Merge pull request #392 from codeWorm2015/develop

fix #391 add code comment

src/io/io.cpp

@@ -68,93 +68,6 @@ static size_t ReadBuffer(const char *file_name, uint8_t **out) {
   return cur_len;
 }
 
-template <typename Dtype, Precision P>
-void Loader<Dtype, P>::LoadVar(framework::Variable *variable,
-                               const framework::VarDesc &var_desc,
-                               const std::string &file_path) {
-  auto tensor = variable->GetMutable<framework::LoDTensor>();
-  char *data = Get_binary_data(file_path);
-
-  // 1. version
-  uint32_t version = *(uint32_t *)data;
-  data += sizeof(uint32_t);
-
-  // 2 Lod information
-  uint32_t lod_level = *(uint64_t *)data;
-  data += sizeof(uint64_t);
-
-  auto &lod = *tensor->mutable_lod();
-  lod.resize(lod_level);
-  for (uint64_t i = 0; i < lod_level; ++i) {
-    uint32_t size = *(uint64_t *)data;
-    data += sizeof(uint64_t);
-
-    std::vector<size_t> tmp(size / sizeof(size_t));
-
-    for (int k = 0; k < tmp.size(); ++k) {
-      tmp[k] = *(size_t *)data;
-    }
-    lod[i] = tmp;
-  }
-
-  // 3. tensor version
-  uint32_t tensor_version = *(uint32_t *)data;
-  data += sizeof(uint32_t);
-
-  // 4. tensor desc
-  uint32_t size = *(int32_t *)data;
-  data += sizeof(int32_t);
-
-  std::unique_ptr<char[]> buf(new char[size]);
-
-  for (int m = 0; m < size; ++m) {
-    buf.get()[m] = data[m];
-  }
-
-  const framework::TensorDesc &desc = var_desc.Tensor_desc();
-
-  PaddleMobile__Framework__Proto__VarType__TensorDesc *tensor_desc = NULL;
-
-  int memory_size = 1;
-  for (auto l : desc.Dims()) {
-    memory_size *= l;
-  }
-
-  tensor->Resize(framework::make_ddim(desc.Dims()));
-
-  void *memory = tensor;
-  int type_size = 0;
-  switch (desc.DataType()) {
-    case framework::VARTYPE_TYPE_FP16:
-      type_size = 2;
-      break;
-    case framework::VARTYPE_TYPE_FP32:
-      type_size = 4;
-      memory = tensor->mutable_data<float>();
-      break;
-    case framework::VARTYPE_TYPE_FP64:
-      type_size = 8;
-      break;
-    case framework::VARTYPE_TYPE_INT32:
-      type_size = 4;
-      break;
-    case framework::VARTYPE_TYPE_INT64:
-      type_size = 8;
-      break;
-    case 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];
-  }
-
-  delete data;
-}
-
 template <typename Dtype, Precision P>
 const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
     const std::string &dirname, bool optimize) {

src/io/io.h

@@ -30,9 +30,17 @@ namespace paddle_mobile {
 template <typename Dtype = CPU, Precision P = Precision::FP32>
 class Loader {
  public:
+  /*
+   * @b load separate format fluid model
+   * @b 加载分开形式的 fluid 模型
+   * */
   const framework::Program<Dtype, P> Load(const std::string &dirname,
                                           bool optimize = false);
 
+  /*
+   * @b load combine format fluid mode
+   * @b 加载结合在一起格式的模型
+   * */
   const framework::Program<Dtype, P> Load(const std::string &model_path,
                                           const std::string &para_path,
                                           bool optimize = false);
@@ -40,9 +48,6 @@ class Loader {
  private:
   const framework::Program<Dtype, P> LoadProgram(const std::string &model_path,
                                                  bool optimize = false);
-  void LoadVar(framework::Variable *variable,
-               const framework::VarDesc &var_desc,
-               const std::string &file_path);
 };
 
 template <typename Dtype = CPU, Precision P = Precision::FP32>
@@ -50,17 +55,28 @@ class Executor {
  public:
   typedef typename PrecisionTrait<P>::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<Dtype> p, int batch_size = 1,
            bool use_optimize = true);
 
+  /*
+   * @b to predict
+   * */
   std::shared_ptr<framework::Tensor> 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<Ptype> Predict(const std::vector<Ptype> &input,
                              const std::vector<int64_t> &dims);
 
  protected:
   Executor() = default;
-
   void InitMemory();
   void LoadMemory(const framework::VarDesc var_desc,
                   framework::LoDTensor *tensor, char *&data);

tools/build.sh

@@ -70,7 +70,6 @@ build_for_android() {
         -DCMAKE_TOOLCHAIN_FILE="${TOOLCHAIN_FILE}" \
         -DANDROID_PLATFORM="${ANDROID_PLATFORM_VERSION}" \
         -DCMAKE_CXX_FLAGS="${CXX_FLAGS}" \
-        -DCMAKE_LDFLAGS="-Wl,--gc-sections --icf=safe" \
         -DANDROID_STL=c++_static \
         -DANDROID=true \
         -D"${NET}=true" \