/* Copyright (c) 2016 Baidu, Inc. All Rights Reserve. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include #include #include "paddle/trainer/Trainer.h" #include using namespace paddle; // NOLINT using namespace std; // NOLINT static const string& configFile1 = "trainer/tests/sample_trainer_config.conf"; static const string& configFile2 = "trainer/tests/sample_trainer_config_hsigmoid.conf"; static const string& configFile3 = "trainer/tests/chunking.conf"; static const string& configFile4 = "trainer/tests/sample_trainer_config_parallel.conf"; P_DECLARE_bool(use_gpu); P_DECLARE_string(config); P_DECLARE_int32(gpu_id); P_DECLARE_bool(allow_only_one_model_on_one_gpu); void checkGradientTest(const string& configFile, bool useGpu, bool parallel, int trainerCount = 1) { FLAGS_use_gpu = useGpu; FLAGS_parallel_nn = parallel; FLAGS_config = configFile; FLAGS_trainer_count = trainerCount; LOG(INFO) << " useGpu=" << useGpu << " trainerCount=" << trainerCount << " configFile=" << configFile; Trainer trainer; trainer.init(TrainerConfigHelper::createFromFlagConfig()); EXPECT_LE(fabs(trainer.checkGradient()), 0.02); } TEST(checkGradient, cpu) { checkGradientTest(configFile1, false, false); } #ifndef PADDLE_ONLY_CPU TEST(checkGradient, gpu) { checkGradientTest(configFile1, true, false); } TEST(checkGradient, multiGpu) { int numGpu; numGpu = hl_get_device_count(); for (auto count : {2, 4}) { if (count <= numGpu) { checkGradientTest(configFile1, true, false, count); } } } TEST(checkGradient, parallel) { checkGradientTest(configFile4, true, true); } TEST(checkGradient, multiParallel) { FLAGS_allow_only_one_model_on_one_gpu = false; checkGradientTest(configFile4, true, true, 2); FLAGS_allow_only_one_model_on_one_gpu = true; } #endif TEST(checkGradient, multi) { int numGpu; if (version::isWithGpu()) { numGpu = hl_get_device_count(); } else { numGpu = 0; } for (bool useGpu : {false, true}) { for (auto count : {2, 4}) { if (useGpu && count > numGpu) continue; checkGradientTest(configFile1, useGpu, false, count); } } } TEST(checkGradient, hsigmoid) { checkGradientTest(configFile2, false, false); } TEST(checkGradient, chunk) { EXPECT_EQ(0, system("python2 trainer/tests/gen_proto_data.py")); checkGradientTest(configFile3, false, false); #ifndef PADDLE_ONLY_CPU checkGradientTest(configFile3, true, true); #endif } TEST(checkGradient, non_parallel) { checkGradientTest(configFile4, false, false); } int main(int argc, char** argv) { initMain(argc, argv); initPython(argc, argv); testing::InitGoogleTest(&argc, argv); return RUN_ALL_TESTS(); }