code: def test_create_train_X_y_ValueError_when_len_name_predictors_not_match_X_train_columns():
      """
      Test ValueError is raised when argument `name_predictors` has less values than the number of
      columns of X_train.
      """
      series = pd.DataFrame(
          {"1": pd.Series(np.arange(5)), "2": pd.Series(np.arange(5))}
      )
  
      forecaster = ForecasterAutoregMultiSeriesCustom(
          regressor=LinearRegression(),
          fun_predictors=create_predictors_3,
          name_predictors=["lag_1", "lag_2"],
          window_size=3,
      )
  
      err_msg = re.escape(
          (
              f"The length of provided predictors names (`name_predictors`) do not "
              f"match the number of columns created by `fun_predictors()`."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.fit(series=series)
  
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiSeriesCustom import ForecasterAutoregMultiSeriesCustom
  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 12 for calling a global function with example usage: test_create_train_X_y_ValueError_when_len_name_predictors_not_match_X_train_columns() without return types