docstr: Unit test load_smartpredictor 1
code: def test_load_smartpredictor_1(self):
      """
      Unit test load_smartpredictor 1
      """
      y_pred = pd.DataFrame(data=np.array([1, 2]), columns=["pred"])
      dataframe_x = pd.DataFrame([[1, 2, 4], [1, 2, 3]])
      clf = cb.CatBoostClassifier(n_estimators=1).fit(
          dataframe_x, y_pred
      )
      xpl = SmartExplainer(model=clf, features_dict={})
      xpl.compile(x=dataframe_x, y_pred=y_pred)
      predictor = xpl.to_smartpredictor()
  
      current = Path(path.abspath(__file__)).parent.parent.parent
      if str(sys.version)[0:4] == "3.10":
          pkl_file = path.join(
              current, "data/predictor_to_load_310.pkl"
          )
      elif str(sys.version)[0:3] == "3.8":
          pkl_file = path.join(current, "data/predictor_to_load_38.pkl")
      elif str(sys.version)[0:3] == "3.9":
          pkl_file = path.join(current, "data/predictor_to_load_39.pkl")
      elif str(sys.version)[0:4] == "3.11":
          pkl_file = path.join(
              current, "data/predictor_to_load_311.pkl"
          )
      else:
          raise NotImplementedError
  
      predictor.save(pkl_file)
      predictor2 = load_smartpredictor(pkl_file)
  
      attrib_predictor = [
          element for element in predictor.__dict__.keys()
      ]
      attrib_predictor2 = [
          element for element in predictor2.__dict__.keys()
      ]
  
      assert all(
          attrib in attrib_predictor2 for attrib in attrib_predictor
      )
      assert all(
          attrib2 in attrib_predictor for attrib2 in attrib_predictor2
      )
  
file_path: shapash/tests/unit_tests/utils/test_load_smartpredictor.py
imports: import unittest
  import sys
  from os import path
  from pathlib import Path
  from shapash.utils.load_smartpredictor import load_smartpredictor
  from shapash import SmartExplainer
  import pandas
  import numpy
  import catboost
label_desc: Use image node_id 1 for calling the Test_load_smartpredictor obj's underlying member method code with example usage: obj.test_load_smartpredictor_1() without return types