code: def test_integration(self):
      a = AutoML(
          results_path=self.automl_dir,
          mode="Compete",
          algorithms=["Baseline", "CatBoost", "LightGBM", "Xgboost"],
          stack_models=True,
          total_time_limit=60,
          validation_strategy={
              "validation_type": "kfold",
              "k_folds": 3,
              "shuffle": True,
              "stratify": True,
              "random_seed": 123,
          },
      )
  
      X, y = datasets.make_classification(
          n_samples=1000,
          n_features=30,
          n_informative=29,
          n_redundant=1,
          n_classes=8,
          n_clusters_per_class=3,
          n_repeated=0,
          shuffle=False,
          random_state=0,
      )
      X_train, X_test, y_train, y_test = train_test_split(
          X, y, train_size=0.8
      )
  
      a.fit(X_train, y_train)
      p = a.predict_all(X_test)
  
      a2 = AutoML(results_path=self.automl_dir)
      p2 = a2.predict_all(X_test)
  
      assert_almost_equal(
          p["prediction_0"].iloc[0], p2["prediction_0"].iloc[0]
      )
      assert_almost_equal(
          p["prediction_7"].iloc[0], p2["prediction_7"].iloc[0]
      )
  
file_path: mljar-supervised/tests/tests_automl/test_prediction_after_load.py
imports: import os
  import unittest
  import tempfile
  import json
  import numpy
  import pandas
  import shutil
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
  from numpy.testing import assert_almost_equal
  from supervised import AutoML
label_desc: Use image node_id 2 for calling the AutoMLPredictionAfterLoadTest obj's underlying member method code with example usage: obj.test_integration() without return types