code: def test_fit_predict(self):
      metric = Metric({"name": "logloss"})
      loss_prev = None
      for _ in range(2):
          cat = CatBoostAlgorithm(self.params)
          cat.fit(self.X, self.y)
          y_predicted = cat.predict(self.X)
          loss = metric(self.y, y_predicted)
          if loss_prev is not None:
              assert_almost_equal(loss, loss_prev, decimal=3)
          loss_prev = loss
  
imports: import unittest
  import tempfile
  import json
  import copy
  import numpy
  import pandas
  import os
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.algorithms.catboost import CatBoostAlgorithm, additional
  from supervised.utils.metric import Metric
  import tempfile
label_desc: Use image node_id 3 for calling the CatBoostAlgorithmTest obj's underlying member method code with example usage: obj.test_fit_predict() without return types