# -*- coding: utf-8 -*- import xgboost as xgb import unittest import numpy as np class TestOMP(unittest.TestCase): def test_omp(self): dpath = 'demo/data/' dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train') dtest = xgb.DMatrix(dpath + 'agaricus.txt.test') param = {'booster': 'gbtree', 'objective': 'binary:logistic', 'grow_policy': 'depthwise', 'tree_method': 'hist', 'eval_metric': 'error', 'max_depth': 5, 'min_child_weight': 0} watchlist = [(dtest, 'eval'), (dtrain, 'train')] num_round = 5 def run_trial(): res = {} bst = xgb.train(param, dtrain, num_round, watchlist, evals_result=res) metrics = [res['train']['error'][-1], res['eval']['error'][-1]] preds = bst.predict(dtest) return metrics, preds def consist_test(title, n): auc, pred = run_trial() for i in range(n-1): auc2, pred2 = run_trial() try: assert auc == auc2 assert np.array_equal(pred, pred2) except Exception as e: print('-------test %s failed, num_trial: %d-------' % (title, i)) raise e auc, pred = auc2, pred2 return auc, pred print('test approx ...') param['tree_method'] = 'approx' param['nthread'] = 1 auc_1, pred_1 = consist_test('approx_thread_1', 100) param['nthread'] = 2 auc_2, pred_2 = consist_test('approx_thread_2', 100) param['nthread'] = 3 auc_3, pred_3 = consist_test('approx_thread_3', 100) assert auc_1 == auc_2 == auc_3 assert np.array_equal(auc_1, auc_2) assert np.array_equal(auc_1, auc_3) print('test hist ...') param['tree_method'] = 'hist' param['nthread'] = 1 auc_1, pred_1 = consist_test('hist_thread_1', 100) param['nthread'] = 2 auc_2, pred_2 = consist_test('hist_thread_2', 100) param['nthread'] = 3 auc_3, pred_3 = consist_test('hist_thread_3', 100) assert auc_1 == auc_2 == auc_3 assert np.array_equal(auc_1, auc_2) assert np.array_equal(auc_1, auc_3)