code: def test_get_metric_import_and_calculate_mean_squared_log_error_correctly():
      """
      Test get_metric import and calculate mean_squared_log_error correctly.
      """
      metric_str = "mean_squared_log_error"
      metric = _get_metric(metric_str)
      y_true = [3, 5, 2.5, 7]
      y_pred = [2.5, 5, 4, 8]
      expected = mean_squared_log_error(y_true=y_true, y_pred=y_pred)
  
      assert metric(y_true=y_true, y_pred=y_pred) == expected
  
file_path: skforecast/skforecast/model_selection/tests/test_get_metric.py
imports: import re
  import pytest
  from pytest import approx
  import numpy
  import pandas
  from skforecast.model_selection.model_selection import _get_metric
  from sklearn.metrics import mean_squared_error
  from sklearn.metrics import mean_absolute_error
  from sklearn.metrics import mean_absolute_percentage_error
  from sklearn.metrics import mean_squared_log_error
label_desc: Use image node_id 5 for calling a global function with example usage: test_get_metric_import_and_calculate_mean_squared_log_error_correctly() without return types