code: def test_predict_ValueError_when_ForecasterSarimax_last_window_exog_is_not_None_and_last_window_is_not_provided():
      """
      Check ValueError is raised when last_window_exog is not None, but
      last_window is not provided.
      """
      forecaster = ForecasterSarimax(regressor=Sarimax(order=(1, 1, 1)))
      forecaster.fit(y=y, exog=exog)
  
      err_msg = re.escape(
          (
              "To make predictions unrelated to the original data, both "
              "`last_window` and `last_window_exog` must be provided."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.predict(
              steps=5,
              exog=exog_predict,
              last_window=None,
              last_window_exog=exog,
          )
  
imports: import re
  import pytest
  import platform
  import pandas
  from sklearn.exceptions import NotFittedError
  from pmdarima.arima import ARIMA
  from skforecast.Sarimax import Sarimax
  from skforecast.ForecasterSarimax import ForecasterSarimax
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from .fixtures_ForecasterSarimax import y
  from .fixtures_ForecasterSarimax import y_lw
  from .fixtures_ForecasterSarimax import exog
  from .fixtures_ForecasterSarimax import exog_lw
  from .fixtures_ForecasterSarimax import exog_predict
  from .fixtures_ForecasterSarimax import exog_lw_predict
  from .fixtures_ForecasterSarimax import y_datetime
  from .fixtures_ForecasterSarimax import y_lw_datetime
  from .fixtures_ForecasterSarimax import exog_datetime
  from .fixtures_ForecasterSarimax import exog_lw_datetime
  from .fixtures_ForecasterSarimax import exog_predict_datetime
  from .fixtures_ForecasterSarimax import exog_lw_predict_datetime
  from .fixtures_ForecasterSarimax import df_exog
  from .fixtures_ForecasterSarimax import df_exog_lw
  from .fixtures_ForecasterSarimax import df_exog_predict
  from .fixtures_ForecasterSarimax import df_exog_lw_predict
  from .fixtures_ForecasterSarimax import df_exog_datetime
  from .fixtures_ForecasterSarimax import df_exog_lw_datetime
  from .fixtures_ForecasterSarimax import df_exog_predict_datetime
  from .fixtures_ForecasterSarimax import df_exog_lw_predict_datetime
label_desc: Use image node_id 2 for calling a global function with example usage: test_predict_ValueError_when_ForecasterSarimax_last_window_exog_is_not_None_and_last_window_is_not_provided() without return types