Merge pull request #642 from xiebaiyuan/develop

增加可被x86编译运行的量化脚本,并增加量化脚本说明文档.

CMakeLists.txt

@@ -9,7 +9,6 @@ option(LOG_PROFILE "log profile" ON)
 option(CPU "armv7 with neon" ON)
 option(MALI_GPU "mali gpu" OFF)
 option(FPGA "fpga" OFF)
-option(QUANTI "quantification" OFF)
 
 file(GLOB_RECURSE PADDLE_MOBILE_CC src/*.cc src/*.cpp src/*.c src/*.mm)
 file(GLOB_RECURSE PADDLE_MOBILE_H src/*.h)
@@ -163,7 +162,4 @@ if(DEBUGING)
     endif()
 endif()
 
-if (QUANTI)
-    add_subdirectory(tools/quantification)
-endif ()
 

doc/quantification.md

+# Quantification 模型量化、反量化
+
+## 背景故事
+部分网络如AlexNet训练出的模型体积较大，不适宜在移动设备上使用。
+
+
+## 解决模型过大办法
+1. 选用适合移动端的模型结构如：mobilenet、googlenet、 yolo、squeezenet 等；
+2. 使用我们提供的量化工具，可以在几乎不影响精度的情况下将float32模型减小至原模型的 1/4；
+
+- - - - - 
+## 量化工具介绍
+
+### 模型转化工具目录：
+
+- [量化工具目录](https://github.com/PaddlePaddle/paddle-mobile/tree/develop/tools/quantification)
+
+- [模型转化工具](https://github.com/PaddlePaddle/paddle-mobile/blob/develop/tools/quantification/convert.cpp)
+
+#### 使用说明
+- [工具使用](https://github.com/PaddlePaddle/paddle-mobile/blob/develop/tools/quantification/README.md)
+
+## 如何读取量化后的模型
+load方法中添加了 quantification 参数，默认为false。 如果需要load量化后的模型，按需传参即可。
+
+[我是源代码](https://github.com/PaddlePaddle/paddle-mobile/blob/55302b33ea3bd68c9797d8f65e527544792b8095/src/io/paddle_mobile.h)
+
+```c++
+bool Load(const std::string &dirname, bool optimize = false,
+            bool quantification = false, int batch_size = 1);
+```
+
+- - - - - 
+
+
+
+
+
+

tools/quantification/CMakeLists.txt

-set(dir ${CMAKE_CURRENT_SOURCE_DIR})
-set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${dir}/build")
+cmake_minimum_required(VERSION 3.6)
+project(quali)
+add_definitions(-DENABLE_EXCEPTION)
 
-ADD_EXECUTABLE(convert convert.cpp)
-target_link_libraries(convert paddle-mobile)
\ No newline at end of file
+set(CMAKE_CXX_STANDARD 11)
+file(GLOB_RECURSE QULIFICATON_CC src/*.cc src/*.cpp src/*.c src/*.mm)
+file(GLOB_RECURSE QULIFICATON_H src/*.h)
+include_directories(. src/)
+
+#add_library(paddle-mobile SHARED ${QULIFICATON_CC} ${QULIFICATON_H} convert.cpp)
+
+add_executable(quantify convert.cpp ${QULIFICATON_CC} ${QULIFICATON_H})
\ No newline at end of file

tools/quantification/README.md

+# 模型量化脚本
+
+#### 量化脚本使用指南
+1. 在PaddleMobile项目目录下（如 ~/PaddleProject/paddle-mobile）
+
+2. cd到  tools/quantification/ 目录
+
+3. cmake编译
+
+    ``` sh
+    cmake .
+    make
+    ```
+
+4. 运行量化脚本
+    ```sh
+    ./quantify (0:seperated. 1:combined ) (输入路径) (输出路径)
+    # quantify googlenet seperated   from  /Users/xiebaiyuan/PaddleProject/quali/models/googlenet to ./googlenet_min
+    ./quantify 0 /Users/xiebaiyuan/PaddleProject/quali/models/googlenet ./googlenet_min 
+
+    ```
+
+*注:*
+*量化工具中*
+*1.seperated模型model文件默认命名为 "__model__";*
+*2.combined模型的model文件默认命名为 "model",参数文件默认命名为"params";*
+
+    
+##### 整体如下:
+以googlenet非combined为例：
+
+```sh
+cd tools/quantification/
+cmake .
+make
+./quantify 0 /Users/xiebaiyuan/PaddleProject/quali/models/googlenet ./googlenet_min
+```
+
+

tools/quantification/convert.cpp

 
 
-#include "io/paddle_mobile.h"
+#include "src/enforce.h"
+#include "src/var_desc.h"
+#include "src/program_desc.h"
 #include <cstdlib>
-using std::string;
-
-static const std::string g_googlenet_combine = "../models/googlenet_combine";
-static const std::string g_googlenet = "../models/googlenet";
-using paddle_mobile::Executor;
-using paddle_mobile::framework::Program;
-
-    char *Get_binary_data(std::string filename) {
-        FILE *file = fopen(filename.c_str(), "rb");
-        PADDLE_MOBILE_ENFORCE(file != nullptr, "can't open file: %s ",
-                              filename.c_str());
-        fseek(file, 0, SEEK_END);
-        int64_t size = ftell(file);
-        PADDLE_MOBILE_ENFORCE(size > 0, "size is too small");
-        rewind(file);
-        char *data = new char[size];
-        size_t bytes_read = fread(data, 1, size, file);
-        PADDLE_MOBILE_ENFORCE(bytes_read == size,
-                              "read binary file bytes do not match with fseek");
-        DLOG << "Get_binary_data end";
-        fclose(file);
-        return data;
+#include <string>
+#include <cmath>
+#include <iostream>
+#include <utility>
+#include <vector>
+#include "src/framework.pb-c.h"
+#include "src/protobuf-c.h"
+#include <fstream>
+#include <iostream>
+
+
+const size_t kSize64 = sizeof(uint64_t);
+const size_t kSize32 = sizeof(uint32_t);
+
+char *Get_binary_data(const std::string &filename) {
+
+    FILE *file = fopen(filename.c_str(), "rb");
+
+    PADDLE_MOBILE_ENFORCE(file != nullptr, "can't open file: %s ",
+                          filename.c_str());
+    fseek(file, 0, SEEK_END);
+    int64_t size = ftell(file);
+
+    PADDLE_MOBILE_ENFORCE(size > 0, "size is too small");
+    rewind(file);
+    auto *data = new char[size];
+    size_t bytes_read = fread(data, 1, static_cast<size_t>(size), file);
+    PADDLE_MOBILE_ENFORCE(bytes_read == size,
+                          "read binary file bytes do not match with fseek");
+    fclose(file);
+    return data;
+}
+
+
+static size_t ReadBuffer(const char *file_name, uint8_t **out) {
+    FILE *fp;
+    fp = fopen(file_name, "rb");
+    PADDLE_MOBILE_ENFORCE(fp != nullptr, " %s open failed !", file_name);
+    fseek(fp, 0, SEEK_END);
+    auto size = static_cast<size_t>(ftell(fp));
+    rewind(fp);
+    *out = reinterpret_cast<uint8_t *>(malloc(size));
+    size_t cur_len = 0;
+    size_t nread;
+    while ((nread = fread(*out + cur_len, 1, size - cur_len, fp)) != 0) {
+        cur_len += nread;
     }
+    fclose(fp);
+    return cur_len;
+}
 
-    void LoadWithDump(const paddle_mobile::framework::VarDesc var_desc,
-                    paddle_mobile::framework::LoDTensor *tensor, char **data, FILE *out_file) {
-        // 1. version
-        uint32_t version = *reinterpret_cast<uint32_t *>(*data);
-        // write version
-        fwrite(&version, sizeof(uint32_t), 1, out_file );
-        (*data) += sizeof(uint32_t);
-        // 2 Lod information
-        uint64_t *lod_level_ptr = new uint64_t();
-        memcpy(lod_level_ptr, (*data), sizeof(uint64_t));
-        uint64_t lod_level = 0;
-        // write lod Information
-        fwrite(&lod_level, sizeof(uint64_t), 1, out_file);
-        delete lod_level_ptr;
-        (*data) += sizeof(uint64_t);
-        auto &lod = *tensor->mutable_lod();
-        lod.resize(lod_level);
-        for (uint64_t i = 0; i < lod_level; ++i) {
-            uint64_t size = *reinterpret_cast<uint64_t *>(*data);
-            // write lod size
-            fwrite(&size, sizeof(uint64_t), 1, out_file);
-            (*data) += sizeof(uint64_t);
-            std::vector<size_t> tmp(size / sizeof(size_t));
-            for (int k = 0; k < tmp.size(); ++k) {
-                tmp[k] = *reinterpret_cast<size_t *>(*data);
-                (*data) += sizeof(size_t);
-            }
-            // write lod size vector
-            fwrite(&tmp, sizeof(size_t), tmp.size(), out_file );
+std::shared_ptr<ProgramDesc> loadParams(const std::string &model_path) {
+    PaddleMobile__Framework__Proto__ProgramDesc *c_program;
+    uint8_t *buf = nullptr;
+    size_t read_size = ReadBuffer(model_path.c_str(), &buf);
+    PADDLE_MOBILE_ENFORCE(buf != nullptr, "read from __model__ is null");
+    c_program = paddle_mobile__framework__proto__program_desc__unpack(
+            nullptr, read_size, buf);
+    PADDLE_MOBILE_ENFORCE(c_program != nullptr, "program is null");
+    auto originProgramDesc = std::make_shared<ProgramDesc>(c_program);
+    return originProgramDesc;
 
-            lod[i] = tmp;
-        }
+}
 
-        // 3. tensor version
-        uint32_t tensor_version = *reinterpret_cast<uint32_t *>(*data);
-        // write tensor version
-        fwrite(&tensor_version, sizeof(uint32_t), 1, out_file);
-        (*data) += sizeof(uint32_t);
-
-        // 4. tensor desc
-        int32_t size = *reinterpret_cast<int32_t *>(*data);
-        // write tensor desc
-        fwrite(&size, sizeof(int32_t), 1, out_file);
-        (*data) += sizeof(int32_t);
-
-        std::unique_ptr<char[]> buf(new char[size]);
-        for (int m = 0; m < size; ++m) {
-            buf.get()[m] = (*data)[m];
-        }
-        fwrite(buf.get(), sizeof(char), size, out_file);
-        (*data) += (sizeof(char) * size);
+void LoadWithDump(const paddle_mobile::framework::VarDesc &var_desc, char *dataP, FILE *out_file) {
+    // 1. version
+    uint32_t version = *reinterpret_cast<uint32_t *>(dataP);
 
-        const paddle_mobile::framework::TensorDesc &desc = var_desc.Tensor_desc();
-        int memory_size = 1;
-        for (auto l : desc.Dims()) {
-            memory_size *= l;
-        }
-        tensor->Resize(paddle_mobile::framework::make_ddim(desc.Dims()));
-
-        void *memory = tensor;
-        int type_size = 0;
-        switch (desc.DataType()) {
-            case paddle_mobile::framework::VARTYPE_TYPE_FP16:
-                type_size = 2;
-                break;
-            case paddle_mobile::framework::VARTYPE_TYPE_FP32:
-                type_size = 4;
-                memory = tensor->mutable_data<float>();
-                break;
-            case paddle_mobile::framework::VARTYPE_TYPE_FP64:
-                type_size = 8;
-                break;
-            case paddle_mobile::framework::VARTYPE_TYPE_INT32:
-                type_size = 4;
-                break;
-            case paddle_mobile::framework::VARTYPE_TYPE_INT64:
-                type_size = 8;
-                break;
-            case paddle_mobile::framework::VARTYPE_TYPE_BOOL:
-                type_size = 1;
-                break;
-            default:
-                break;
-        }
-        for (int n = 0; n < memory_size * type_size; ++n) {
-            static_cast<char *>(memory)[n] = (*data)[n];
-        }
-        (*data) += (sizeof(char) * memory_size * type_size);
-        // for float 32
-        float min_value = std::numeric_limits<float>::max();
-        float max_value = std::numeric_limits<float>::min();
-        for (int k = 0; k < memory_size; ++k) {
-            min_value = std::min(min_value, static_cast<float *> (memory)[k]);
-            max_value = std::max(max_value, static_cast<float *> (memory)[k]);
-        }
-        fwrite(&min_value, sizeof(float), 1, out_file);
-        fwrite(&max_value, sizeof(float), 1, out_file);
-        for (int g = 0; g < memory_size; ++g) {
-            float value = static_cast<float *> (memory)[g];
-            uint8_t factor = (uint8_t) round((value - min_value) / (max_value - min_value) * 255);
-            fwrite(&factor, sizeof(uint8_t), 1, out_file);
+    // write version
+    fwrite(&version, kSize32, 1, out_file);
+
+    dataP += kSize32;
+
+    // 2 Lod information
+    auto *lod_level_ptr = new uint64_t();
+    memcpy(lod_level_ptr, dataP, kSize64);
+
+    uint64_t lod_level = 0;
+    // write lod Information
+    fwrite(&lod_level, kSize64, 1, out_file);
+    delete lod_level_ptr;
+
+    dataP += kSize64;
+
+    for (uint64_t i = 0; i < lod_level; ++i) {
+        uint64_t size = *reinterpret_cast<uint64_t *>(dataP);
+        // write lod size
+        fwrite(&size, kSize64, 1, out_file);
+        (dataP) += kSize64;
+
+        std::vector<size_t> tmp(size / sizeof(size_t));
+        for (unsigned long &k : tmp) {
+            k = *reinterpret_cast<size_t *>(dataP);
+            (dataP) += sizeof(size_t);
         }
+        // write lod size vector
+        fwrite(&tmp, sizeof(size_t), tmp.size(), out_file);
+    }
+
+    // 3. tensor version
+    uint32_t tensor_version = *reinterpret_cast<uint32_t *>(dataP);
+    // write tensor version
+    fwrite(&tensor_version, kSize32, 1, out_file);
+    (dataP) += kSize32;
+
+    // 4. tensor desc
+    int32_t size = *reinterpret_cast<int32_t *>(dataP);
+    // write tensor desc
+    fwrite(&size, sizeof(int32_t), 1, out_file);
+    (dataP) += sizeof(int32_t);
+
+    std::unique_ptr<char[]> buf(new char[size]);
+    for (int m = 0; m < size; ++m) {
+        buf.get()[m] = (dataP)[m];
+    }
+
+    fwrite(buf.get(), sizeof(char), static_cast<size_t>(size), out_file);
+    (dataP) += (sizeof(char) * size);
+
+    const paddle_mobile::framework::TensorDesc &desc = var_desc.Tensor_desc();
+    int memory_size = 1;
+    for (auto l : desc.Dims()) {
+        memory_size *= l;
+    }
+
+    void *memory = nullptr;
+    int type_size = 0;
+    switch (desc.DataType()) {
+        case paddle_mobile::framework::VARTYPE_TYPE_FP16:
+            type_size = 2;
+            break;
+        case paddle_mobile::framework::VARTYPE_TYPE_FP32:
+            type_size = 4;
+            break;
+        case paddle_mobile::framework::VARTYPE_TYPE_FP64:
+            type_size = 8;
+            break;
+        case paddle_mobile::framework::VARTYPE_TYPE_INT32:
+            type_size = 4;
+            break;
+        case paddle_mobile::framework::VARTYPE_TYPE_INT64:
+            type_size = 8;
+            break;
+        case paddle_mobile::framework::VARTYPE_TYPE_BOOL:
+            type_size = 1;
+            break;
+        default:
+            break;
+    }
+    size_t tensorSize = sizeof(char) * memory_size * type_size;
+
+    memory = new char[tensorSize];
+
+    for (int n = 0; n < tensorSize; ++n) {
+        static_cast<char *>(memory)[n] = (dataP)[n];
+    }
+    dataP += tensorSize;
+
+    // for float 32
+    float min_value = std::numeric_limits<float>::max();
+    float max_value = std::numeric_limits<float>::min();
 
+    for (int k = 0; k < memory_size; ++k) {
+        min_value = std::min(min_value, static_cast<float *> (memory)[k]);
+        max_value = std::max(max_value, static_cast<float *> (memory)[k]);
+    }
+
+    fwrite(&min_value, sizeof(float), 1, out_file);
+    fwrite(&max_value, sizeof(float), 1, out_file);
 
+    for (int g = 0; g < memory_size; ++g) {
+        float value = static_cast<float *> (memory)[g];
+        auto factor = (uint8_t) round((value - min_value) / (max_value - min_value) * 255);
+        fwrite(&factor, sizeof(uint8_t), 1, out_file);
     }
+}
 
-    void quantificate_combined(std::string model_path, std::string param_path, std::string param_min_path){
-        paddle_mobile::Loader<paddle_mobile::CPU,paddle_mobile::Precision::FP32 > loader;
-        bool optimize = true;
-        auto program = loader.Load(model_path, param_path, optimize);
-        char *origin_data = Get_binary_data(program.para_path);
-        char *data = origin_data;
-        FILE *out_file = fopen(param_min_path.c_str(), "wb");
-        for (const auto &block : program.originProgram->Blocks()) {
-            for (const auto &var_desc : block->Vars()) {
-                auto var = program.scope->Var(var_desc->Name());
-                if(var_desc ->Persistable()) {
-                    auto tensor = var->template GetMutable<paddle_mobile::framework::LoDTensor>();
-                    if (var_desc->Name() == "feed" || var_desc->Name() == "fetch") {
-                        continue;
-                    }
-                    LoadWithDump(*var_desc, tensor, &data,out_file);
+void
+quantificate_combined(const std::string &model_path, const std::string &param_path, const std::string &param_min_path) {
+
+    auto program = loadParams(model_path);
+    char *origin_data = Get_binary_data(param_path);
+    char *data = origin_data;
+    FILE *out_file = fopen(param_min_path.c_str(), "wb");
+    for (const auto &block : program->Blocks()) {
+        for (const auto &var_desc : block->Vars()) {
+            if (var_desc->Persistable()) {
+                if (var_desc->Name() == "feed" || var_desc->Name() == "fetch") {
+                    continue;
                 }
+                LoadWithDump(*var_desc, data, out_file);
             }
         }
-        fclose(out_file);
-        delete origin_data;
-
     }
-    void quantificate_seperated(std::string model_dir, std::string param_min_path) {
-        paddle_mobile::Loader<paddle_mobile::CPU,paddle_mobile::Precision::FP32 > loader;
-        bool optimize = true;
-        auto program = loader.Load(model_dir, optimize);
-        std::string shell_command = "mkdir "+param_min_path;
-        system(shell_command.c_str());
-        for (const auto &block : program.originProgram->Blocks()) {
-            for (const auto &var_desc : block->Vars()) {
-                auto var = program.scope->Var(var_desc->Name());
-                if(var_desc ->Persistable()) {
-                    auto tensor = var->template GetMutable<paddle_mobile::framework::LoDTensor>();
-                    if (var_desc->Name() == "feed" || var_desc->Name() == "fetch") {
-                        continue;
-                    }
-                    std::string file_name = param_min_path +"/"+ var_desc->Name();
-
-                    FILE *out_file = fopen(file_name.c_str(), "wb");
-                    char *origin_data =
-                            Get_binary_data(program.model_path + "/" + var_desc->Name());
-                    char *data = origin_data;
-                    LoadWithDump(*var_desc, tensor, &data,out_file);
-                    delete origin_data;
-                    fclose(out_file);
+    fclose(out_file);
+    delete origin_data;
+
+}
+
+void quantificate_seperated(const std::string model_dir, const std::string param_min_path) {
+
+    auto program = loadParams(model_dir + "/__model__");
+
+    std::string shell_command = "mkdir " + param_min_path;
+    system(shell_command.c_str());
+
+    for (const auto &block : program->Blocks()) {
+        for (const auto &var_desc : block->Vars()) {
+            if (var_desc->Persistable()) {
+                if (var_desc->Name() == "feed" || var_desc->Name() == "fetch") {
+                    continue;
                 }
+                std::string file_name = param_min_path + "/" + var_desc->Name();
+                FILE *out_file = fopen(file_name.c_str(), "wb");
+                char *origin_data = Get_binary_data(model_dir + "/" + var_desc->Name());
+                char *data = origin_data;
+                LoadWithDump(*var_desc, data, out_file);
+                delete origin_data;
+                fclose(out_file);
             }
         }
+    }
+
+}
+
+
+int main(int argc, char **argv) {
+
+    const std::string kNoteEg = "( eg:  ./quantify 1 your_combined_model_path output_path  or  ./quantify 0 your_seperated_model_path output_path)";
 
+    PADDLE_MOBILE_ENFORCE(argc > 1, "wee need params.%s ", kNoteEg.c_str());
+
+    std::string action_type = argv[1];
+    PADDLE_MOBILE_ENFORCE(argc > 1 && (action_type) == "1" || action_type == "0",
+                          "only 1 or 2 supported, current is %s %s ",
+                          action_type.c_str(),
+                          kNoteEg.c_str());
+
+    PADDLE_MOBILE_ENFORCE(argc > 2, "we need your model path. %s ", kNoteEg.c_str());
+    std::string base_path = argv[2];
+
+    PADDLE_MOBILE_ENFORCE(argc > 3, "we need your output path. %s ", kNoteEg.c_str());
+    std::string output_path = argv[3];
+
+    if (action_type == "0") {
+        // for seperated
+        const std::string &seperated_min_dir = output_path;
+        quantificate_seperated(base_path, seperated_min_dir);
+        return 0;
     }
-    int main() {
-        std::string filename = "params_min";
-        std::string model_path = g_googlenet_combine + "/model";
-        std::string param_path = g_googlenet_combine + "/params";
-        std::string dirname = "param_min_dir";
-        std::string model_dir = g_googlenet;
-//        quantificate_combined(model_path, param_path,filename);
-        quantificate_seperated(model_dir, dirname);
+
+    if (action_type == "1") {
+        // for combined
+        const std::string &combined_min_dir = output_path;
+        std::string model_path = base_path + "/model";
+        std::string param_path = base_path + "/params";
+        quantificate_combined(model_path, param_path, combined_min_dir);
 
         return 0;
     }
 
+    return -1;
+}
+
 
 
 

tools/quantification/src/block_desc_local.cpp

+/* 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. */
+
+//
+// Created by 谢柏渊 on 2018/7/25.
+//
+#include "src/block_desc_local.h"
+#include <algorithm>
+#include <memory>
+#include <vector>
+
+#include "src/framework.pb-c.h"
+
+std::vector<std::shared_ptr<paddle_mobile::framework::VarDesc>>
+BlockDesc::Vars() const {
+  return vars_;
+}
+
+BlockDesc::BlockDesc(PaddleMobile__Framework__Proto__BlockDesc *desc)
+    : index_(desc->idx), parent_index_(desc->idx) {
+  for (int i = 0; i < desc->n_vars; ++i) {
+    PaddleMobile__Framework__Proto__VarDesc *var_desc = desc->vars[i];
+    vars_.emplace_back(std::shared_ptr<paddle_mobile::framework::VarDesc>(
+        new paddle_mobile::framework::VarDesc(var_desc)));
+  }
+
+  std::sort(vars_.begin(), vars_.end(),
+            [](std::shared_ptr<paddle_mobile::framework::VarDesc> left,
+               std::shared_ptr<paddle_mobile::framework::VarDesc> right) {
+              return left->Name() < right->Name();
+            });
+
+  //        for (int j = 0; j < desc->n_ops; ++j) {
+  //            PaddleMobile__Framework__Proto__OpDesc *op_desc = desc->ops[j];
+  //            ops_.emplace_back(new OpDesc(op_desc));
+  //        }
+}

tools/quantification/src/block_desc_local.h

+/* 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. */
+
+//
+// Created by 谢柏渊 on 2018/7/25.
+//
+
+#ifndef TOOLS_QUANTIFICATION_SRC_BLOCK_DESC_LOCAL_H_
+#define TOOLS_QUANTIFICATION_SRC_BLOCK_DESC_LOCAL_H_
+
+#include <vector>
+#include "src/var_desc.h"
+
+class BlockDesc {
+ public:
+  friend class Node;
+  friend class ProgramOptimize;
+  BlockDesc() {}
+  explicit BlockDesc(PaddleMobile__Framework__Proto__BlockDesc *desc);
+
+  const int &ID() const { return index_; }
+
+  const bool &MultiThread() const { return multi_thread_; }
+
+  const int &Parent() const { return parent_index_; }
+
+  bool operator==(const BlockDesc &in_block) const {
+    return this->ID() == in_block.ID() && this->Parent() == in_block.Parent();
+  }
+
+  bool operator<(const BlockDesc &in_block) const {
+    return this->ID() < in_block.ID() && this->Parent() < in_block.Parent();
+  }
+
+  std::vector<std::shared_ptr<paddle_mobile::framework::VarDesc>> Vars() const;
+
+ private:
+  int index_;
+  bool multi_thread_;
+  int parent_index_;
+  std::vector<std::shared_ptr<paddle_mobile::framework::VarDesc>> vars_;
+};
+
+#endif  // TOOLS_QUANTIFICATION_SRC_BLOCK_DESC_LOCAL_H_

tools/quantification/src/enforce.h

+/* 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
+
+#ifdef ENABLE_EXCEPTION
+#include <stdio.h>
+#include <exception>
+#include <string>
+
+#endif
+
+namespace paddle_mobile {
+
+#ifdef ENABLE_EXCEPTION
+struct PaddleMobileException : public std::exception {
+  const std::string exception_prefix = "paddle mobile C++ Exception: \n";
+  std::string message;
+
+  PaddleMobileException(const char *header, const char *detail,
+                        const char *file, const int line) {
+    char buffer[1500];
+    snprintf(buffer, sizeof(buffer),
+             "%s| %s \n| [in file] : %s\n| [on line] : %d\n| [detail]  : %s\n",
+             exception_prefix.c_str(), header, file, line, detail);
+    message = std::string(buffer);
+  }
+  const char *what() const noexcept { return message.c_str(); }
+};
+
+#define PADDLE_MOBILE_THROW_EXCEPTION(...)                                 \
+  {                                                                        \
+    char buffer[1000];                                                     \
+    snprintf(buffer, sizeof(buffer), __VA_ARGS__);                         \
+    std::string detail(buffer);                                            \
+    throw paddle_mobile::PaddleMobileException("Custom Exception", buffer, \
+                                               __FILE__, __LINE__);        \
+  }
+
+#define PADDLE_MOBILE_ENFORCE(stat, ...)                                      \
+  {                                                                           \
+    if (stat) {                                                               \
+    } else {                                                                  \
+      char buffer[1000];                                                      \
+      snprintf(buffer, sizeof(buffer), __VA_ARGS__);                          \
+      std::string detail(buffer);                                             \
+      throw paddle_mobile::PaddleMobileException("paddle-mobile enforce",     \
+                                                 buffer, __FILE__, __LINE__); \
+    }                                                                         \
+  }
+#else
+#define PADDLE_MOBILE_THROW_EXCEPTION(...)
+#define PADDLE_MOBILE_ENFORCE(stat, ...)
+#endif
+
+}  // namespace paddle_mobile

tools/quantification/src/program_desc.cpp

+/* 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. */
+
+//
+// Created by 谢柏渊 on 2018/7/25.
+//
+
+#include "src/program_desc.h"
+#include <vector>
+
+ProgramDesc::ProgramDesc(PaddleMobile__Framework__Proto__ProgramDesc *desc) {
+  for (int i = 0; i < desc->n_blocks; ++i) {
+    blocks_.emplace_back(std::make_shared<BlockDesc>(desc->blocks[i]));
+  }
+}
+
+const std::vector<std::shared_ptr<BlockDesc>> ProgramDesc::Blocks() {
+  return blocks_;
+}

tools/quantification/src/program_desc.h

+/* 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. */
+
+//
+// Created by 谢柏渊 on 2018/7/25.
+//
+
+#ifndef TOOLS_QUANTIFICATION_SRC_PROGRAM_DESC_H_
+#define TOOLS_QUANTIFICATION_SRC_PROGRAM_DESC_H_
+
+#include <memory>
+#include <vector>
+#include "src/block_desc_local.h"
+#include "src/framework.pb-c.h"
+
+class ProgramDesc {
+ public:
+  //    friend class Node;
+  //
+  //    friend class ProgramOptimize;
+
+  explicit ProgramDesc(PaddleMobile__Framework__Proto__ProgramDesc *desc);
+
+  const std::vector<std::shared_ptr<BlockDesc>> Blocks();
+
+ private:
+  std::vector<std::shared_ptr<BlockDesc>> blocks_;
+};
+
+#endif  // TOOLS_QUANTIFICATION_SRC_PROGRAM_DESC_H_

tools/quantification/src/tensor_desc.h

+/* 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 <vector>
+
+#include "src/framework.pb-c.h"
+
+namespace paddle_mobile {
+namespace framework {
+
+enum VarType_Type {
+  VARTYPE_TYPE_BOOL = 0,
+  VARTYPE_TYPE_INT16 = 1,
+  VARTYPE_TYPE_INT32 = 2,
+  VARTYPE_TYPE_INT64 = 3,
+  VARTYPE_TYPE_FP16 = 4,
+  VARTYPE_TYPE_FP32 = 5,
+  VARTYPE_TYPE_FP64 = 6,
+  VARTYPE_TYPE_LOD_TENSOR = 7,
+  VARTYPE_TYPE_SELECTED_ROWS = 8,
+  VARTYPE_TYPE_FEED_MINIBATCH = 9,
+  VARTYPE_TYPE_FETCH_LIST = 10,
+  VARTYPE_TYPE_STEP_SCOPES = 11,
+  VARTYPE_TYPE_STEP_LOD_RANK_TABLE = 12,
+  VARTYPE_TYPE_STEP_LOD_TENSOR_ARRAY = 13,
+  VARTYPE_TYPE_STEP_PLACE_LIST = 14,
+  VARTYPE_TYPE_READER = 15,
+  VARTYPE_TYPE_CHANNEL = 16,
+  VARTYPE_TYPE_RAW = 17,
+  VARTYPE_TYPE_TUPLE = 18
+};
+
+class TensorDesc {
+ public:
+  TensorDesc() = default;
+  TensorDesc(const TensorDesc &desc) {
+    this->dims_ = desc.dims_;
+    this->data_type_ = desc.data_type_;
+  }
+
+  explicit TensorDesc(
+      PaddleMobile__Framework__Proto__VarType__TensorDesc *desc) {
+    for (int i = 0; i < desc->n_dims; ++i) {
+      int64_t d = desc->dims[i];
+      dims_.emplace_back(d);
+    }
+    data_type_ = (VarType_Type)desc->data_type;
+  }
+
+  std::vector<int64_t> Dims() const { return dims_; }
+  VarType_Type DataType() const { return data_type_; }
+
+ private:
+  std::vector<int64_t> dims_;
+  VarType_Type data_type_;
+};
+
+}  // namespace framework
+}  // namespace paddle_mobile