code: def test_multits_holtwinters(seasonal, h, datatype):
      global airpassengers, co2
      airpassengers = np.asarray(airpassengers, dtype=datatype)
      co2 = np.asarray(co2, dtype=datatype)
  
      if seasonal == "multiplicative":
          pytest.xfail(
              "Statsmodels nan errors with gcc 9.3 (Issue #3384)"
          )
  
      air_train = airpassengers[:-h]
      air_test = airpassengers[-h:]
      co2_train = co2[:-h]
      co2_test = co2[-h:]
      data = np.asarray([air_train, co2_train], dtype=datatype)
      cu_hw = cuml_ES(
          data, seasonal=seasonal, seasonal_periods=12, ts_num=2
      )
  
      sm_air_hw = sm_ES(
          air_train,
          initialization_method="heuristic",
          seasonal=seasonal,
          seasonal_periods=12,
      )
      sm_co2_hw = sm_ES(
          co2_train,
          initialization_method="heuristic",
          seasonal=seasonal,
          seasonal_periods=12,
      )
      cu_hw.fit()
      sm_air_hw = sm_air_hw.fit()
      sm_co2_hw = sm_co2_hw.fit()
  
      cu_air_pred = cu_hw.forecast(h, 0)
      cu_co2_pred = cu_hw.forecast(h, 1)
      sm_air_pred = sm_air_hw.forecast(h)
      sm_co2_pred = sm_co2_hw.forecast(h)
  
      cu_air_r2 = r2_score(cu_air_pred.to_numpy(), air_test)
      cu_co2_r2 = r2_score(cu_co2_pred.to_numpy(), co2_test)
      sm_air_r2 = r2_score(sm_air_pred, air_test)
      sm_co2_r2 = r2_score(sm_co2_pred, co2_test)
  
      assert (cu_air_r2 >= sm_air_r2) or (
          abs(cu_air_r2 - sm_air_r2) < 4
      )
      assert (cu_co2_r2 >= sm_co2_r2) or (
          abs(cu_co2_r2 - sm_co2_r2) < 4
      )
  
      full_cu_pred = cu_hw.forecast(h)
      air_cu_r2 = r2_score(full_cu_pred[0].to_numpy(), air_test)
      co2_cu_r2 = r2_score(full_cu_pred[1].to_numpy(), co2_test)
      assert (air_cu_r2 >= sm_air_r2) or (
          abs(air_cu_r2 - sm_air_r2) < 4
      )
      assert (co2_cu_r2 >= sm_co2_r2) or (
          abs(co2_cu_r2 - sm_co2_r2) < 4
      )
  
file_path: cuml/python/cuml/tests/test_holtwinters.py
imports: from sklearn.metrics import r2_score
  from statsmodels.tsa.holtwinters import ExponentialSmoothing
  from cuml.tsa.holtwinters import ExponentialSmoothing
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 2 for calling a global function with example usage: test_multits_holtwinters(seasonal, h, datatype) without return types