code: def test_smoke(
      data, period, use_mle, deseasonalize, use_test, diff, model
  ):
      if period is None and isinstance(data, np.ndarray):
          return
      res = ThetaModel(
          data,
          period=period,
          deseasonalize=deseasonalize,
          use_test=use_test,
          difference=diff,
          method=model,
      ).fit(use_mle=use_mle)
      assert "b0" in str(res.summary())
      res.forecast(36)
      res.forecast_components(47)
      assert res.model.use_test is (
          use_test and res.model.deseasonalize
      )
      assert res.model.difference is diff
  
file_path: statsmodels/statsmodels/tsa/forecasting/tests/test_theta.py
imports: from itertools import product
  import numpy
  import pandas
  import pytest
  from statsmodels.tsa.forecasting.theta import ThetaModel
label_desc: Use image node_id 3 for calling a global function with example usage: test_smoke(data, period, use_mle, deseasonalize, use_test, diff, model) without return types