code: def test_set_params():
      """Test set_params."""
      params = {"trend": "additive"}
  
      f = ExponentialSmoothing(**params)
      f.fit(y_train, fh=1)
      expected = f.predict()
  
      f = ExponentialSmoothing()
      f.set_params(**params)
      f.fit(y_train, fh=1)
      y_pred = f.predict()
  
      assert_array_equal(y_pred, expected)
  
file_path: sktime/sktime/forecasting/tests/test_exp_smoothing.py
imports: import pandas
  import pytest
  from numpy.testing import assert_array_equal
  from sktime.datasets import load_airline
  from sktime.forecasting.exp_smoothing import ExponentialSmoothing
  from sktime.split import temporal_train_test_split
  from sktime.utils._testing.forecasting import make_forecasting_problem
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 1 for calling a global function with example usage: test_set_params() without return types