code: def test_set_params():
      model = OneByOneEstimator(
          estimator="SimpleSilverkiteEstimator",
          forecast_horizon=3,
          estimator_map=1,
          estimator_params={
              "autoreg_dict": "auto",
              "yearly_seasonality": 2,
              "feature_sets_enabled": False,
          },
      )
      assert model.estimator_map == 1
      assert model.estimator_params["yearly_seasonality"] == 2
      assert model.estimator_params.get("daily_seasonality") is None
  
      model.set_params(
          **{
              "estimator_map": 2,
              "yearly_seasonality": 4,
              "daily_seasonality": 2,
          }
      )
      assert model.estimator_map == 2
      assert model.estimator_params["yearly_seasonality"] == 4
      assert model.estimator_params["daily_seasonality"] == 2
  
      assert set(model.estimator_param_names) == set(
          SimpleSilverkiteEstimator().get_params().keys()
      )
  
      with pytest.raises(
          ValueError,
          match=r"Invalid parameter some_param for estimator OneByOneEstimator. "
          r"Check the list of available parameters with "
          r"`estimator.get\_params\(\).keys\(\)`.",
      ):
          model.set_params(**{"some_param": 5})
  
file_path: greykite/greykite/tests/sklearn/estimator/test_one_by_one_estimator.py
imports: import datetime
  import sys
  import pandas
  import pytest
  from sklearn.metrics import mean_squared_error
  import greykite.common.constants
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.sklearn.estimator.one_by_one_estimator import OneByOneEstimator
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
label_desc: Use image node_id 6 for calling a global function with example usage: test_set_params() without return types