code: def test_check_backtesting_input_TypeError_when_metric_not_correct_type():
      """
      Test TypeError is raised in check_backtesting_input if `metric` is not string,
      a callable function, or a list containing multiple strings and/or callables.
      """
      forecaster = ForecasterAutoreg(
          regressor=Ridge(random_state=123), lags=2
      )
      metric = 5
  
      err_msg = re.escape(
          (
              f"`metric` must be a string, a callable function, or a list containing "
              f"multiple strings and/or callables. Got {type(metric)}."
          )
      )
      with pytest.raises(TypeError, match=err_msg):
          check_backtesting_input(
              forecaster=forecaster,
              steps=5,
              metric=metric,
              y=y,
              series=None,
              initial_train_size=len(y[:-12]),
              fixed_train_size=False,
              gap=0,
              allow_incomplete_fold=False,
              refit=False,
              interval=None,
              n_boot=500,
              random_state=123,
              in_sample_residuals=True,
              verbose=False,
              show_progress=False,
          )
  
imports: import re
  import pytest
  import numpy
  import pandas
  from pmdarima.arima import ARIMA
  from sklearn.linear_model import Ridge
  from sklearn.exceptions import NotFittedError
  from skforecast.ForecasterAutoreg import ForecasterAutoreg
  from skforecast.ForecasterAutoregCustom import ForecasterAutoregCustom
  from skforecast.ForecasterAutoregDirect import ForecasterAutoregDirect
  from skforecast.ForecasterSarimax import ForecasterSarimax
  from skforecast.ForecasterAutoregMultiSeries import ForecasterAutoregMultiSeries
  from skforecast.ForecasterAutoregMultiSeriesCustom import ForecasterAutoregMultiSeriesCustom
  from skforecast.ForecasterAutoregMultiVariate import ForecasterAutoregMultiVariate
  from skforecast.utils import check_backtesting_input
  from skforecast.model_selection.tests.fixtures_model_selection import y
  from skforecast.model_selection_multiseries.tests.fixtures_model_selection_multiseries import series
label_desc: Use image node_id 6 for calling a global function with example usage: test_check_backtesting_input_TypeError_when_metric_not_correct_type() without return types