code: def my_metric(y_true, y_pred):  # pragma: no cover
      """
      Callable metric
      """
      metric = ((y_true - y_pred) / len(y_true)).mean()
  
      return metric
  
imports: import re
  import pytest
  import platform
  from pytest import approx
  import numpy
  import pandas
  from sklearn.linear_model import Ridge
  from pmdarima.arima import ARIMA
  from skforecast.Sarimax import Sarimax
  from skforecast.ForecasterAutoreg import ForecasterAutoreg
  from skforecast.ForecasterSarimax import ForecasterSarimax
  from skforecast.model_selection_sarimax import backtesting_sarimax
  from ...ForecasterSarimax.tests.fixtures_ForecasterSarimax import y_datetime
  from ...ForecasterSarimax.tests.fixtures_ForecasterSarimax import exog_datetime
label_desc: Use image node_id 11 for calling a global function with example usage: my_metric(y_true, y_pred) and returns: metric