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