code: def test_time_trend_smoke(index, forecast_index):
      tt = TimeTrend(True, 2)
      tt.in_sample(index)
      steps = 83 if forecast_index is None else len(forecast_index)
      warn = None
      if (
          is_int_index(index)
          and np.any(np.diff(index) != 1)
          or (
              type(index) is pd.Index
              and max(index) > 2**63
              and forecast_index is None
          )
      ):
          warn = UserWarning
      with pytest_warns(warn):
          tt.out_of_sample(steps, index, forecast_index)
      str(tt)
      hash(tt)
      assert isinstance(tt.order, int)
      assert isinstance(tt._constant, bool)
      assert TimeTrend.from_string("ctt") == tt
      assert TimeTrend.from_string("ct") != tt
      assert TimeTrend.from_string("t") != tt
      assert TimeTrend.from_string("n") != tt
      assert Seasonality(12) != tt
      tt0 = TimeTrend(False, 0)
      tt0.in_sample(index)
      str(tt0)
  
imports: from statsmodels.compat.pandas import MONTH_END, PD_LT_1_0_0, QUARTER_END, YEAR_END, is_int_index
  from statsmodels.compat.pytest import pytest_warns
  from collections.abc import Hashable
  import numpy
  import pandas
  import pytest
  from statsmodels.tsa.deterministic import CalendarFourier, CalendarSeasonality, CalendarTimeTrend, DeterministicProcess, DeterministicTerm, Fourier, Seasonality, TimeTrend
label_desc: Use image node_id 4 for calling a global function with example usage: test_time_trend_smoke(index, forecast_index) without return types