code: def test_setup2(params2):
      """Tests __init__ and attributes set during fit"""
      coverage = 0.90
      silverkite = SimpleSilverkiteForecast()
      model = SimpleSilverkiteEstimator(
          silverkite=silverkite,
          score_func=mean_squared_error,
          coverage=coverage,
          null_model_params=None,
          **params2,
      )
  
      assert model.silverkite == silverkite
      assert model.score_func == mean_squared_error
      assert model.coverage == coverage
      assert model.null_model_params is None
  
      # set_params must be able to replicate the init
      model2 = SimpleSilverkiteEstimator()
      model2.set_params(
          **dict(
              silverkite=silverkite,
              score_func=mean_squared_error,
              coverage=coverage,
              null_model_params=None,
              **params2,
          )
      )
      assert model2.__dict__ == model.__dict__
  
      initialized_params = model.__dict__
      initialized_params_subset = {
          k: v
          for k, v in initialized_params.items()
          if k in params2.keys()
      }
      assert_equal(initialized_params_subset, params2)
  
      assert model.model_dict is None
      assert model.pred_cols is None
      assert model.feature_cols is None
      assert model.coef_ is None
  
      train_df = daily_data_reg().get("train_df").copy()
      model.fit(train_df)
      assert model.fit_algorithm_dict == {
          "fit_algorithm": "ridge",
          "fit_algorithm_params": None,
      }
      assert model.model_dict is not None
      assert model.model_dict["training_evaluation"] is not None
      assert model.model_dict["test_evaluation"] is None
      assert model.pred_cols is not None
      assert model.feature_cols is not None
      assert_frame_equal(model.df, train_df)
      assert model.coef_ is not None
  
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 8 for calling a global function with example usage: test_setup2(params2) without return types