code: def test_copy(self):
      # train model #1
      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)
      # create model #2
      lgb2 = LightgbmAlgorithm(self.params)
      # model #2 is set to None, while initialized
      self.assertTrue(lgb2.model is None)
      # do a copy and use it for predictions
      lgb2 = lgb.copy()
      self.assertEqual(type(lgb), type(lgb2))
      y_predicted = lgb2.predict(self.X)
      loss2 = metric(self.y, y_predicted)
      self.assertEqual(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 4 for calling the LightgbmAlgorithmTest obj's underlying member method code with example usage: obj.test_copy() without return types