code: def test_sort_features_by_priority_different_model(sample_features):
      # test the ordering of feature importance computation when prior feature importance computation from a different fitted model was done
      prev_importance_df = evaluated_fi_df_template(sample_features)
      using_prev_fit_fi = sample_features[-2:]
      sorted_features = sort_features_by_priority(
          features=sample_features,
          prev_importance_df=prev_importance_df,
          using_prev_fit_fi=using_prev_fit_fi,
      )
      sorted_prev_fit_features = (
          prev_importance_df[
              prev_importance_df.index.isin(using_prev_fit_fi)
          ]
          .sort_values("importance")
          .index.tolist()
      )
      sorted_curr_fit_features = (
          prev_importance_df[
              ~prev_importance_df.index.isin(using_prev_fit_fi)
          ]
          .sort_values("importance")
          .index.tolist()
      )
      expected_features = (
          sorted_prev_fit_features + sorted_curr_fit_features
      )
      assert sorted_features == expected_features
  
file_path: autogluon/core/tests/unittests/test_feature_selection.py
imports: import numpy
  import pandas
  import pytest
  from numpy.core.fromnumeric import sort
  from autogluon.core.utils.feature_selection import *
  from autogluon.core.utils.utils import unevaluated_fi_df_template
label_desc: Use image node_id 12 for calling a global function with example usage: test_sort_features_by_priority_different_model(sample_features) without return types