code: def test_check_predict_input_ValueError_when_last_step_greater_than_max_steps():
      """
      Test ValueError is raised when max(steps) > max_steps. (`ForecasterAutoregDirect`
      and `ForecasterAutoregMultiVariate`).
      """
      steps = list(np.arange(20) + 1)
      max_steps = 10
  
      err_msg = re.escape(
          (
              f"The maximum value of `steps` must be less than or equal to "
              f"the value of steps defined when initializing the forecaster. "
              f"Got {max(steps)}, but the maximum is {max_steps}."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          check_predict_input(
              forecaster_name="ForecasterAutoregMultiVariate",
              steps=steps,
              fitted=True,
              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=max_steps,
              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 4 for calling a global function with example usage: test_check_predict_input_ValueError_when_last_step_greater_than_max_steps() without return types