/* 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 #include #include "../test_helper.h" #include "../test_include.h" void test(int argc, char *argv[]); int main(int argc, char *argv[]) { test(argc, argv); return 0; } void test(int argc, char *argv[]) { int arg_index = 1; bool fuse = std::stoi(argv[arg_index]) == 1; arg_index++; bool enable_memory_optimization = std::stoi(argv[arg_index]) == 1; arg_index++; paddle_mobile::PaddleMobileConfigInternal config; config.enable_memory_optimization = enable_memory_optimization; paddle_mobile::PaddleMobile paddle_mobile(config); paddle_mobile.SetThreadNum(1); int dim_count = std::stoi(argv[arg_index]); arg_index++; int size = 1; std::vector dims; for (int i = 0; i < dim_count; i++) { int64_t dim = std::stoi(argv[arg_index + i]); size *= dim; dims.push_back(dim); } arg_index += dim_count; bool is_lod = std::stoi(argv[arg_index]) == 1; arg_index++; paddle_mobile::framework::LoD lod{{}}; if (is_lod) { int lod_count = std::stoi(argv[arg_index]); arg_index++; for (int i = 0; i < lod_count; i++) { int dim = std::stoi(argv[arg_index + i]); lod[0].push_back(dim); } arg_index += lod_count; } int var_count = std::stoi(argv[arg_index]); arg_index++; int sample_step = std::stoi(argv[arg_index]); arg_index++; std::vector var_names; for (int i = 0; i < var_count; i++) { std::string var_name = argv[arg_index + i]; var_names.push_back(var_name); } arg_index += var_count; auto time1 = time(); if (paddle_mobile.Load("./checked_model/model", "./checked_model/params", fuse, false, 1, true)) { auto time2 = time(); std::cout << "auto-test" << " load-time-cost :" << time_diff(time1, time1) << "ms" << std::endl; std::vector input_data; std::ifstream in("input.txt", std::ios::in); for (int i = 0; i < size; i++) { float num; in >> num; input_data.push_back(num); } in.close(); paddle_mobile::framework::LoDTensor input_tensor; if (is_lod) { input_tensor.Resize(paddle_mobile::framework::make_ddim(dims)); input_tensor.set_lod(lod); auto *tensor_data = input_tensor.mutable_data(); for (int i = 0; i < size; i++) { tensor_data[i] = input_data[i]; } } // 预热10次 for (int i = 0; i < 10; i++) { if (is_lod) { auto out = paddle_mobile.Predict(input_tensor); } else { auto out = paddle_mobile.Predict(input_data, dims); } } // 测速 auto time3 = time(); for (int i = 0; i < 50; i++) { if (is_lod) { auto out = paddle_mobile.Predict(input_tensor); } else { auto out = paddle_mobile.Predict(input_data, dims); } } auto time4 = time(); std::cout << "auto-test" << " predict-time-cost " << time_diff(time3, time4) / 50 << "ms" << std::endl; // 测试正确性 if (is_lod) { auto out = paddle_mobile.Predict(input_tensor); } else { auto out = paddle_mobile.Predict(input_data, dims); } for (auto var_name : var_names) { auto out = paddle_mobile.Fetch(var_name); auto len = out->numel(); if (len == 0) { continue; } if (out->memory_size() == 0) { continue; } auto data = out->data(); std::string sample = ""; for (int i = 0; i < len; i += sample_step) { sample += " " + std::to_string(data[i]); } std::cout << "auto-test" << " var " << var_name << sample << std::endl; } std::cout << std::endl; } }