code: def test_check_predict_input_NotFittedError_when_fitted_is_False():
      """
      Test NotFittedError is raised when fitted is False.
      """
      err_msg = re.escape(
          (
              "This Forecaster instance is not fitted yet. Call `fit` with "
              "appropriate arguments before using predict."
          )
      )
      with pytest.raises(NotFittedError, match=err_msg):
          check_predict_input(
              forecaster_name="ForecasterAutoreg",
              steps=5,
              fitted=False,
              included_exog=False,
              index_type=None,
              index_freq=None,
              window_size=None,
              last_window=None,
              last_window_exog=None,
              exog=None,
              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 1 for calling a global function with example usage: test_check_predict_input_NotFittedError_when_fitted_is_False() without return types