code: def test(self):
      case1 = dx.Explainer(self.model, self.X, self.y, verbose=False)
      case2 = dx.Explainer(self.model, self.X, None, verbose=False)
      case3 = dx.Explainer(self.model, None, self.y, verbose=False)
      case4 = dx.Explainer(self.model, None, None, verbose=False)
  
      self.assertIsInstance(case1, dx.Explainer)
      self.assertIsInstance(case2, dx.Explainer)
      self.assertIsInstance(case3, dx.Explainer)
      self.assertIsInstance(case4, dx.Explainer)
  
      with self.assertRaises(ValueError):
          case2.model_performance()
      with self.assertRaises(ValueError):
          case3.model_parts()
      with self.assertRaises(ValueError):
          case4.model_profile()
  
      case5 = case2.predict_parts(self.X.iloc[[0]])
      case6 = case2.predict_profile(self.X.iloc[[0]])
  
      self.assertIsInstance(case5, dx.predict_explanations.BreakDown)
      self.assertIsInstance(
          case6, dx.predict_explanations.CeterisParibus
      )
  
      with warnings.catch_warnings(record=True) as w:
          # Cause all warnings to always be triggered.
          warnings.simplefilter("always")
          # Trigger a warning.
          case5 = dx.Explainer(
              self.model,
              self.X,
              self.y,
              predict_function=1,
              verbose=False,
          )
          assert issubclass(w[-1].category, UserWarning)
  
      self.assertIsInstance(case5, dx.Explainer)
  
file_path: DALEX/python/dalex/test/test_explainer.py
imports: import unittest
  from sklearn.compose import ColumnTransformer
  from sklearn.impute import SimpleImputer
  from sklearn.neural_network import MLPRegressor
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder
  import dalex
  import numpy
  import warnings
label_desc: Use image node_id 2 for calling the ExplainerTest obj's underlying member method code with example usage: obj.test() without return types