From 22c71398e3b9a864d8c2d3a3a2e589d42db82098 Mon Sep 17 00:00:00 2001 From: Tao Luo Date: Fri, 21 Dec 2018 17:49:27 +0800 Subject: [PATCH] add MM_DNN inference test test=develop --- .../fluid/inference/tests/api/CMakeLists.txt | 5 + .../tests/api/analyzer_mm_dnn_tester.cc | 178 ++++++++++++++++++ 2 files changed, 183 insertions(+) create mode 100644 paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc diff --git a/paddle/fluid/inference/tests/api/CMakeLists.txt b/paddle/fluid/inference/tests/api/CMakeLists.txt index 46ce61b73..95bbc74a5 100644 --- a/paddle/fluid/inference/tests/api/CMakeLists.txt +++ b/paddle/fluid/inference/tests/api/CMakeLists.txt @@ -75,6 +75,11 @@ set(LAC_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/lac") download_model_and_data(${LAC_INSTALL_DIR} "lac_model.tar.gz" "lac_data.txt.tar.gz") inference_analysis_api_test(test_analyzer_lac ${LAC_INSTALL_DIR} analyzer_lac_tester.cc) +# MM DNN +set(MM_DNN_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/mm_dnn") +download_model_and_data(${MM_DNN_INSTALL_DIR} "MM_DNN_model.tar.gz" "MM_DNN_data.txt.tar.gz") +inference_analysis_api_test(test_analyzer_mm_dnn ${MM_DNN_INSTALL_DIR} analyzer_mm_dnn_tester.cc) + # text_classification set(TEXT_CLASSIFICATION_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/text_classification") download_model_and_data(${TEXT_CLASSIFICATION_INSTALL_DIR} "text-classification-Senta.tar.gz" "text_classification_data.txt.tar.gz") diff --git a/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc b/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc new file mode 100644 index 000000000..858bc6d4e --- /dev/null +++ b/paddle/fluid/inference/tests/api/analyzer_mm_dnn_tester.cc @@ -0,0 +1,178 @@ +// Copyright (c) 2018 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. + +#include "paddle/fluid/inference/tests/api/tester_helper.h" + +namespace paddle { +namespace inference { +using contrib::AnalysisConfig; + +struct DataRecord { + std::vector> query_data_all, title_data_all; + std::vector lod1, lod2; + size_t batch_iter{0}; + size_t batch_size{1}; + size_t num_samples; // total number of samples + DataRecord() = default; + explicit DataRecord(const std::string &path, int batch_size = 1) + : batch_size(batch_size) { + Load(path); + } + DataRecord NextBatch() { + DataRecord data; + size_t batch_end = batch_iter + batch_size; + // NOTE skip the final batch, if no enough data is provided. + if (batch_end <= query_data_all.size()) { + data.query_data_all.assign(query_data_all.begin() + batch_iter, + query_data_all.begin() + batch_end); + data.title_data_all.assign(title_data_all.begin() + batch_iter, + title_data_all.begin() + batch_end); + // Prepare LoDs + data.lod1.push_back(0); + data.lod2.push_back(0); + CHECK(!data.query_data_all.empty()); + CHECK(!data.title_data_all.empty()); + CHECK_EQ(data.query_data_all.size(), data.title_data_all.size()); + for (size_t j = 0; j < data.query_data_all.size(); j++) { + // calculate lod + data.lod1.push_back(data.lod1.back() + data.query_data_all[j].size()); + data.lod2.push_back(data.lod2.back() + data.query_data_all[j].size()); + } + } + batch_iter += batch_size; + return data; + } + void Load(const std::string &path) { + std::ifstream file(path); + std::string line; + int num_lines = 0; + while (std::getline(file, line)) { + num_lines++; + std::vector data; + split(line, '\t', &data); + // load query data + std::vector query_data; + split_to_int64(data[0], ' ', &query_data); + // load title data + std::vector title_data; + split_to_int64(data[1], ' ', &title_data); + query_data_all.push_back(std::move(query_data)); + title_data_all.push_back(std::move(title_data)); + } + num_samples = num_lines; + } +}; + +void PrepareInputs(std::vector *input_slots, DataRecord *data, + int batch_size) { + PaddleTensor lod_query_tensor, lod_title_tensor; + lod_query_tensor.name = "left"; + lod_title_tensor.name = "right"; + auto one_batch = data->NextBatch(); + int size1 = one_batch.lod1[one_batch.lod1.size() - 1]; // token batch size + int size2 = one_batch.lod2[one_batch.lod2.size() - 1]; // token batch size + lod_query_tensor.shape.assign({size1, 1}); + lod_query_tensor.lod.assign({one_batch.lod1}); + lod_title_tensor.shape.assign({size2, 1}); + lod_title_tensor.lod.assign({one_batch.lod2}); + // assign data + TensorAssignData(&lod_query_tensor, one_batch.query_data_all); + TensorAssignData(&lod_title_tensor, one_batch.title_data_all); + // Set inputs. + input_slots->assign({lod_query_tensor, lod_title_tensor}); + for (auto &tensor : *input_slots) { + tensor.dtype = PaddleDType::INT64; + } +} + +void SetConfig(contrib::AnalysisConfig *cfg) { + cfg->model_dir = FLAGS_infer_model; + cfg->use_gpu = false; + cfg->device = 0; + cfg->specify_input_name = true; + cfg->enable_ir_optim = true; +} + +void SetInput(std::vector> *inputs) { + DataRecord data(FLAGS_infer_data, FLAGS_batch_size); + std::vector input_slots; + int epoch = FLAGS_test_all_data ? data.num_samples / FLAGS_batch_size : 1; + LOG(INFO) << "number of samples: " << epoch * FLAGS_batch_size; + for (int bid = 0; bid < epoch; ++bid) { + PrepareInputs(&input_slots, &data, FLAGS_batch_size); + (*inputs).emplace_back(input_slots); + } +} + +// Easy for profiling independently. +TEST(Analyzer_MM_DNN, profile) { + contrib::AnalysisConfig cfg; + SetConfig(&cfg); + std::vector outputs; + + std::vector> input_slots_all; + SetInput(&input_slots_all); + TestPrediction(reinterpret_cast(&cfg), + input_slots_all, &outputs, FLAGS_num_threads); + + if (FLAGS_num_threads == 1 && !FLAGS_test_all_data) { + PADDLE_ENFORCE_EQ(outputs.size(), 2UL); + for (auto &output : outputs) { + size_t size = GetSize(output); + PADDLE_ENFORCE_GT(size, 0); + float *result = static_cast(output.data.data()); + // output is probability, which is in (-1, 1). + for (size_t i = 0; i < size; i++) { + EXPECT_GT(result[i], -1); + EXPECT_LT(result[i], 1); + } + } + } +} + +// Check the fuse status +TEST(Analyzer_MM_DNN, fuse_statis) { + contrib::AnalysisConfig cfg; + SetConfig(&cfg); + + int num_ops; + auto predictor = CreatePaddlePredictor(cfg); + auto fuse_statis = GetFuseStatis( + static_cast(predictor.get()), &num_ops); +} + +// Compare result of NativeConfig and AnalysisConfig +TEST(Analyzer_MM_DNN, compare) { + contrib::AnalysisConfig cfg; + SetConfig(&cfg); + + std::vector> input_slots_all; + SetInput(&input_slots_all); + CompareNativeAndAnalysis( + reinterpret_cast(&cfg), input_slots_all); +} + +// Compare Deterministic result +TEST(Analyzer_MM_DNN, compare_determine) { + AnalysisConfig cfg; + SetConfig(&cfg); + + std::vector> input_slots_all; + SetInput(&input_slots_all); + CompareDeterministic(reinterpret_cast(&cfg), + input_slots_all); +} + +} // namespace inference +} // namespace paddle -- GitLab