code: def test_create_train_X_y_ValueError_when_lags_keys_not_in_series():
      """
      Test ValueError is raised when lags keys are not in series column names.
      """
      series = pd.DataFrame(
          {
              "l1": pd.Series(np.arange(10)),
              "l2": pd.Series(np.arange(10)),
          }
      )
      forecaster = ForecasterAutoregMultiVariate(
          LinearRegression(),
          level="l1",
          lags={"l1": 2, "2": 3},
          steps=2,
      )
  
      series_col_names = list(series.columns)
  
      err_msg = re.escape(
          (
              f"When `lags` parameter is a `dict`, its keys must be the "
              f"same as `series` column names.\n"
              f"    Lags keys        : {list(forecaster.lags_.keys())}.\n"
              f"    `series` columns : {series_col_names}."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.create_train_X_y(series=series)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiVariate import ForecasterAutoregMultiVariate
  from skforecast.exceptions import MissingValuesExogWarning
  from sklearn.linear_model import LinearRegression
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
label_desc: Use image node_id 5 for calling a global function with example usage: test_create_train_X_y_ValueError_when_lags_keys_not_in_series() without return types