code: def test_check_predict_input_TypeError_when_exog_is_not_pandas_series_or_dataframe():
      """ """
      err_msg = re.escape(
          "`exog` must be a pandas Series or DataFrame."
      )
      with pytest.raises(TypeError, match=err_msg):
          check_predict_input(
              forecaster_name="ForecasterAutoreg",
              steps=10,
              fitted=True,
              included_exog=True,
              index_type=pd.DatetimeIndex,
              index_freq="M",
              window_size=5,
              last_window=pd.Series(
                  np.arange(10),
                  index=pd.date_range(
                      start="1/1/2018", periods=10, freq="M"
                  ),
              ),
              last_window_exog=None,
              exog=np.arange(10),
              exog_type=None,
              exog_col_names=None,
              interval=None,
              alpha=None,
              max_steps=None,
              levels=None,
              series_col_names=None,
          )
  
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.exceptions import NotFittedError
  from skforecast.utils import check_predict_input
  from skforecast.utils import check_exog
  from skforecast.utils import preprocess_exog
  from skforecast.utils import preprocess_last_window
  from skforecast.exceptions import MissingValuesExogWarning
label_desc: Use image node_id 17 for calling a global function with example usage: test_check_predict_input_TypeError_when_exog_is_not_pandas_series_or_dataframe() without return types