code: def test_constructor(self):
      case1 = self.exp.model_parts()
      self.assertIsInstance(
          case1, (dx.model_explanations.VariableImportance,)
      )
      self.assertIsInstance(case1.result, (pd.DataFrame,))
      self.assertEqual(
          list(case1.result.columns),
          ["variable", "dropout_loss", "label"],
      )
  
      case2 = self.exp.model_parts(keep_raw_permutations=True)
      self.assertTrue(hasattr(case2, "permutation"))
      self.assertIsInstance(case2.permutation, pd.DataFrame)
  
imports: import unittest
  import numpy
  from plotly.graph_objs import Figure
  from sklearn.compose import ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.neural_network import MLPClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
  import dalex
  from dalex.model_explanations._model_performance.utils import *
  from dalex.model_explanations._variable_importance import utils
label_desc: Use image node_id 4 for calling the FeatureImportanceTestTitanic obj's underlying member method code with example usage: obj.test_constructor() without return types