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139 changes: 139 additions & 0 deletions
139
paddle/fluid/inference/tests/infer_ut/test_ernie_text_cls.cc
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| // Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
| // | ||
| // 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. | ||
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| #include "test_suite.h" // NOLINT | ||
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| DEFINE_string(modeldir, "", "Directory of the inference model."); | ||
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| namespace paddle_infer { | ||
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| template <typename T> | ||
| T cRandom(int min, int max) { | ||
| unsigned int seed = 100; | ||
| return (min + | ||
| static_cast<T>(max * rand_r(&seed) / static_cast<T>(RAND_MAX + 1))); | ||
| } | ||
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| std::map<std::string, paddle::test::Record> PrepareInput(int batch_size) { | ||
| // init input data | ||
| int digit_length = 115; | ||
| paddle::test::Record input_ids, segment_ids; | ||
| int input_num = batch_size * digit_length; | ||
| std::vector<int64_t> input_data(input_num, 1); | ||
| std::vector<int64_t> segment_data(input_num, 0); | ||
| srand((unsigned)time(NULL)); | ||
| for (int x = 0; x < input_data.size(); x++) { | ||
| input_data[x] = cRandom<int>(1, 100); | ||
| } | ||
| input_ids.data = std::vector<float>(input_data.begin(), input_data.end()); | ||
| input_ids.shape = std::vector<int>{batch_size, digit_length}; | ||
| input_ids.type = paddle::PaddleDType::INT64; | ||
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| segment_ids.data = | ||
| std::vector<float>(segment_data.begin(), segment_data.end()); | ||
| segment_ids.shape = std::vector<int>{batch_size, digit_length}; | ||
| segment_ids.type = paddle::PaddleDType::INT64; | ||
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| std::map<std::string, paddle::test::Record> my_input_data_map; | ||
| my_input_data_map.insert({"input_ids", input_ids}); | ||
| my_input_data_map.insert({"token_type_ids", segment_ids}); | ||
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| return my_input_data_map; | ||
| } | ||
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| TEST(test_ernie_text_cls, analysis_gpu_bz2_buffer) { | ||
| // init input data | ||
| auto my_input_data_map = PrepareInput(2); | ||
| // init output data | ||
| std::map<std::string, paddle::test::Record> infer_output_data, | ||
| truth_output_data; | ||
| // prepare groudtruth config | ||
| paddle_infer::Config config, config_no_ir; | ||
| config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel", | ||
| FLAGS_modeldir + "/inference.pdiparams"); | ||
| config_no_ir.SwitchIrOptim(false); | ||
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| // prepare inference config from buffer | ||
| std::string prog_file = FLAGS_modeldir + "/inference.pdmodel"; | ||
| std::string params_file = FLAGS_modeldir + "/inference.pdiparams"; | ||
| std::string prog_str = paddle::test::read_file(prog_file); | ||
| std::string params_str = paddle::test::read_file(params_file); | ||
| config.SetModelBuffer(prog_str.c_str(), prog_str.size(), params_str.c_str(), | ||
| params_str.size()); | ||
| // get groudtruth by disbale ir | ||
| paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1); | ||
| SingleThreadPrediction(pred_pool_no_ir.Retrive(0), &my_input_data_map, | ||
| &truth_output_data, 1); | ||
| // get infer results | ||
| paddle_infer::services::PredictorPool pred_pool(config, 1); | ||
| SingleThreadPrediction(pred_pool.Retrive(0), &my_input_data_map, | ||
| &infer_output_data); | ||
| // check outputs | ||
| CompareRecord(&truth_output_data, &infer_output_data); | ||
| std::cout << "finish test" << std::endl; | ||
| } | ||
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| TEST(DISABLED_test_ernie_text_cls, multi_thread4_mkl_fp32_bz2) { | ||
| // TODO(OliverLPH): disabled since it cause bug | ||
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| int thread_num = 4; | ||
| // init input data | ||
| auto my_input_data_map = PrepareInput(2); | ||
| // init output data | ||
| std::map<std::string, paddle::test::Record> infer_output_data, | ||
| truth_output_data; | ||
| // prepare groudtruth config | ||
| paddle_infer::Config config, config_no_ir; | ||
| config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel", | ||
| FLAGS_modeldir + "/inference.pdiparams"); | ||
| config.DisableGpu(); | ||
| config_no_ir.SwitchIrOptim(false); | ||
| // prepare inference config | ||
| config.SetModel(FLAGS_modeldir + "/inference.pdmodel", | ||
| FLAGS_modeldir + "/inference.pdiparams"); | ||
| config.DisableGpu(); | ||
| config.EnableMKLDNN(); | ||
| config.SetMkldnnCacheCapacity(10); | ||
| config.SetCpuMathLibraryNumThreads(10); | ||
| // get groudtruth by disbale ir | ||
| paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1); | ||
| SingleThreadPrediction(pred_pool_no_ir.Retrive(0), &my_input_data_map, | ||
| &truth_output_data, 1); | ||
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| // get infer results from multi threads | ||
| std::vector<std::thread> threads; | ||
| services::PredictorPool pred_pool(config, thread_num); | ||
| for (int i = 0; i < thread_num; ++i) { | ||
| threads.emplace_back(paddle::test::SingleThreadPrediction, | ||
| pred_pool.Retrive(i), &my_input_data_map, | ||
| &infer_output_data, 2); | ||
| } | ||
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| // thread join & check outputs | ||
| for (int i = 0; i < thread_num; ++i) { | ||
| LOG(INFO) << "join tid : " << i; | ||
| threads[i].join(); | ||
| CompareRecord(&truth_output_data, &infer_output_data); | ||
| } | ||
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| std::cout << "finish multi-thread test" << std::endl; | ||
| } | ||
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| } // namespace paddle_infer | ||
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| int main(int argc, char** argv) { | ||
| ::testing::InitGoogleTest(&argc, argv); | ||
| ::google::ParseCommandLineFlags(&argc, &argv, true); | ||
| return RUN_ALL_TESTS(); | ||
| } |
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