/* 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. */ #pragma once #include #include #include #include #include "common/types.h" #include "framework/lod_tensor.h" #include "framework/operator.h" #include "framework/program/program.h" #include "framework/tensor.h" #ifdef PADDLE_EXECUTOR_MULTITHREAD #include #include #include #include "common/depCore.h" #endif namespace paddle_mobile { template class Loader { public: /* * @b load separate format fluid model * @b 加载分开形式的 fluid 模型 * */ const framework::Program Load(const std::string &dirname, bool optimize = false, bool can_add_split = false); /* * @b load combine format fluid mode * @b 加载结合在一起格式的模型 * */ const framework::Program Load(const std::string &model_path, const std::string ¶_path, bool optimize = false); private: const framework::Program LoadProgram(const std::string &model_path, bool optimize = false, bool can_add_split = false); }; template class Executor { public: typedef typename PrecisionTrait

::ptype Ptype; /* * @b init executor with program load by Loader class * @b 用 loader load 的 program 实例化 executor * */ Executor(const framework::Program p, int batch_size = 1, bool use_optimize = true); /* * @b to predict * */ std::shared_ptr Predict(const framework::Tensor &t); /* * @b to predict with vector and dim * * @b 使用 输入 和 输入的维度信息 进行预测 * */ std::vector Predict(const std::vector &input, const std::vector &dims); protected: Executor() = default; void InitMemory(); void LoadMemory(const framework::VarDesc var_desc, framework::LoDTensor *tensor, char *&data); void InitCombineMemory(); framework::Program program_; int batch_size_ = 1; std::shared_ptr to_predict_program_; std::shared_ptr Predict(const framework::Tensor &t, int block_id); std::map>>> ops_of_block_; bool use_optimize_ = false; #ifdef PADDLE_EXECUTOR_MULTITHREAD std::vector depManager; #endif #ifdef PADDLE_MOBILE_PROFILE struct ProfInfo { int tid = 0; uint64_t runBegin = 0UL; uint64_t runEnd = 0UL; }; #endif }; } // namespace paddle_mobile