code: def test_filter_train_X_y_for_step_exception_when_step_not_in_steps(
      step,
  ):
      """
      Test exception is raised when step not in steps.
      """
      series = pd.DataFrame(
          {
              "l1": pd.Series(np.arange(10), dtype=float),
              "l2": pd.Series(np.arange(100, 110), dtype=float),
          }
      )
  
      forecaster = ForecasterAutoregMultiVariate(
          LinearRegression(), level="l1", lags=3, steps=3
      )
      X_train, y_train = forecaster.create_train_X_y(series=series)
  
      err_msg = re.escape(
          (
              f"Invalid value `step`. For this forecaster, minimum value is 1 "
              f"and the maximum step is {forecaster.steps}."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.filter_train_X_y_for_step(
              step=step, X_train=X_train, y_train=y_train
          )
  
file_path: skforecast/skforecast/ForecasterAutoregMultiVariate/tests/test_filter_train_X_y_for_step.py
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiVariate import ForecasterAutoregMultiVariate
  from sklearn.linear_model import LinearRegression
label_desc: Use image node_id 1 for calling a global function with example usage: test_filter_train_X_y_for_step_exception_when_step_not_in_steps(step) without return types