dict=dict(method="uniform", n_changepoints=2),
          auto_seasonality=True,
          yearly_seasonality=0,
          quarterly_seasonality="auto",
          monthly_seasonality=False,
          weekly_seasonality=True,
          daily_seasonality=5,
      )
      model.fit(X=df, time_col=cst.TIME_COL, value_col=cst.VALUE_COL)
      # Seasonality is overridden by auto seasonality.
      assert model.model_dict["fs_components_df"][
          ["name", "period", "order", "seas_names"]
      ].equals(
          pd.DataFrame(
              {
                  "name": ["tow", "toq", "ct1"],
                  "period": [7.0, 1.0, 1.0],
                  "order": [3, 1, 6],
                  "seas_names": ["weekly", "quarterly", "yearly"],
              }
          )
      )
      # Growth is overridden by auto growth.
      assert "ct1" in model.model_dict["x_mat"].columns
      assert model.model_dict["changepoints_dict"]["method"] == "custom"
      # Holidays is overridden by auto seasonality.
      assert len(model.model_dict["daily_event_df_dict"]) == 6
      assert "custom_event" in model.model_dict["daily_event_df_dict"]
      assert (
          "holiday_group_0" in model.model_dict["daily_event_df_dict"]
      )
  
imports: import datetime
  import numpy
  import pandas
  import pytest
  from pandas.testing import assert_frame_equal
  from sklearn.linear_model import SGDRegressor
  from sklearn.metrics import mean_squared_error
  import greykite.common.constants
  from greykite.algo.forecast.silverkite.forecast_simple_silverkite import SimpleSilverkiteForecast
  from greykite.common.constants import EVENT_DF_DATE_COL
  from greykite.common.constants import EVENT_DF_LABEL_COL
  from greykite.common.data_loader import DataLoader
  from greykite.common.features.timeseries_features import convert_date_to_continuous_time
  from greykite.common.python_utils import assert_equal
  from greykite.common.testing_utils import daily_data_reg
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.common.testing_utils import generate_df_with_reg_for_tests
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
  from greykite.sklearn.estimator.testing_utils import params_component_breakdowns
label_desc: Use image node_id 18 for calling a global function with example usage: test_auto_config() without return types