code: def test_fit_ValueError_when_exog_columns_same_as_series_col_names(
      exog,
  ):
      """
      Test ValueError is raised when an exog column is named the same as
      the series levels.
      """
      series = pd.DataFrame(
          {
              "l1": pd.Series(np.arange(10)),
              "l2": pd.Series(np.arange(10)),
          }
      )
  
      forecaster = ForecasterAutoregMultiSeriesCustom(
          regressor=LinearRegression(),
          fun_predictors=create_predictors,
          window_size=3,
      )
      series_col_names = ["l1", "l2"]
      exog_col_names = exog if isinstance(exog, list) else [exog]
  
      err_msg = re.escape(
          (
              f"`exog` cannot contain a column named the same as one of the series"
              f" (column names of series).\n"
              f"    `series` columns : {series_col_names}.\n"
              f"    `exog`   columns : {exog_col_names}."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.fit(
              series=series,
              exog=series[exog],
              store_in_sample_residuals=False,
          )
  
file_path: skforecast/skforecast/ForecasterAutoregMultiSeriesCustom/tests/test_fit.py
imports: import re
  import pytest
  import numpy
  import pandas
  from skforecast.ForecasterAutoregMultiSeriesCustom import ForecasterAutoregMultiSeriesCustom
  from sklearn.linear_model import LinearRegression
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 2 for calling a global function with example usage: test_fit_ValueError_when_exog_columns_same_as_series_col_names(exog) without return types