code: def test_save_and_load(self):
      metric = Metric({"name": "logloss"})
      nn = MLPAlgorithm(self.params)
      nn.fit(self.X, self.y)
      y_predicted = nn.predict(self.X)
      loss = metric(self.y, y_predicted)
  
      filename = os.path.join(
          tempfile.gettempdir(), os.urandom(12).hex()
      )
  
      nn.save(filename)
      json_desc = nn.get_params()
      nn2 = MLPAlgorithm(json_desc["params"])
      nn2.load(filename)
      # Finished with the file, delete it
      os.remove(filename)
  
      y_predicted = nn2.predict(self.X)
      loss2 = metric(self.y, y_predicted)
      assert_almost_equal(loss, loss2)
  
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  import os
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from sklearn import preprocessing
  from supervised.algorithms.nn import MLPAlgorithm, MLPRegressorAlgorithm
  from supervised.utils.metric import Metric
label_desc: Use image node_id 4 for calling the MLPAlgorithmTest obj's underlying member method code with example usage: obj.test_save_and_load() without return types