code: def test_save_and_load(self):
      metric = Metric({"name": "logloss"})
      lgb = LightgbmAlgorithm(self.params)
      lgb.fit(self.X, self.y)
      y_predicted = lgb.predict(self.X)
      loss = metric(self.y, y_predicted)
  
      filename = os.path.join(
          tempfile.gettempdir(), os.urandom(12).hex()
      )
      lgb.save(filename)
      lgb2 = LightgbmAlgorithm({})
      self.assertTrue(lgb.uid != lgb2.uid)
      self.assertTrue(lgb2.model is None)
      lgb2.load(filename)
      # Finished with the file, delete it
      os.remove(filename)
  
      y_predicted = lgb2.predict(self.X)
      loss2 = metric(self.y, y_predicted)
      assert_almost_equal(loss, loss2)
  
imports: import unittest
  import tempfile
  import json
  import copy
  import os
  import numpy
  import pandas
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.algorithms.lightgbm import LightgbmAlgorithm, additional
  from supervised.utils.metric import Metric
label_desc: Use image node_id 5 for calling the LightgbmAlgorithmTest obj's underlying member method code with example usage: obj.test_save_and_load() without return types