Merge pull request #170 from allonli/develop

fix #171 update clang-format & update code stylee. 

.clang-format

+---
+Language:        Cpp
+BasedOnStyle:  LLVM
+Standard:  Cpp11 
+IndentWidth: 4
+NamespaceIndentation: All
+...

.pre-commit-config.yaml

@@ -6,6 +6,7 @@ repos:
         files: (src).*\.(md|py|mm|swift|java|c|cc|cxx|cpp|cu|h|hpp|hxx)$
     -   id: remove-tabs
         files: (src).*\.(md|py|mm|swift|java|c|cc|cxx|cpp|cu|h|hpp|hxx)$
+
 -   repo: https://github.com/pre-commit/pre-commit-hooks
     sha: 5bf6c09bfa1297d3692cadd621ef95f1284e33c0
     hooks:
@@ -18,11 +19,21 @@ repos:
         files: (src).*\.(md|py|mm|swift|java|c|cc|cxx|cpp|cu|h|hpp|hxx)$
     -   id: trailing-whitespace
         files: (src).*\.(md|py|mm|swift|java|c|cc|cxx|cpp|cu|h|hpp|hxx)$
+
 -   repo: local
     hooks:
     -   id: clang-format-with-version-check
         name: clang-format
         description: Format files with ClangFormat.
-        entry: bash .clang_format.hook -i
+        entry: bash ./tools/pre-commit.hooks/.clang_format.hook -i
         language: system
         files: (src).*\.(c|cc|cxx|cpp|h|hpp|hxx)$
+
+#-   repo: local
+#    hooks:
+#    -   id: copyright_checker
+#        name: copyright_checker
+#        entry: python ./tools/pre-commit.hooks/.copyright.hook
+#        language: system
+#        files: (src).*\.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto|py)$
+#        exclude: (?!.*third_party)^.*$ | (?!.*book)^.*$

README.md

-# Paddle-Mobile
+# Paddle-Mobile 
+
+![License MIT](https://img.shields.io/github/license/mashape/apistatus.svg)  [![Build Status](https://travis-ci.org/PaddlePaddle/paddle-mobile.svg?branch=develop&longCache=true&style=flat-square)](https://travis-ci.org/PaddlePaddle/paddle-mobile)
+
+
 
 This project is used to develop the next version deep learning freamwork for mobile device.
 

src/common/type_define.h

@@ -23,30 +23,31 @@ SOFTWARE.
 
 namespace paddle_mobile {
 
-namespace framework {
-template <typename Dtype> class OperatorBase;
-class OpDesc;
-class BlockDesc;
-class InferShapeContext;
-}
-
-using VariableNameMap = std::map<std::string, std::vector<std::string>>;
-
-template <typename Dtype>
-using OpCreator = std::function<framework::OperatorBase<Dtype> *(
-    const std::string & /*type*/, const VariableNameMap & /*inputs*/,
-    const VariableNameMap & /*outputs*/,
-    const framework::AttributeMap & /*attrs*/)>;
-
-using GradOpMakerFN =
-    std::function<std::vector<std::unique_ptr<framework::OpDesc>>(
-        const framework::OpDesc &,
-        const std::unordered_set<std::string> & /*no_grad_set*/,
-        std::unordered_map<std::string, std::string> * /*grad_to_var*/,
-        const std::vector<framework::BlockDesc *> &grad_block)>;
-
-using InferVarTypeFN = std::function<void(const framework::OpDesc & /*op_desc*/,
-                                          framework::BlockDesc * /*block*/)>;
-
-using InferShapeFN = std::function<void(framework::InferShapeContext *)>;
+    namespace framework {
+        template <typename Dtype> class OperatorBase;
+        class OpDesc;
+        class BlockDesc;
+        class InferShapeContext;
+    }
+
+    using VariableNameMap = std::map<std::string, std::vector<std::string>>;
+
+    template <typename Dtype>
+    using OpCreator = std::function<framework::OperatorBase<Dtype> *(
+        const std::string & /*type*/, const VariableNameMap & /*inputs*/,
+        const VariableNameMap & /*outputs*/,
+        const framework::AttributeMap & /*attrs*/)>;
+
+    using GradOpMakerFN =
+        std::function<std::vector<std::unique_ptr<framework::OpDesc>>(
+            const framework::OpDesc &,
+            const std::unordered_set<std::string> & /*no_grad_set*/,
+            std::unordered_map<std::string, std::string> * /*grad_to_var*/,
+            const std::vector<framework::BlockDesc *> &grad_block)>;
+
+    using InferVarTypeFN =
+        std::function<void(const framework::OpDesc & /*op_desc*/,
+                           framework::BlockDesc * /*block*/)>;
+
+    using InferShapeFN = std::function<void(framework::InferShapeContext *)>;
 };

src/common/types.h

@@ -19,45 +19,45 @@ SOFTWARE.
 #pragma once;
 
 namespace paddle_mobile {
-enum class Precision : int { FP32 = 0 };
+    enum class Precision : int { FP32 = 0 };
 
-//! device type
-enum DeviceTypeEnum { kINVALID = -1, kCPU = 0, kFPGA = 1, kGPU_MALI = 2 };
+    //! device type
+    enum DeviceTypeEnum { kINVALID = -1, kCPU = 0, kFPGA = 1, kGPU_MALI = 2 };
 
-template <DeviceTypeEnum T> struct DeviceType {};
+    template <DeviceTypeEnum T> struct DeviceType {};
 
-typedef DeviceType<kCPU> CPU;
-typedef DeviceType<kFPGA> FPGA;
-typedef DeviceType<kGPU_MALI> GPU_MALI;
+    typedef DeviceType<kCPU> CPU;
+    typedef DeviceType<kFPGA> FPGA;
+    typedef DeviceType<kGPU_MALI> GPU_MALI;
 
-//! data type
-enum DataType {
-  PM_INVALID = -1,
-  PM_HALF = 0,
-  PM_FLOAT = 1,
-  PM_DOUBLE = 2,
-  PM_INT8 = 3,
-  PM_INT16 = 4,
-  PM_INT32 = 5,
-  PM_INT64 = 6,
-  PM_UINT8 = 7,
-  PM_UINT16 = 8,
-  PM_UINT32 = 9,
-  PM_STRING = 10,
-  PM_BOOL = 11,
-  PM_SHAPE = 12,
-  PM_TENSOR = 13
-};
-//!
-enum PMStatus {
-  PMSuccess = 0xFF,        /*!< No errors */
-  PMNotInitialized = 0x01, /*!< Data not initialized. */
-  PMInvalidValue = 0x02,   /*!< Incorrect variable value. */
-  PMMemAllocFailed = 0x03, /*!< Memory allocation error. */
-  PMUnKownError = 0x04,    /*!< Unknown error. */
-  PMOutOfAuthority = 0x05, /*!< Try to modified data not your own*/
-  PMOutOfMem = 0x06,       /*!< OOM error*/
-  PMUnImplError = 0x07,    /*!< Unimplement error. */
-  PMWrongDevice = 0x08     /*!< un-correct device. */
-};
+    //! data type
+    enum DataType {
+        PM_INVALID = -1,
+        PM_HALF = 0,
+        PM_FLOAT = 1,
+        PM_DOUBLE = 2,
+        PM_INT8 = 3,
+        PM_INT16 = 4,
+        PM_INT32 = 5,
+        PM_INT64 = 6,
+        PM_UINT8 = 7,
+        PM_UINT16 = 8,
+        PM_UINT32 = 9,
+        PM_STRING = 10,
+        PM_BOOL = 11,
+        PM_SHAPE = 12,
+        PM_TENSOR = 13
+    };
+    //!
+    enum PMStatus {
+        PMSuccess = 0xFF,        /*!< No errors */
+        PMNotInitialized = 0x01, /*!< Data not initialized. */
+        PMInvalidValue = 0x02,   /*!< Incorrect variable value. */
+        PMMemAllocFailed = 0x03, /*!< Memory allocation error. */
+        PMUnKownError = 0x04,    /*!< Unknown error. */
+        PMOutOfAuthority = 0x05, /*!< Try to modified data not your own*/
+        PMOutOfMem = 0x06,       /*!< OOM error*/
+        PMUnImplError = 0x07,    /*!< Unimplement error. */
+        PMWrongDevice = 0x08     /*!< un-correct device. */
+    };
 }

src/common/variant.h

@@ -21,79 +21,79 @@ SOFTWARE.
 #pragma once
 
 namespace paddle_mobile {
-template <int ID, typename Type> struct IDToType { typedef Type type_t; };
+    template <int ID, typename Type> struct IDToType { typedef Type type_t; };
 
-template <typename F, typename... Ts> struct VariantHelper {
-  static const size_t size = sizeof(F) > VariantHelper<Ts...>::size
-                                 ? sizeof(F)
-                                 : VariantHelper<Ts...>::size;
+    template <typename F, typename... Ts> struct VariantHelper {
+        static const size_t size = sizeof(F) > VariantHelper<Ts...>::size
+                                       ? sizeof(F)
+                                       : VariantHelper<Ts...>::size;
 
-  inline static void Destroy(size_t id, void *data) {
-    if (id == typeid(F).hash_code()) {
-      reinterpret_cast<F *>(data)->~F();
-    } else {
-      VariantHelper<Ts...>::Destroy(id, data);
-    }
-  }
-};
+        inline static void Destroy(size_t id, void *data) {
+            if (id == typeid(F).hash_code()) {
+                reinterpret_cast<F *>(data)->~F();
+            } else {
+                VariantHelper<Ts...>::Destroy(id, data);
+            }
+        }
+    };
 
-template <typename F> struct VariantHelper<F> {
-  static const size_t size = sizeof(F);
-  inline static void Destroy(size_t id, void *data) {
-    if (id == typeid(F).hash_code()) {
-      //              reinterpret_cast<F*>(data)->~F();
-    } else {
-      //              std::cout << "未匹配到 " << std::endl;
-    }
-  }
-};
+    template <typename F> struct VariantHelper<F> {
+        static const size_t size = sizeof(F);
+        inline static void Destroy(size_t id, void *data) {
+            if (id == typeid(F).hash_code()) {
+                //              reinterpret_cast<F*>(data)->~F();
+            } else {
+                //              std::cout << "未匹配到 " << std::endl;
+            }
+        }
+    };
 
-template <size_t size> class RawData {
-public:
-  char data[size];
-  RawData() {}
-  RawData(const RawData &raw_data) { strcpy(data, raw_data.data); }
-  //      void operator=(const RawData &raw_data){
-  //        strcpy(data, raw_data.data);
-  //      }
-};
+    template <size_t size> class RawData {
+      public:
+        char data[size];
+        RawData() {}
+        RawData(const RawData &raw_data) { strcpy(data, raw_data.data); }
+        //      void operator=(const RawData &raw_data){
+        //        strcpy(data, raw_data.data);
+        //      }
+    };
 
-template <typename... Ts> struct Variant {
-  Variant(const Variant &variant) {
-    //        std::cout << " 赋值构造函数 " << std::endl;
-    type_id = variant.type_id;
-    data = variant.data;
-  }
+    template <typename... Ts> struct Variant {
+        Variant(const Variant &variant) {
+            //        std::cout << " 赋值构造函数 " << std::endl;
+            type_id = variant.type_id;
+            data = variant.data;
+        }
 
-  Variant() : type_id(invalid_type()) {}
-  ~Variant() {
-    //        helper::Destroy(type_id, &data);
-  }
+        Variant() : type_id(invalid_type()) {}
+        ~Variant() {
+            //        helper::Destroy(type_id, &data);
+        }
 
-  template <typename T, typename... Args> void Set(Args &&... args) {
-    helper::Destroy(type_id, &data);
-    new (&data) T(std::forward<Args>(args)...);
-    type_id = typeid(T).hash_code();
-  }
+        template <typename T, typename... Args> void Set(Args &&... args) {
+            helper::Destroy(type_id, &data);
+            new (&data) T(std::forward<Args>(args)...);
+            type_id = typeid(T).hash_code();
+        }
 
-  template <typename T> T &Get() const {
-    if (type_id == typeid(T).hash_code()) {
-      return *const_cast<T *>(reinterpret_cast<const T *>(&data));
-    } else {
-      //      std::cout << " bad cast in variant " << std::endl;
-      throw std::bad_cast();
-    }
-  }
+        template <typename T> T &Get() const {
+            if (type_id == typeid(T).hash_code()) {
+                return *const_cast<T *>(reinterpret_cast<const T *>(&data));
+            } else {
+                //      std::cout << " bad cast in variant " << std::endl;
+                throw std::bad_cast();
+            }
+        }
 
-  size_t TypeId() const { return type_id; }
+        size_t TypeId() const { return type_id; }
 
-private:
-  static inline size_t invalid_type() { return typeid(void).hash_code(); }
-  typedef VariantHelper<Ts...> helper;
-  size_t type_id;
-  RawData<helper::size> data;
-};
+      private:
+        static inline size_t invalid_type() { return typeid(void).hash_code(); }
+        typedef VariantHelper<Ts...> helper;
+        size_t type_id;
+        RawData<helper::size> data;
+    };
 
-template <typename T> struct Vistor { typedef T type_t; };
+    template <typename T> struct Vistor { typedef T type_t; };
 
 } // namespace paddle_mobile

src/framework/attribute.cpp

@@ -19,5 +19,5 @@ SOFTWARE.
 #include "attribute.h"
 
 namespace paddle_mobile {
-namespace framework {}
+    namespace framework {}
 } // namespace paddle_mobile

src/framework/attribute.h

@@ -22,107 +22,110 @@ SOFTWARE.
 #include "framework.pb.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-class BlockDesc;
+        class BlockDesc;
 
-class Attribute {
-public:
-  static Attribute GetAttrValue(const proto::OpDesc::Attr &attr_desc) {
-    //    std::cout << "begin get attr value" << std::endl;
-    Attribute attr;
-    switch (attr_desc.type()) {
-    case proto::AttrType::BOOLEAN: {
-      attr.Set<bool>(attr_desc.b());
-      break;
-    }
-    case proto::AttrType::INT: {
-      attr.Set<int>(attr_desc.i());
-      break;
-    }
-    case proto::AttrType::FLOAT: {
-      attr.Set<float>(attr_desc.f());
-      break;
-    }
-    case proto::AttrType::STRING: {
-      attr.Set<std::string>(attr_desc.s());
-      break;
-    }
-    case proto::AttrType::BOOLEANS: {
-      std::vector<bool> val(attr_desc.bools_size());
-      for (int i = 0; i < attr_desc.bools_size(); ++i) {
-        val[i] = attr_desc.bools(i);
-      }
-      attr.Set<std::vector<bool>>(val);
-      break;
-    }
-    case proto::AttrType::INTS: {
-      std::vector<int> val(attr_desc.ints_size());
-      for (int i = 0; i < attr_desc.ints_size(); ++i) {
-        val[i] = attr_desc.ints(i);
-      }
-      attr.Set<std::vector<int>>(val);
-      break;
-    }
-    case proto::AttrType::FLOATS: {
-      std::vector<float> val(attr_desc.floats_size());
-      for (int i = 0; i < attr_desc.floats_size(); ++i) {
-        val[i] = attr_desc.floats(i);
-      }
-      attr.Set<std::vector<float>>(val);
-      break;
-    }
-    case proto::AttrType::STRINGS: {
-      std::vector<std::string> val(attr_desc.strings_size());
-      for (int i = 0; i < attr_desc.strings_size(); ++i) {
-        val[i] = attr_desc.strings(i);
-      }
-      attr.Set<std::vector<std::string>>(val);
-      break;
-    }
-    case proto::AttrType::LONG: {
-      attr.Set<int64_t>(attr_desc.l());
-      break;
-    }
-    default:
-      //        std::cout << " not support " << std::endl;
-      break;
-    }
-    //    std::cout << "end get attr value" << std::endl;
-    return attr;
-  }
+        class Attribute {
+          public:
+            static Attribute
+            GetAttrValue(const proto::OpDesc::Attr &attr_desc) {
+                //    std::cout << "begin get attr value" << std::endl;
+                Attribute attr;
+                switch (attr_desc.type()) {
+                case proto::AttrType::BOOLEAN: {
+                    attr.Set<bool>(attr_desc.b());
+                    break;
+                }
+                case proto::AttrType::INT: {
+                    attr.Set<int>(attr_desc.i());
+                    break;
+                }
+                case proto::AttrType::FLOAT: {
+                    attr.Set<float>(attr_desc.f());
+                    break;
+                }
+                case proto::AttrType::STRING: {
+                    attr.Set<std::string>(attr_desc.s());
+                    break;
+                }
+                case proto::AttrType::BOOLEANS: {
+                    std::vector<bool> val(attr_desc.bools_size());
+                    for (int i = 0; i < attr_desc.bools_size(); ++i) {
+                        val[i] = attr_desc.bools(i);
+                    }
+                    attr.Set<std::vector<bool>>(val);
+                    break;
+                }
+                case proto::AttrType::INTS: {
+                    std::vector<int> val(attr_desc.ints_size());
+                    for (int i = 0; i < attr_desc.ints_size(); ++i) {
+                        val[i] = attr_desc.ints(i);
+                    }
+                    attr.Set<std::vector<int>>(val);
+                    break;
+                }
+                case proto::AttrType::FLOATS: {
+                    std::vector<float> val(attr_desc.floats_size());
+                    for (int i = 0; i < attr_desc.floats_size(); ++i) {
+                        val[i] = attr_desc.floats(i);
+                    }
+                    attr.Set<std::vector<float>>(val);
+                    break;
+                }
+                case proto::AttrType::STRINGS: {
+                    std::vector<std::string> val(attr_desc.strings_size());
+                    for (int i = 0; i < attr_desc.strings_size(); ++i) {
+                        val[i] = attr_desc.strings(i);
+                    }
+                    attr.Set<std::vector<std::string>>(val);
+                    break;
+                }
+                case proto::AttrType::LONG: {
+                    attr.Set<int64_t>(attr_desc.l());
+                    break;
+                }
+                default:
+                    //        std::cout << " not support " << std::endl;
+                    break;
+                }
+                //    std::cout << "end get attr value" << std::endl;
+                return attr;
+            }
 
-  Attribute() {}
-  template <typename T, typename... Args> Attribute &Set(Args &&... args) {
-    variant_.Set<T>(args...);
-    return *this;
-  }
+            Attribute() {}
+            template <typename T, typename... Args>
+            Attribute &Set(Args &&... args) {
+                variant_.Set<T>(args...);
+                return *this;
+            }
 
-  template <typename T> T &Get() const { return variant_.Get<T>(); }
+            template <typename T> T &Get() const { return variant_.Get<T>(); }
 
-private:
-  Variant<int, float, std::string, std::vector<int>, std::vector<float>,
-          std::vector<std::string>, bool, std::vector<bool>, BlockDesc *,
-          int64_t>
-      variant_;
-};
+          private:
+            Variant<int, float, std::string, std::vector<int>,
+                    std::vector<float>, std::vector<std::string>, bool,
+                    std::vector<bool>, BlockDesc *, int64_t>
+                variant_;
+        };
 
-using AttributeMap = std::unordered_map<std::string, Attribute>;
+        using AttributeMap = std::unordered_map<std::string, Attribute>;
 
-class AttrReader {
-public:
-  explicit AttrReader(const AttributeMap &attrs) : attrs_(attrs) {}
+        class AttrReader {
+          public:
+            explicit AttrReader(const AttributeMap &attrs) : attrs_(attrs) {}
 
-  template <typename T> inline T Get(const std::string &name) const {
-    //          PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should be in
-    //          AttributeMap",
-    //                         name);
-    return ((Attribute)attrs_.at(name)).Get<T>();
-  }
+            template <typename T> inline T Get(const std::string &name) const {
+                //          PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should
+                //          be in
+                //          AttributeMap",
+                //                         name);
+                return ((Attribute)attrs_.at(name)).Get<T>();
+            }
 
-private:
-  const AttributeMap &attrs_;
-};
+          private:
+            const AttributeMap &attrs_;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/block_desc.cpp

@@ -19,32 +19,32 @@ SOFTWARE.
 #include "block_desc.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-std::vector<std::shared_ptr<VarDesc>> BlockDesc::Vars() const {
-  std::vector<std::shared_ptr<VarDesc>> res;
-  for (const auto &p : vars_) {
-    res.push_back(p.second);
-  }
-  return res;
-}
+        std::vector<std::shared_ptr<VarDesc>> BlockDesc::Vars() const {
+            std::vector<std::shared_ptr<VarDesc>> res;
+            for (const auto &p : vars_) {
+                res.push_back(p.second);
+            }
+            return res;
+        }
 
-std::vector<std::shared_ptr<OpDesc>> BlockDesc::Ops() const {
-  std::vector<std::shared_ptr<OpDesc>> res;
-  for (const auto &op : ops_) {
-    res.push_back(op);
-  }
-  return res;
-}
+        std::vector<std::shared_ptr<OpDesc>> BlockDesc::Ops() const {
+            std::vector<std::shared_ptr<OpDesc>> res;
+            for (const auto &op : ops_) {
+                res.push_back(op);
+            }
+            return res;
+        }
 
-BlockDesc::BlockDesc(const proto::BlockDesc &desc) : desc_(desc) {
-  for (const proto::VarDesc &var_desc : desc_.vars()) {
-    vars_[var_desc.name()].reset(new VarDesc(var_desc));
-  }
-  for (const proto::OpDesc &op_desc : desc_.ops()) {
-    ops_.emplace_back(new framework::OpDesc(op_desc));
-  }
-}
+        BlockDesc::BlockDesc(const proto::BlockDesc &desc) : desc_(desc) {
+            for (const proto::VarDesc &var_desc : desc_.vars()) {
+                vars_[var_desc.name()].reset(new VarDesc(var_desc));
+            }
+            for (const proto::OpDesc &op_desc : desc_.ops()) {
+                ops_.emplace_back(new framework::OpDesc(op_desc));
+            }
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/block_desc.h

@@ -24,46 +24,50 @@ SOFTWARE.
 #include "var_desc.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-class BlockDesc : PaddleMobileObject {
-public:
-  BlockDesc(const proto::BlockDesc &desc);
+        class BlockDesc : PaddleMobileObject {
+          public:
+            BlockDesc(const proto::BlockDesc &desc);
 
-  const int &ID() const { return desc_.idx(); }
+            const int &ID() const { return desc_.idx(); }
 
-  const int &Parent() const { return desc_.parent_idx(); }
+            const int &Parent() const { return desc_.parent_idx(); }
 
-  bool operator==(const paddle_mobile::framework::BlockDesc &in_block) const {
-    return this->ID() == in_block.ID() && this->Parent() == in_block.Parent();
-  }
+            bool operator==(
+                const paddle_mobile::framework::BlockDesc &in_block) const {
+                return this->ID() == in_block.ID() &&
+                       this->Parent() == in_block.Parent();
+            }
 
-  bool operator<(const paddle_mobile::framework::BlockDesc &in_block) const {
-    return this->ID() < in_block.ID() && this->Parent() < in_block.Parent();
-  }
+            bool operator<(
+                const paddle_mobile::framework::BlockDesc &in_block) const {
+                return this->ID() < in_block.ID() &&
+                       this->Parent() < in_block.Parent();
+            }
 
-  std::vector<std::shared_ptr<VarDesc>> Vars() const;
-  std::vector<std::shared_ptr<OpDesc>> Ops() const;
+            std::vector<std::shared_ptr<VarDesc>> Vars() const;
+            std::vector<std::shared_ptr<OpDesc>> Ops() const;
 
-private:
-  proto::BlockDesc desc_;
-  std::vector<std::shared_ptr<OpDesc>> ops_;
-  std::unordered_map<std::string, std::shared_ptr<VarDesc>> vars_;
-};
+          private:
+            proto::BlockDesc desc_;
+            std::vector<std::shared_ptr<OpDesc>> ops_;
+            std::unordered_map<std::string, std::shared_ptr<VarDesc>> vars_;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile
 
 namespace std {
 
-template <> struct hash<paddle_mobile::framework::BlockDesc> {
-  typedef paddle_mobile::framework::BlockDesc argument_type;
-  typedef std::size_t result_type;
-  result_type operator()(argument_type const &s) const noexcept {
-    result_type const h1(std::hash<int>{}(s.ID()));
-    result_type const h2(std::hash<int>{}(s.ID()));
-    return h1 ^ (h2 << 1);
-  }
-};
+    template <> struct hash<paddle_mobile::framework::BlockDesc> {
+        typedef paddle_mobile::framework::BlockDesc argument_type;
+        typedef std::size_t result_type;
+        result_type operator()(argument_type const &s) const noexcept {
+            result_type const h1(std::hash<int>{}(s.ID()));
+            result_type const h2(std::hash<int>{}(s.ID()));
+            return h1 ^ (h2 << 1);
+        }
+    };
 
 } // namespace std

src/framework/data_layout.h

@@ -19,49 +19,50 @@ limitations under the License. */
 #include <string>
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-enum class DataLayout {
-  kNHWC = 0,
-  kNCHW = 1,
-  kAnyLayout = 2,
-};
+        enum class DataLayout {
+            kNHWC = 0,
+            kNCHW = 1,
+            kAnyLayout = 2,
+        };
 
-inline DataLayout StringToDataLayout(const std::string &str) {
-  std::string s(str);
-  for (size_t i = 0; i < s.size(); ++i) {
-    s[i] = toupper(s[i]);
-  }
+        inline DataLayout StringToDataLayout(const std::string &str) {
+            std::string s(str);
+            for (size_t i = 0; i < s.size(); ++i) {
+                s[i] = toupper(s[i]);
+            }
 
-  if (s == "NHWC") {
-    return DataLayout::kNHWC;
-  } else if (s == "NCHW") {
-    return DataLayout::kNCHW;
-  } else if (s == "ANYLAYOUT") {
-    return DataLayout::kAnyLayout;
-  } else {
-    //    std::cout << "Unknown storage order string: %s", s;
-  }
-}
+            if (s == "NHWC") {
+                return DataLayout::kNHWC;
+            } else if (s == "NCHW") {
+                return DataLayout::kNCHW;
+            } else if (s == "ANYLAYOUT") {
+                return DataLayout::kAnyLayout;
+            } else {
+                //    std::cout << "Unknown storage order string: %s", s;
+            }
+        }
 
-inline std::string DataLayoutToString(const DataLayout &data_layout) {
-  switch (data_layout) {
-  case DataLayout::kNHWC:
-    return "NHWC";
-  case DataLayout::kNCHW:
-    return "NCHW";
-  case DataLayout::kAnyLayout:
-    return "ANY_LAYOUT";
-  default:
-    break;
-    //      std::cout << "unknown DataLayou %d", data_layout;
-  }
-}
+        inline std::string DataLayoutToString(const DataLayout &data_layout) {
+            switch (data_layout) {
+            case DataLayout::kNHWC:
+                return "NHWC";
+            case DataLayout::kNCHW:
+                return "NCHW";
+            case DataLayout::kAnyLayout:
+                return "ANY_LAYOUT";
+            default:
+                break;
+                //      std::cout << "unknown DataLayou %d", data_layout;
+            }
+        }
 
-inline std::ostream &operator<<(std::ostream &out, const DataLayout &l) {
-  out << DataLayoutToString(l);
-  return out;
-}
+        inline std::ostream &operator<<(std::ostream &out,
+                                        const DataLayout &l) {
+            out << DataLayoutToString(l);
+            return out;
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/data_transform.cpp

@@ -21,67 +21,72 @@ SOFTWARE.
 #include "data_transform.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-static void PassTensorData(Tensor *from, Tensor *to) {
-  to->ShareDataWith(*from);
-  *from = Tensor();
-}
+        static void PassTensorData(Tensor *from, Tensor *to) {
+            to->ShareDataWith(*from);
+            *from = Tensor();
+        }
 
-void DataTransform(const OpKernelType &expected_kernel_type,
-                   const OpKernelType &kernel_type_for_var,
-                   const Tensor &input_tensor, Tensor *output_tensor) {
-  bool transformed = false;
-  Tensor in;
-  in.ShareDataWith(input_tensor);
-  Tensor out;
+        void DataTransform(const OpKernelType &expected_kernel_type,
+                           const OpKernelType &kernel_type_for_var,
+                           const Tensor &input_tensor, Tensor *output_tensor) {
+            bool transformed = false;
+            Tensor in;
+            in.ShareDataWith(input_tensor);
+            Tensor out;
 
-  //  // do layout transform
-  //  if (NeedTransformLayout(expected_kernel_type.data_layout_,
-  //                          kernel_type_for_var.data_layout_)) {
-  //    TransDataLayout(kernel_type_for_var, expected_kernel_type, in, &out);
-  //    transformed = true;
-  //    PassTensorData(&out, &in);
-  //  }
-  //
-  //  // do data type transform
-  //  if (expected_kernel_type.data_type_ != kernel_type_for_var.data_type_) {
-  //    TransDataType(kernel_type_for_var, expected_kernel_type, in, &out);
-  //    transformed = true;
-  //    PassTensorData(&out, &in);
-  //  }
-  //
-  //  // do device transform
-  //  if (!platform::is_same_place(kernel_type_for_var.place_,
-  //                               expected_kernel_type.place_)) {
-  //    TransDataDevice(in, expected_kernel_type.place_, &out);
-  //    transformed = true;
-  //    PassTensorData(&out, &in);
-  //  }
-  //
-  //  PADDLE_ENFORCE(transformed, "No transform is applied, please check!");
-  // get output data
-  output_tensor->ShareDataWith(in);
-}
+            //  // do layout transform
+            //  if (NeedTransformLayout(expected_kernel_type.data_layout_,
+            //                          kernel_type_for_var.data_layout_)) {
+            //    TransDataLayout(kernel_type_for_var, expected_kernel_type, in,
+            //    &out);
+            //    transformed = true;
+            //    PassTensorData(&out, &in);
+            //  }
+            //
+            //  // do data type transform
+            //  if (expected_kernel_type.data_type_ !=
+            //  kernel_type_for_var.data_type_) {
+            //    TransDataType(kernel_type_for_var, expected_kernel_type, in,
+            //    &out);
+            //    transformed = true;
+            //    PassTensorData(&out, &in);
+            //  }
+            //
+            //  // do device transform
+            //  if (!platform::is_same_place(kernel_type_for_var.place_,
+            //                               expected_kernel_type.place_)) {
+            //    TransDataDevice(in, expected_kernel_type.place_, &out);
+            //    transformed = true;
+            //    PassTensorData(&out, &in);
+            //  }
+            //
+            //  PADDLE_ENFORCE(transformed, "No transform is applied, please
+            //  check!");
+            // get output data
+            output_tensor->ShareDataWith(in);
+        }
 
-void CopyVariableWithTensor(const Variable &in_var, const Tensor &tensor,
-                            Variable &out_var) {
-  //  if (in_var.IsType<LoDTensor>()) {
-  //    auto& in_lod_tensor = in_var.Get<LoDTensor>();
-  //    auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>();
-  //    tran_lod_tensor->set_lod(in_lod_tensor.lod());
-  //    tran_lod_tensor->set_layout(in_lod_tensor.layout());
-  //    tran_lod_tensor->ShareDataWith(tensor);
-  //  } else if (in_var.IsType<SelectedRows>()) {
-  //    auto& in_selected_rows = in_var.Get<SelectedRows>();
-  //    auto* trans_selected_rows = out_var.GetMutable<SelectedRows>();
-  //    trans_selected_rows->set_height(in_selected_rows.height());
-  //    trans_selected_rows->set_rows(in_selected_rows.rows());
-  //    trans_selected_rows->mutable_value()->ShareDataWith(tensor);
-  //  } else {
-  //    PADDLE_THROW("unknown var type");
-  //  }
-}
+        void CopyVariableWithTensor(const Variable &in_var,
+                                    const Tensor &tensor, Variable &out_var) {
+            //  if (in_var.IsType<LoDTensor>()) {
+            //    auto& in_lod_tensor = in_var.Get<LoDTensor>();
+            //    auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>();
+            //    tran_lod_tensor->set_lod(in_lod_tensor.lod());
+            //    tran_lod_tensor->set_layout(in_lod_tensor.layout());
+            //    tran_lod_tensor->ShareDataWith(tensor);
+            //  } else if (in_var.IsType<SelectedRows>()) {
+            //    auto& in_selected_rows = in_var.Get<SelectedRows>();
+            //    auto* trans_selected_rows =
+            //    out_var.GetMutable<SelectedRows>();
+            //    trans_selected_rows->set_height(in_selected_rows.height());
+            //    trans_selected_rows->set_rows(in_selected_rows.rows());
+            //    trans_selected_rows->mutable_value()->ShareDataWith(tensor);
+            //  } else {
+            //    PADDLE_THROW("unknown var type");
+            //  }
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/data_transform.h

@@ -28,14 +28,14 @@ SOFTWARE.
 #include "variable.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-void DataTransform(const OpKernelType &expected_kernel_type,
-                   const OpKernelType &kernel_type_for_var,
-                   const Tensor &input_tensor, Tensor *out);
+        void DataTransform(const OpKernelType &expected_kernel_type,
+                           const OpKernelType &kernel_type_for_var,
+                           const Tensor &input_tensor, Tensor *out);
 
-void CopyVariableWithTensor(const Variable &in_var, const Tensor &tensor,
-                            Variable &out_var);
+        void CopyVariableWithTensor(const Variable &in_var,
+                                    const Tensor &tensor, Variable &out_var);
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/data_type.h

@@ -21,23 +21,23 @@ SOFTWARE.
 #include "framework.pb.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-//    inline proto::VarType::Type ToDataType(std::type_index type) {
-//        using namespace paddle_mobile::framework::proto;
-//        if (typeid(float).hash_code() == type.hash_code()) {
-//            return proto::VarType::FP32;
-//        } else if (typeid(double).hash_code() == type.hash_code()) {
-//            return proto::VarType::FP64;
-//        } else if (typeid(int).hash_code() == type.hash_code()) {
-//            return proto::VarType::INT32;
-//        } else if (typeid(int64_t).hash_code() == type.hash_code()) {
-//            return proto::VarType::INT64;
-//        } else if (typeid(bool).hash_code() == type.hash_code()) {
-//            return proto::VarType::BOOL;
-//        } else {
-////            PADDLE_THROW("Not supported");
-//        }
-//    }
-}
+        //    inline proto::VarType::Type ToDataType(std::type_index type) {
+        //        using namespace paddle_mobile::framework::proto;
+        //        if (typeid(float).hash_code() == type.hash_code()) {
+        //            return proto::VarType::FP32;
+        //        } else if (typeid(double).hash_code() == type.hash_code()) {
+        //            return proto::VarType::FP64;
+        //        } else if (typeid(int).hash_code() == type.hash_code()) {
+        //            return proto::VarType::INT32;
+        //        } else if (typeid(int64_t).hash_code() == type.hash_code()) {
+        //            return proto::VarType::INT64;
+        //        } else if (typeid(bool).hash_code() == type.hash_code()) {
+        //            return proto::VarType::BOOL;
+        //        } else {
+        ////            PADDLE_THROW("Not supported");
+        //        }
+        //    }
+    }
 } // namespace paddle_mobile

src/framework/ddim.cc

@@ -15,311 +15,320 @@ limitations under the License. */
 #include "ddim.h"
 
 namespace paddle_mobile {
-namespace framework {
-
-/// @cond HIDDEN
-
-template <int i> Dim<i> make_dim(const int64_t *d) {
-  return Dim<i>(*d, make_dim<i - 1>(d + 1));
-}
-
-template <> Dim<0> make_dim<0>(const int64_t *d) { return Dim<0>(*d); }
-
-void make_ddim(DDim &ddim, const int64_t *dims, int n) {
-  switch (n) {
-  case 0:
-    ddim = make_dim<0>(dims);
-    break;
-  case 1:
-    ddim = make_dim<1>(dims);
-    break;
-  case 2:
-    ddim = make_dim<2>(dims);
-    break;
-  case 3:
-    ddim = make_dim<3>(dims);
-    break;
-  case 4:
-    ddim = make_dim<4>(dims);
-    break;
-  case 5:
-    ddim = make_dim<5>(dims);
-    break;
-  case 6:
-    ddim = make_dim<6>(dims);
-    break;
-  case 7:
-    ddim = make_dim<7>(dims);
-    break;
-  case 8:
-    ddim = make_dim<8>(dims);
-    break;
-  case 9:
-    ddim = make_dim<9>(dims);
-    break;
-  default:
-    //      std::cout << "Dynamic dimensions must have between [1, 9]
-    //      dimensions.";
-    break;
-  }
-}
-
-/// @endcond
-
-DDim make_ddim(std::initializer_list<int64_t> dims) {
-  DDim result(make_dim(0));
-  make_ddim(result, dims.begin(), dims.size());
-  return result;
-}
-
-DDim make_ddim(const std::vector<int64_t> &dims) {
-  DDim result(make_dim(0));
-  make_ddim(result, &dims[0], dims.size());
-  return result;
-}
-
-DDim make_ddim(const std::vector<int> &dims) {
-  std::vector<int64_t> res(dims.size());
-  std::transform(dims.begin(), dims.end(), res.begin(),
-                 [](int d) { return static_cast<int64_t>(d); });
-  return make_ddim(res);
-}
-
-/// @cond HIDDEN
-// XXX For some reason, putting this in an anonymous namespace causes errors
-struct DynamicMutableIndexer : Vistor<int64_t &> {
-public:
-  explicit DynamicMutableIndexer(int idx) : idx_(idx) {}
-
-  template <int D> int64_t &operator()(Dim<D> &dim) const { return dim[idx_]; }
-
-private:
-  int idx_;
-};
-
-struct DynamicConstIndexer : public Vistor<int64_t> {
-public:
-  explicit DynamicConstIndexer(int idx) : idx_(idx) {}
-
-  template <int D> int64_t operator()(const Dim<D> &dim) const {
-    return dim[idx_];
-  }
-
-private:
-  int idx_;
-};
-
-/// @endcond
-
-int64_t &DDim::operator[](int idx) {
-  return DDim::ApplyVistor(DynamicMutableIndexer(idx), *this);
-}
-
-int64_t DDim::operator[](int idx) const {
-  return DDim::ApplyVistor(DynamicConstIndexer(idx), *this);
-}
-
-int DDim::size() const { return arity(*this); }
-
-bool DDim::operator==(DDim d) const {
-  //  if (var.which() != d.getVar().which()) {
-  //    return false;
-  //  } else {
-  std::vector<int64_t> v1 = vectorize(*this);
-  std::vector<int64_t> v2 = vectorize(d);
-
-  for (unsigned int i = 0; i < v1.size(); i++) {
-    if (v1[i] != v2[i]) {
-      return false;
-    }
-  }
-
-  return true;
-  //  }
-}
-
-bool DDim::operator!=(DDim d) const { return !(*this == d); }
-
-DDim DDim::operator+(DDim d) const {
-  std::vector<int64_t> v1 = vectorize(*this);
-  std::vector<int64_t> v2 = vectorize(d);
-
-  std::vector<int64_t> v3;
-
-  assert(v1.size() == v2.size());
-
-  for (unsigned int i = 0; i < v1.size(); i++) {
-    v3.push_back(v1[i] + v2[i]);
-  }
-
-  return make_ddim(v3);
-}
-
-DDim DDim::operator*(DDim d) const {
-  std::vector<int64_t> v1 = vectorize(*this);
-  std::vector<int64_t> v2 = vectorize(d);
-
-  std::vector<int64_t> v3;
-
-  assert(v1.size() == v2.size());
-
-  for (unsigned int i = 0; i < v1.size(); i++) {
-    v3.push_back(v1[i] * v2[i]);
-  }
-
-  return make_ddim(v3);
-}
-
-int64_t get(const DDim &ddim, int idx) { return ddim[idx]; }
-
-void set(DDim &ddim, int idx, int value) { ddim[idx] = value; }
-
-/// @cond HIDDEN
-struct VectorizeVisitor : Vistor<void> {
-  std::vector<int64_t> &vector;
-
-  explicit VectorizeVisitor(std::vector<int64_t> &v) : vector(v) {}
-
-  template <typename T> void operator()(const T &t) {
-    vector.push_back(t.head);
-    this->operator()(t.tail);
-  }
-
-  void operator()(const Dim<0> &t) {}
-};
-/// @endcond
-
-std::vector<int64_t> vectorize(const DDim &ddim) {
-  std::vector<int64_t> result;
-  VectorizeVisitor visitor(result);
-  DDim::ApplyVistor(visitor, ddim);
-  return result;
-}
-
-// NOTE: framework::vectorize converts to type int64_t
-//       which does not fit cudnn inputs.
-std::vector<int> vectorize2int(const DDim &ddim) {
-  std::vector<int64_t> temp = vectorize(ddim);
-  std::vector<int> result(temp.begin(), temp.end());
-  return result;
-}
-
-struct ProductVisitor : Vistor<int64_t> {
-  template <int D> int64_t operator()(const Dim<D> &dim) {
-    return product(dim);
-  }
-};
-
-int64_t product(const DDim &ddim) {
-  ProductVisitor visitor;
-  return DDim::ApplyVistor(visitor, ddim);
-}
-
-struct SliceVectorizeVisitor : Vistor<void> {
-  std::vector<int64_t> &vector;
-  int begin;
-  int end;
-
-  SliceVectorizeVisitor(std::vector<int64_t> &v, int b, int e)
-      : vector(v), begin(b), end(e) {
-    //    PADDLE_ENFORCE(begin < end,
-    //                   "Begin index must be less than end index in ddim
-    //                   slice.");
-    //    PADDLE_ENFORCE(begin >= 0,
-    //                   "Begin index can't be less than zero in ddim slice.");
-  }
-
-  template <int S> void operator()(const Dim<S> &dim) {
-    if (begin == 0) {
-      vector.push_back(dim.head);
-    } else {
-      --begin;
-    }
-    --end;
-    if (end > 0) {
-      this->operator()(dim.tail);
-    }
-  }
-
-  void operator()(const Dim<0> &dim) {
-    //    PADDLE_ENFORCE(end == 0, "End index in ddim slice is out of bound.");
-  }
-};
-
-DDim slice_ddim(const DDim &ddim, int begin, int end) {
-  std::vector<int64_t> vec;
-  vec.reserve(end - begin);
-  SliceVectorizeVisitor visitor(vec, begin, end);
-  //  boost::apply_visitor(visitor, dim);
-  DDim::ApplyVistor(visitor, ddim);
-  //  visitor(ddim.var.Get<Dim<4>>());
-  return make_ddim(vec);
-}
-
-/// \cond HIDDEN
-
-struct ArityVisitor : Vistor<int> {
-  template <int D> int operator()(Dim<D>) const { return D; }
-};
-
-/// \endcond
-
-int arity(const DDim &d) {
-  ArityVisitor arityVisitor = ArityVisitor();
-  return DDim::ApplyVistor(arityVisitor, d);
-  //  return arityVisitor(d.var.Get<Dim<4>>());
-  //  return boost::apply_visitor(ArityVisitor(), d); }
-}
-/// \cond HIDDEN
-
-/// \endcond
-
-struct OSVistor : Vistor<std::ostream &> {
-  OSVistor(std::ostream &os) : os_(os) {}
-
-  template <int D> std::ostream &operator()(Dim<D> dim) const {
-    return os_ << dim;
-  }
-
-private:
-  std::ostream &os_;
-};
-
-std::ostream &operator<<(std::ostream &os, const DDim &ddim) {
-  auto vistor = OSVistor(os);
-  DDim::ApplyVistor(vistor, ddim);
-  return os;
-}
-
-DDim::DDim(std::initializer_list<int64_t> init_list) {
-  *this = make_ddim(init_list);
-}
-
-DDim flatten_to_2d(const DDim &src, int num_col_dims) {
-  int rank = src.size();
-  return make_ddim({product(slice_ddim(src, 0, num_col_dims)),
-                    product(slice_ddim(src, num_col_dims, rank))});
-}
-
-DDim flatten_to_1d(const DDim &src) { return make_ddim({product(src)}); }
-
-DDim stride(const DDim &ddim) {
-  std::vector<int64_t> strides(ddim.size());
-  strides[ddim.size() - 1] = 1;
-  for (int i = ddim.size() - 2; i >= 0; --i) {
-    strides[i] = strides[i + 1] * ddim[i + 1];
-  }
-  return framework::make_ddim(strides);
-}
-
-DDim stride_numel(const framework::DDim &ddim) {
-  std::vector<int64_t> strides(ddim.size());
-  strides[ddim.size() - 1] = ddim[ddim.size() - 1];
-  for (int i = ddim.size() - 2; i >= 0; --i) {
-    strides[i] = strides[i + 1] * ddim[i];
-  }
-  return framework::make_ddim(strides);
-}
-
-} // namespace framework
+    namespace framework {
+
+        /// @cond HIDDEN
+
+        template <int i> Dim<i> make_dim(const int64_t *d) {
+            return Dim<i>(*d, make_dim<i - 1>(d + 1));
+        }
+
+        template <> Dim<0> make_dim<0>(const int64_t *d) { return Dim<0>(*d); }
+
+        void make_ddim(DDim &ddim, const int64_t *dims, int n) {
+            switch (n) {
+            case 0:
+                ddim = make_dim<0>(dims);
+                break;
+            case 1:
+                ddim = make_dim<1>(dims);
+                break;
+            case 2:
+                ddim = make_dim<2>(dims);
+                break;
+            case 3:
+                ddim = make_dim<3>(dims);
+                break;
+            case 4:
+                ddim = make_dim<4>(dims);
+                break;
+            case 5:
+                ddim = make_dim<5>(dims);
+                break;
+            case 6:
+                ddim = make_dim<6>(dims);
+                break;
+            case 7:
+                ddim = make_dim<7>(dims);
+                break;
+            case 8:
+                ddim = make_dim<8>(dims);
+                break;
+            case 9:
+                ddim = make_dim<9>(dims);
+                break;
+            default:
+                //      std::cout << "Dynamic dimensions must have between [1,
+                //      9]
+                //      dimensions.";
+                break;
+            }
+        }
+
+        /// @endcond
+
+        DDim make_ddim(std::initializer_list<int64_t> dims) {
+            DDim result(make_dim(0));
+            make_ddim(result, dims.begin(), dims.size());
+            return result;
+        }
+
+        DDim make_ddim(const std::vector<int64_t> &dims) {
+            DDim result(make_dim(0));
+            make_ddim(result, &dims[0], dims.size());
+            return result;
+        }
+
+        DDim make_ddim(const std::vector<int> &dims) {
+            std::vector<int64_t> res(dims.size());
+            std::transform(dims.begin(), dims.end(), res.begin(),
+                           [](int d) { return static_cast<int64_t>(d); });
+            return make_ddim(res);
+        }
+
+        /// @cond HIDDEN
+        // XXX For some reason, putting this in an anonymous namespace causes
+        // errors
+        struct DynamicMutableIndexer : Vistor<int64_t &> {
+          public:
+            explicit DynamicMutableIndexer(int idx) : idx_(idx) {}
+
+            template <int D> int64_t &operator()(Dim<D> &dim) const {
+                return dim[idx_];
+            }
+
+          private:
+            int idx_;
+        };
+
+        struct DynamicConstIndexer : public Vistor<int64_t> {
+          public:
+            explicit DynamicConstIndexer(int idx) : idx_(idx) {}
+
+            template <int D> int64_t operator()(const Dim<D> &dim) const {
+                return dim[idx_];
+            }
+
+          private:
+            int idx_;
+        };
+
+        /// @endcond
+
+        int64_t &DDim::operator[](int idx) {
+            return DDim::ApplyVistor(DynamicMutableIndexer(idx), *this);
+        }
+
+        int64_t DDim::operator[](int idx) const {
+            return DDim::ApplyVistor(DynamicConstIndexer(idx), *this);
+        }
+
+        int DDim::size() const { return arity(*this); }
+
+        bool DDim::operator==(DDim d) const {
+            //  if (var.which() != d.getVar().which()) {
+            //    return false;
+            //  } else {
+            std::vector<int64_t> v1 = vectorize(*this);
+            std::vector<int64_t> v2 = vectorize(d);
+
+            for (unsigned int i = 0; i < v1.size(); i++) {
+                if (v1[i] != v2[i]) {
+                    return false;
+                }
+            }
+
+            return true;
+            //  }
+        }
+
+        bool DDim::operator!=(DDim d) const { return !(*this == d); }
+
+        DDim DDim::operator+(DDim d) const {
+            std::vector<int64_t> v1 = vectorize(*this);
+            std::vector<int64_t> v2 = vectorize(d);
+
+            std::vector<int64_t> v3;
+
+            assert(v1.size() == v2.size());
+
+            for (unsigned int i = 0; i < v1.size(); i++) {
+                v3.push_back(v1[i] + v2[i]);
+            }
+
+            return make_ddim(v3);
+        }
+
+        DDim DDim::operator*(DDim d) const {
+            std::vector<int64_t> v1 = vectorize(*this);
+            std::vector<int64_t> v2 = vectorize(d);
+
+            std::vector<int64_t> v3;
+
+            assert(v1.size() == v2.size());
+
+            for (unsigned int i = 0; i < v1.size(); i++) {
+                v3.push_back(v1[i] * v2[i]);
+            }
+
+            return make_ddim(v3);
+        }
+
+        int64_t get(const DDim &ddim, int idx) { return ddim[idx]; }
+
+        void set(DDim &ddim, int idx, int value) { ddim[idx] = value; }
+
+        /// @cond HIDDEN
+        struct VectorizeVisitor : Vistor<void> {
+            std::vector<int64_t> &vector;
+
+            explicit VectorizeVisitor(std::vector<int64_t> &v) : vector(v) {}
+
+            template <typename T> void operator()(const T &t) {
+                vector.push_back(t.head);
+                this->operator()(t.tail);
+            }
+
+            void operator()(const Dim<0> &t) {}
+        };
+        /// @endcond
+
+        std::vector<int64_t> vectorize(const DDim &ddim) {
+            std::vector<int64_t> result;
+            VectorizeVisitor visitor(result);
+            DDim::ApplyVistor(visitor, ddim);
+            return result;
+        }
+
+        // NOTE: framework::vectorize converts to type int64_t
+        //       which does not fit cudnn inputs.
+        std::vector<int> vectorize2int(const DDim &ddim) {
+            std::vector<int64_t> temp = vectorize(ddim);
+            std::vector<int> result(temp.begin(), temp.end());
+            return result;
+        }
+
+        struct ProductVisitor : Vistor<int64_t> {
+            template <int D> int64_t operator()(const Dim<D> &dim) {
+                return product(dim);
+            }
+        };
+
+        int64_t product(const DDim &ddim) {
+            ProductVisitor visitor;
+            return DDim::ApplyVistor(visitor, ddim);
+        }
+
+        struct SliceVectorizeVisitor : Vistor<void> {
+            std::vector<int64_t> &vector;
+            int begin;
+            int end;
+
+            SliceVectorizeVisitor(std::vector<int64_t> &v, int b, int e)
+                : vector(v), begin(b), end(e) {
+                //    PADDLE_ENFORCE(begin < end,
+                //                   "Begin index must be less than end index in
+                //                   ddim
+                //                   slice.");
+                //    PADDLE_ENFORCE(begin >= 0,
+                //                   "Begin index can't be less than zero in
+                //                   ddim slice.");
+            }
+
+            template <int S> void operator()(const Dim<S> &dim) {
+                if (begin == 0) {
+                    vector.push_back(dim.head);
+                } else {
+                    --begin;
+                }
+                --end;
+                if (end > 0) {
+                    this->operator()(dim.tail);
+                }
+            }
+
+            void operator()(const Dim<0> &dim) {
+                //    PADDLE_ENFORCE(end == 0, "End index in ddim slice is out
+                //    of bound.");
+            }
+        };
+
+        DDim slice_ddim(const DDim &ddim, int begin, int end) {
+            std::vector<int64_t> vec;
+            vec.reserve(end - begin);
+            SliceVectorizeVisitor visitor(vec, begin, end);
+            //  boost::apply_visitor(visitor, dim);
+            DDim::ApplyVistor(visitor, ddim);
+            //  visitor(ddim.var.Get<Dim<4>>());
+            return make_ddim(vec);
+        }
+
+        /// \cond HIDDEN
+
+        struct ArityVisitor : Vistor<int> {
+            template <int D> int operator()(Dim<D>) const { return D; }
+        };
+
+        /// \endcond
+
+        int arity(const DDim &d) {
+            ArityVisitor arityVisitor = ArityVisitor();
+            return DDim::ApplyVistor(arityVisitor, d);
+            //  return arityVisitor(d.var.Get<Dim<4>>());
+            //  return boost::apply_visitor(ArityVisitor(), d); }
+        }
+        /// \cond HIDDEN
+
+        /// \endcond
+
+        struct OSVistor : Vistor<std::ostream &> {
+            OSVistor(std::ostream &os) : os_(os) {}
+
+            template <int D> std::ostream &operator()(Dim<D> dim) const {
+                return os_ << dim;
+            }
+
+          private:
+            std::ostream &os_;
+        };
+
+        std::ostream &operator<<(std::ostream &os, const DDim &ddim) {
+            auto vistor = OSVistor(os);
+            DDim::ApplyVistor(vistor, ddim);
+            return os;
+        }
+
+        DDim::DDim(std::initializer_list<int64_t> init_list) {
+            *this = make_ddim(init_list);
+        }
+
+        DDim flatten_to_2d(const DDim &src, int num_col_dims) {
+            int rank = src.size();
+            return make_ddim({product(slice_ddim(src, 0, num_col_dims)),
+                              product(slice_ddim(src, num_col_dims, rank))});
+        }
+
+        DDim flatten_to_1d(const DDim &src) {
+            return make_ddim({product(src)});
+        }
+
+        DDim stride(const DDim &ddim) {
+            std::vector<int64_t> strides(ddim.size());
+            strides[ddim.size() - 1] = 1;
+            for (int i = ddim.size() - 2; i >= 0; --i) {
+                strides[i] = strides[i + 1] * ddim[i + 1];
+            }
+            return framework::make_ddim(strides);
+        }
+
+        DDim stride_numel(const framework::DDim &ddim) {
+            std::vector<int64_t> strides(ddim.size());
+            strides[ddim.size() - 1] = ddim[ddim.size() - 1];
+            for (int i = ddim.size() - 2; i >= 0; --i) {
+                strides[i] = strides[i + 1] * ddim[i];
+            }
+            return framework::make_ddim(strides);
+        }
+
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/ddim.h

@@ -22,140 +22,145 @@ limitations under the License. */
 #include <vector>
 
 namespace paddle_mobile {
-namespace framework {
-
-/**
- * \brief A dynamically sized dimension.
- *
- * The number of dimensions must be between [1, 9].
- */
-struct DDim {
-  typedef Variant<Dim<0>, Dim<1>, Dim<2>, Dim<3>, Dim<4>, Dim<5>, Dim<6>,
-                  Dim<7>, Dim<8>, Dim<9>>
-      DDimVar;
-  DDimVar var;
-
-  template <typename Vistor>
-  static typename Vistor::type_t ApplyVistor(Vistor vistor, const DDim &d) {
-    if (d.var.TypeId() == typeid(Dim<0>).hash_code()) {
-      return vistor(d.var.Get<Dim<0>>());
-    } else if (d.var.TypeId() == typeid(Dim<1>).hash_code()) {
-      return vistor(d.var.Get<Dim<1>>());
-    } else if (d.var.TypeId() == typeid(Dim<2>).hash_code()) {
-      return vistor(d.var.Get<Dim<2>>());
-    } else if (d.var.TypeId() == typeid(Dim<3>).hash_code()) {
-      return vistor(d.var.Get<Dim<3>>());
-    } else if (d.var.TypeId() == typeid(Dim<4>).hash_code()) {
-      return vistor(d.var.Get<Dim<4>>());
-    } else if (d.var.TypeId() == typeid(Dim<5>).hash_code()) {
-      return vistor(d.var.Get<Dim<5>>());
-    } else if (d.var.TypeId() == typeid(Dim<6>).hash_code()) {
-      return vistor(d.var.Get<Dim<6>>());
-    } else if (d.var.TypeId() == typeid(Dim<7>).hash_code()) {
-      return vistor(d.var.Get<Dim<7>>());
-    } else if (d.var.TypeId() == typeid(Dim<8>).hash_code()) {
-      return vistor(d.var.Get<Dim<8>>());
-    } else if (d.var.TypeId() == typeid(Dim<9>).hash_code()) {
-      return vistor(d.var.Get<Dim<9>>());
-    } else {
-      printf(" dim not support  \n");
-      throw std::bad_exception();
-      //        return typename Vistor::type_t();
-    }
-  }
-
-  DDim() { var.Set<Dim<1>>(Dim<1>()); }
-
-  template <int D> explicit DDim(const Dim<D> &in) { var.Set<Dim<D>>(in); }
-
-  /*implicit*/ DDim(std::initializer_list<int64_t> init_list);
-
-  template <int D> DDim &operator=(const Dim<D> &in) {
-    var.Set<Dim<D>>(in);
-    return *this;
-  }
-
-  int64_t &operator[](int idx);
-
-  int64_t operator[](int idx) const;
-
-  //  template <typename Visitor>
-  //  typename Visitor::result_type apply_visitor(Visitor& visitor) {
-  //    return var.apply_visitor(visitor);
-  //  }
-  //
-  //  template <typename Visitor>
-  //  typename Visitor::result_type apply_visitor(Visitor& visitor) const {
-  //    return var.apply_visitor(visitor);
-  //  }
-
-  DDimVar getVar() { return var; }
-
-  bool operator==(DDim d) const;
-
-  bool operator!=(DDim d) const;
-
-  DDim operator+(DDim d) const;
-
-  DDim operator*(DDim d) const;
-
-  int size() const;
-};
-
-/**
- * \brief Make a DDim from std::vector<int64_t>
- *
- * \param dims An vector of ints. Must be sized between [1, 9]
- */
-DDim make_ddim(const std::vector<int64_t> &dims);
-
-DDim make_ddim(const std::vector<int> &dims);
-
-/**
- * \brief Make a DDim from an initializer list
- *
- * \param dims An initializer list of ints. Must be sized between [1, 9]
- *
- */
-DDim make_ddim(std::initializer_list<int64_t> dims);
-
-int64_t get(const DDim &dim, int idx);
-
-void set(DDim &dim, int idx, int val);
-
-std::vector<int64_t> vectorize(const DDim &ddim);
-
-std::vector<int> vectorize2int(const DDim &ddim);
-
-int64_t product(const DDim &ddim);
-
-/**
- * \brief Slice a ddim
- *
- * Slice dim with [begin, end).
- * e.g.  DDim d = make_ddim({1,2,3,4,5});
- *       slice_ddim(d, 1, 3); ====> {2,3}
- */
-DDim slice_ddim(const DDim &dim, int begin, int end);
-
-/**
- * \brief What is the length of this dimension?
- *
- * \param Dynamic dimension to inspect
- */
+    namespace framework {
+
+        /**
+         * \brief A dynamically sized dimension.
+         *
+         * The number of dimensions must be between [1, 9].
+         */
+        struct DDim {
+            typedef Variant<Dim<0>, Dim<1>, Dim<2>, Dim<3>, Dim<4>, Dim<5>,
+                            Dim<6>, Dim<7>, Dim<8>, Dim<9>>
+                DDimVar;
+            DDimVar var;
+
+            template <typename Vistor>
+            static typename Vistor::type_t ApplyVistor(Vistor vistor,
+                                                       const DDim &d) {
+                if (d.var.TypeId() == typeid(Dim<0>).hash_code()) {
+                    return vistor(d.var.Get<Dim<0>>());
+                } else if (d.var.TypeId() == typeid(Dim<1>).hash_code()) {
+                    return vistor(d.var.Get<Dim<1>>());
+                } else if (d.var.TypeId() == typeid(Dim<2>).hash_code()) {
+                    return vistor(d.var.Get<Dim<2>>());
+                } else if (d.var.TypeId() == typeid(Dim<3>).hash_code()) {
+                    return vistor(d.var.Get<Dim<3>>());
+                } else if (d.var.TypeId() == typeid(Dim<4>).hash_code()) {
+                    return vistor(d.var.Get<Dim<4>>());
+                } else if (d.var.TypeId() == typeid(Dim<5>).hash_code()) {
+                    return vistor(d.var.Get<Dim<5>>());
+                } else if (d.var.TypeId() == typeid(Dim<6>).hash_code()) {
+                    return vistor(d.var.Get<Dim<6>>());
+                } else if (d.var.TypeId() == typeid(Dim<7>).hash_code()) {
+                    return vistor(d.var.Get<Dim<7>>());
+                } else if (d.var.TypeId() == typeid(Dim<8>).hash_code()) {
+                    return vistor(d.var.Get<Dim<8>>());
+                } else if (d.var.TypeId() == typeid(Dim<9>).hash_code()) {
+                    return vistor(d.var.Get<Dim<9>>());
+                } else {
+                    printf(" dim not support  \n");
+                    throw std::bad_exception();
+                    //        return typename Vistor::type_t();
+                }
+            }
+
+            DDim() { var.Set<Dim<1>>(Dim<1>()); }
+
+            template <int D> explicit DDim(const Dim<D> &in) {
+                var.Set<Dim<D>>(in);
+            }
+
+            /*implicit*/ DDim(std::initializer_list<int64_t> init_list);
+
+            template <int D> DDim &operator=(const Dim<D> &in) {
+                var.Set<Dim<D>>(in);
+                return *this;
+            }
+
+            int64_t &operator[](int idx);
+
+            int64_t operator[](int idx) const;
+
+            //  template <typename Visitor>
+            //  typename Visitor::result_type apply_visitor(Visitor& visitor) {
+            //    return var.apply_visitor(visitor);
+            //  }
+            //
+            //  template <typename Visitor>
+            //  typename Visitor::result_type apply_visitor(Visitor& visitor)
+            //  const {
+            //    return var.apply_visitor(visitor);
+            //  }
+
+            DDimVar getVar() { return var; }
+
+            bool operator==(DDim d) const;
+
+            bool operator!=(DDim d) const;
+
+            DDim operator+(DDim d) const;
+
+            DDim operator*(DDim d) const;
+
+            int size() const;
+        };
+
+        /**
+         * \brief Make a DDim from std::vector<int64_t>
+         *
+         * \param dims An vector of ints. Must be sized between [1, 9]
+         */
+        DDim make_ddim(const std::vector<int64_t> &dims);
+
+        DDim make_ddim(const std::vector<int> &dims);
+
+        /**
+         * \brief Make a DDim from an initializer list
+         *
+         * \param dims An initializer list of ints. Must be sized between [1, 9]
+         *
+         */
+        DDim make_ddim(std::initializer_list<int64_t> dims);
+
+        int64_t get(const DDim &dim, int idx);
+
+        void set(DDim &dim, int idx, int val);
+
+        std::vector<int64_t> vectorize(const DDim &ddim);
+
+        std::vector<int> vectorize2int(const DDim &ddim);
+
+        int64_t product(const DDim &ddim);
+
+        /**
+         * \brief Slice a ddim
+         *
+         * Slice dim with [begin, end).
+         * e.g.  DDim d = make_ddim({1,2,3,4,5});
+         *       slice_ddim(d, 1, 3); ====> {2,3}
+         */
+        DDim slice_ddim(const DDim &dim, int begin, int end);
+
+        /**
+         * \brief What is the length of this dimension?
+         *
+         * \param Dynamic dimension to inspect
+         */
 
-int arity(const DDim &ddim);
+        int arity(const DDim &ddim);
 
-std::ostream &operator<<(std::ostream &, const DDim &);
+        std::ostream &operator<<(std::ostream &, const DDim &);
 
-// Reshape a tensor to a matrix. The matrix's first dimension(column length)
-// will be the product of tensor's first `num_col_dims` dimensions.
-DDim flatten_to_2d(const DDim &src, int num_col_dims);
+        // Reshape a tensor to a matrix. The matrix's first dimension(column
+        // length)
+        // will be the product of tensor's first `num_col_dims` dimensions.
+        DDim flatten_to_2d(const DDim &src, int num_col_dims);
 
-DDim flatten_to_1d(const DDim &src);
+        DDim flatten_to_1d(const DDim &src);
 
-DDim stride(const DDim &ddim);
+        DDim stride(const DDim &ddim);
 
-DDim stride_numel(const DDim &ddim);
-} // namespace framework
+        DDim stride_numel(const DDim &ddim);
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/executor.cpp

@@ -23,84 +23,93 @@ SOFTWARE.
 #include "variable.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-template <typename Dtype>
-Executor<Dtype>::Executor(const Program<Dtype> p) : program_(p) {
-  if (use_optimize_) {
-    to_predict_program_ = program_.optimizeProgram;
-  } else {
-    to_predict_program_ = program_.originProgram;
-  }
+        template <typename Dtype>
+        Executor<Dtype>::Executor(const Program<Dtype> p) : program_(p) {
+            if (use_optimize_) {
+                to_predict_program_ = program_.optimizeProgram;
+            } else {
+                to_predict_program_ = program_.originProgram;
+            }
 
-  const std::vector<std::shared_ptr<BlockDesc>> blocks =
-      to_predict_program_->Blocks();
-  //  std::cout << " **block size " << blocks.size() << std::endl;
-  for (int i = 0; i < blocks.size(); ++i) {
-    std::shared_ptr<BlockDesc> block_desc = blocks[i];
-    std::vector<std::shared_ptr<OpDesc>> ops = block_desc->Ops();
-    //    std::cout << " ops " << ops.size() << std::endl;
-    for (int j = 0; j < ops.size(); ++j) {
-      std::shared_ptr<OpDesc> op = ops[j];
-      //        std::cout << " input 0 " << op->Input("Input")[0] << std::endl;
-      if (op->Type() == "conv2d" && op->Input("Input")[0] == "pixel") {
-        //        std::cout << " conv2d attr size: " << op->GetAttrMap().size()
-        //                  << std::endl;
-        //        std::cout << " input size: " << op->GetInputs().size() <<
-        //        std::endl;
+            const std::vector<std::shared_ptr<BlockDesc>> blocks =
+                to_predict_program_->Blocks();
+            //  std::cout << " **block size " << blocks.size() << std::endl;
+            for (int i = 0; i < blocks.size(); ++i) {
+                std::shared_ptr<BlockDesc> block_desc = blocks[i];
+                std::vector<std::shared_ptr<OpDesc>> ops = block_desc->Ops();
+                //    std::cout << " ops " << ops.size() << std::endl;
+                for (int j = 0; j < ops.size(); ++j) {
+                    std::shared_ptr<OpDesc> op = ops[j];
+                    //        std::cout << " input 0 " << op->Input("Input")[0]
+                    //        << std::endl;
+                    if (op->Type() == "conv2d" &&
+                        op->Input("Input")[0] == "pixel") {
+                        //        std::cout << " conv2d attr size: " <<
+                        //        op->GetAttrMap().size()
+                        //                  << std::endl;
+                        //        std::cout << " input size: " <<
+                        //        op->GetInputs().size() <<
+                        //        std::endl;
 
-        //        std::cout << " output size: " << op->GetOutputs().size() <<
-        //        std::endl;
+                        //        std::cout << " output size: " <<
+                        //        op->GetOutputs().size() <<
+                        //        std::endl;
 
-        Attribute strides_attr = op->GetAttrMap().at("strides");
-        std::vector<int> stride = strides_attr.Get<std::vector<int>>();
-        for (int k = 0; k < stride.size(); ++k) {
-          //          std::cout << " stride " << stride[k] << std::endl;
-        }
+                        Attribute strides_attr = op->GetAttrMap().at("strides");
+                        std::vector<int> stride =
+                            strides_attr.Get<std::vector<int>>();
+                        for (int k = 0; k < stride.size(); ++k) {
+                            //          std::cout << " stride " << stride[k] <<
+                            //          std::endl;
+                        }
 
-        std::shared_ptr<operators::ConvOp<Dtype, float>> conv =
-            std::make_shared<operators::ConvOp<Dtype, float>>(
-                op->Type(), op->GetInputs(), op->GetOutputs(), op->GetAttrMap(),
-                program_.scope);
-        ops_of_block_[*block_desc.get()].push_back(conv);
-      }
-    }
-  }
-}
+                        std::shared_ptr<operators::ConvOp<Dtype, float>> conv =
+                            std::make_shared<operators::ConvOp<Dtype, float>>(
+                                op->Type(), op->GetInputs(), op->GetOutputs(),
+                                op->GetAttrMap(), program_.scope);
+                        ops_of_block_[*block_desc.get()].push_back(conv);
+                    }
+                }
+            }
+        }
 
-template <typename Dtype>
-std::shared_ptr<Tensor> Executor<Dtype>::predict(Tensor &t) {
-  // feed
-  auto scope = program_.scope;
-  Variable *g_feed_value = scope->Var("pixel");
-  auto tensor = g_feed_value->GetMutable<Tensor>();
-  tensor->ShareDataWith(t);
+        template <typename Dtype>
+        std::shared_ptr<Tensor> Executor<Dtype>::predict(Tensor &t) {
+            // feed
+            auto scope = program_.scope;
+            Variable *g_feed_value = scope->Var("pixel");
+            auto tensor = g_feed_value->GetMutable<Tensor>();
+            tensor->ShareDataWith(t);
 
-  Variable *con_output = scope->Var("conv2d_0.tmp_0");
-  Tensor *output_tensor = con_output->GetMutable<Tensor>();
-  output_tensor->mutable_data<float>({1, 16, 32, 32});
-  //  std::cout << typeid(output_tensor).name() << std::endl;
-  //  std::cout << "output_tensor dims: " << output_tensor->dims() << std::endl;
+            Variable *con_output = scope->Var("conv2d_0.tmp_0");
+            Tensor *output_tensor = con_output->GetMutable<Tensor>();
+            output_tensor->mutable_data<float>({1, 16, 32, 32});
+            //  std::cout << typeid(output_tensor).name() << std::endl;
+            //  std::cout << "output_tensor dims: " << output_tensor->dims() <<
+            //  std::endl;
 
-  std::shared_ptr<Tensor> out_tensor = std::make_shared<LoDTensor>();
-  out_tensor.reset(output_tensor);
+            std::shared_ptr<Tensor> out_tensor = std::make_shared<LoDTensor>();
+            out_tensor.reset(output_tensor);
 
-  predict(t, 0);
-  return out_tensor;
-}
+            predict(t, 0);
+            return out_tensor;
+        }
 
-template <typename Dtype>
-void Executor<Dtype>::predict(const Tensor &t, int block_id) {
-  std::shared_ptr<BlockDesc> to_predict_block =
-      to_predict_program_->Block(block_id);
-  for (int j = 0; j < ops_of_block_[*to_predict_block.get()].size(); ++j) {
-    auto op = ops_of_block_[*to_predict_block.get()][j];
-    //    std::cout << "开始run" << std::endl;
-    op->Run();
-  }
-}
+        template <typename Dtype>
+        void Executor<Dtype>::predict(const Tensor &t, int block_id) {
+            std::shared_ptr<BlockDesc> to_predict_block =
+                to_predict_program_->Block(block_id);
+            for (int j = 0; j < ops_of_block_[*to_predict_block.get()].size();
+                 ++j) {
+                auto op = ops_of_block_[*to_predict_block.get()][j];
+                //    std::cout << "开始run" << std::endl;
+                op->Run();
+            }
+        }
 
-template class Executor<CPU>;
+        template class Executor<CPU>;
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/executor.h

@@ -32,22 +32,22 @@ SOFTWARE.
 #include "variable.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-template <typename Dtype> class Executor {
-public:
-  Executor(const Program<Dtype> p);
-  std::shared_ptr<Tensor> predict(Tensor &t);
+        template <typename Dtype> class Executor {
+          public:
+            Executor(const Program<Dtype> p);
+            std::shared_ptr<Tensor> predict(Tensor &t);
 
-private:
-  const framework::Program<Dtype> program_;
-  std::shared_ptr<ProgramDesc> to_predict_program_;
-  void predict(const Tensor &t, int block_id);
-  std::map<framework::BlockDesc,
-           std::vector<std::shared_ptr<OperatorBase<Dtype>>>>
-      ops_of_block_;
-  bool use_optimize_ = false;
-};
+          private:
+            const framework::Program<Dtype> program_;
+            std::shared_ptr<ProgramDesc> to_predict_program_;
+            void predict(const Tensor &t, int block_id);
+            std::map<framework::BlockDesc,
+                     std::vector<std::shared_ptr<OperatorBase<Dtype>>>>
+                ops_of_block_;
+            bool use_optimize_ = false;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/lod_tensor.h

@@ -23,178 +23,190 @@ limitations under the License. */
 
 namespace paddle_mobile {
 
-namespace framework {
-
-/*
- * LoD is short for Level of Details.
- *
- * - in a level, each element indicates relative offset of the lower level
- * - the first element should be 0 and that indicates that this sequence start
- * from 0
- * - each sequence's begin and end(no-inclusive) is level[id, id+1]
- *
- * For example:
- *    3-level LoD stores
- *
- *    0 2 3
- *    0 2 4 7
- *    0 2 5 7 10 12 15 20
- */
-using LoD = std::vector<std::vector<size_t>>;
-
-std::ostream &operator<<(std::ostream &os, const LoD &lod);
-
-std::ostream &operator<<(std::ostream &os, const LoDTensor &t);
-
-std::string LoDToString(const LoD &lod);
-
-LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin,
-                 size_t elem_end);
-
-/*
- * Transform an LoD from relative offsets to absolute offsets.
- */
-LoD ToAbsOffset(const LoD &in);
-
-bool operator==(const LoD &a, const LoD &b);
-
-/*
- * Check whether this lod's format is valid.
- *
- * ATTENTION:
- *   - Empty lod is treated as valid.
- *
- * It will check two things:
- *
- *  1. all the offsets in a level should be ascending(no same items allows).
- *  2. there should be more than 2 offsets existing in each level.
- *  3. the higher level's last offset should equals the lower level's size-1.
- *  4. the first offset(the begin offset) of each level should be 0.
- *  5. the lowest level's last offset should equals `tensor_height` if
- * tensor_height>0.
- */
-
-bool CheckLoD(const LoD &in, int tensor_height = -1);
-
-/*
- * Check whether this absolute lod's format is valid.
- *
- * ATTENTION:
- *   - Empty lod is treated as valid.
- *
- * It will check two things:
- *  1. all the offsets in a level should be ascending(no same items allows)
- *  2. there should be more than 2 offsets existing in each level.
- *  3. the first offset of each level should be 0, and the last should be the
- *     same(the height of underlying tensor) or `tensor_height` if
- *     tensor_height>0.
- */
-bool CheckAbsLoD(const LoD &in, int tensor_height = -1);
-
-/*
- * LoDTensor (Level of details Tensor)
- * see https://en.wikipedia.org/wiki/Level_of_details for reference.
- */
-class LoDTensor : public Tensor {
-public:
-  LoDTensor() : Tensor() {}
-
-  explicit LoDTensor(const LoD &lod) : lod_(lod) {}
-
-  void set_lod(const LoD &lod) { lod_ = lod; }
-
-  const LoD &lod() const { return lod_; }
-
-  LoD *mutable_lod() { return &lod_; }
-
-  /*
-   * Get the start offset and end offset of an  element from LoD.
-   */
-  std::pair<size_t, size_t> lod_element(size_t level, size_t elem) const {
-    //    PADDLE_ENFORCE_LT(level, NumLevels());
-    //    PADDLE_ENFORCE_LT(elem, NumElements(level));
-    return std::make_pair((lod_)[level][elem], (lod_)[level][elem + 1]);
-  }
-
-  /*
-   * Number of LoDTensor's levels, each level has units of data, for example,
-   * in the sentence's view, article, paragraph, sentence are 3 levels.
-   */
-  size_t NumLevels() const { return lod_.size(); }
-
-  /*
-   * Number of elements in a level.
-   */
-  size_t NumElements(size_t level = 0) const {
-    //    PADDLE_ENFORCE_LT(level, NumLevels());
-    // the last offset is the end of last element
-    return (lod_)[level].size() - 1;
-  }
-
-private:
-  LoD lod_;
-};
-
-/*
- * Expand the `source` to fit the LoD of `lod`. For example, a `source`
- * LoDTensor is
- *  - LoD: [0, 2]
- *  - tensor: [a0, a1]
- * a `lod` is
- *  - LoD: [0 3 5]
- * returns a new LoDTensor
- *  - [a0 a0 a0 a1 a1]
- */
-template <typename T>
-LoDTensor LodExpand(const LoDTensor &source, const LoD &lod, size_t level) {
-  LoD abs_lod = ToAbsOffset(lod);
-  const auto &lod_level = lod[level];
-  size_t num_instances = source.dims()[0];
-
-  // new tensor
-  LoDTensor tensor;
-  tensor.set_lod(lod);
-  auto dims = source.dims();
-  dims[0] = lod_level.back();
-  tensor.Resize(dims);
-  tensor.mutable_data<T>();
-
-  //  PADDLE_ENFORCE_EQ(num_instances, lod_level.size() - 1);
-  for (size_t ins = 0; ins < num_instances; ins++) {
-    for (size_t elem = lod_level[ins]; elem < lod_level[ins + 1]; elem++) {
-      auto slice = tensor.Slice(elem, elem + 1);
-      TensorCopy(source.Slice(ins, ins + 1), &slice);
-    }
-  }
-  return tensor;
-}
-
-// Get the absolute offset of a lod[start_level][start_idx:end_idx] and
-// relative length of details for every levels(i.e., [start_level: ]).
-//
-// For example,
-//   lod = [[0, 3, 4, 8], [0, 9, 10, 11, 13, 17, 19, 22, 24]]
-//   start_level = 0
-//   start_idx = 1
-//   end_idx = 3
-//
-// Returns:
-//  LoD = [[1, 4], [2, 4, 2, 3, 2]]
-//  pair<size_t, size_t> = {11, 24}
-std::pair<LoD, std::pair<size_t, size_t>>
-GetSubLoDAndAbsoluteOffset(const LoD &lod, size_t start_idx, size_t end_idx,
-                           size_t start_level);
-
-void AppendLoD(LoD *lod, const LoD &lod_length);
-
-/*
- * Serialize/Desiralize LoDTensor to std::ostream
- * You can pass ofstream or ostringstream to serilize to file
- * or to a in memory string. GPU tensor will be copied to CPU.
- */
-void SerializeToStream(std::ostream &os, const LoDTensor &tensor);
-
-void DeserializeFromStream(std::istream &is, LoDTensor *tensor);
-
-} // namespace framework
+    namespace framework {
+
+        /*
+         * LoD is short for Level of Details.
+         *
+         * - in a level, each element indicates relative offset of the lower
+         * level
+         * - the first element should be 0 and that indicates that this sequence
+         * start
+         * from 0
+         * - each sequence's begin and end(no-inclusive) is level[id, id+1]
+         *
+         * For example:
+         *    3-level LoD stores
+         *
+         *    0 2 3
+         *    0 2 4 7
+         *    0 2 5 7 10 12 15 20
+         */
+        using LoD = std::vector<std::vector<size_t>>;
+
+        std::ostream &operator<<(std::ostream &os, const LoD &lod);
+
+        std::ostream &operator<<(std::ostream &os, const LoDTensor &t);
+
+        std::string LoDToString(const LoD &lod);
+
+        LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin,
+                         size_t elem_end);
+
+        /*
+         * Transform an LoD from relative offsets to absolute offsets.
+         */
+        LoD ToAbsOffset(const LoD &in);
+
+        bool operator==(const LoD &a, const LoD &b);
+
+        /*
+         * Check whether this lod's format is valid.
+         *
+         * ATTENTION:
+         *   - Empty lod is treated as valid.
+         *
+         * It will check two things:
+         *
+         *  1. all the offsets in a level should be ascending(no same items
+         * allows).
+         *  2. there should be more than 2 offsets existing in each level.
+         *  3. the higher level's last offset should equals the lower level's
+         * size-1.
+         *  4. the first offset(the begin offset) of each level should be 0.
+         *  5. the lowest level's last offset should equals `tensor_height` if
+         * tensor_height>0.
+         */
+
+        bool CheckLoD(const LoD &in, int tensor_height = -1);
+
+        /*
+         * Check whether this absolute lod's format is valid.
+         *
+         * ATTENTION:
+         *   - Empty lod is treated as valid.
+         *
+         * It will check two things:
+         *  1. all the offsets in a level should be ascending(no same items
+         * allows)
+         *  2. there should be more than 2 offsets existing in each level.
+         *  3. the first offset of each level should be 0, and the last should
+         * be the
+         *     same(the height of underlying tensor) or `tensor_height` if
+         *     tensor_height>0.
+         */
+        bool CheckAbsLoD(const LoD &in, int tensor_height = -1);
+
+        /*
+         * LoDTensor (Level of details Tensor)
+         * see https://en.wikipedia.org/wiki/Level_of_details for reference.
+         */
+        class LoDTensor : public Tensor {
+          public:
+            LoDTensor() : Tensor() {}
+
+            explicit LoDTensor(const LoD &lod) : lod_(lod) {}
+
+            void set_lod(const LoD &lod) { lod_ = lod; }
+
+            const LoD &lod() const { return lod_; }
+
+            LoD *mutable_lod() { return &lod_; }
+
+            /*
+             * Get the start offset and end offset of an  element from LoD.
+             */
+            std::pair<size_t, size_t> lod_element(size_t level,
+                                                  size_t elem) const {
+                //    PADDLE_ENFORCE_LT(level, NumLevels());
+                //    PADDLE_ENFORCE_LT(elem, NumElements(level));
+                return std::make_pair((lod_)[level][elem],
+                                      (lod_)[level][elem + 1]);
+            }
+
+            /*
+             * Number of LoDTensor's levels, each level has units of data, for
+             * example,
+             * in the sentence's view, article, paragraph, sentence are 3
+             * levels.
+             */
+            size_t NumLevels() const { return lod_.size(); }
+
+            /*
+             * Number of elements in a level.
+             */
+            size_t NumElements(size_t level = 0) const {
+                //    PADDLE_ENFORCE_LT(level, NumLevels());
+                // the last offset is the end of last element
+                return (lod_)[level].size() - 1;
+            }
+
+          private:
+            LoD lod_;
+        };
+
+        /*
+         * Expand the `source` to fit the LoD of `lod`. For example, a `source`
+         * LoDTensor is
+         *  - LoD: [0, 2]
+         *  - tensor: [a0, a1]
+         * a `lod` is
+         *  - LoD: [0 3 5]
+         * returns a new LoDTensor
+         *  - [a0 a0 a0 a1 a1]
+         */
+        template <typename T>
+        LoDTensor LodExpand(const LoDTensor &source, const LoD &lod,
+                            size_t level) {
+            LoD abs_lod = ToAbsOffset(lod);
+            const auto &lod_level = lod[level];
+            size_t num_instances = source.dims()[0];
+
+            // new tensor
+            LoDTensor tensor;
+            tensor.set_lod(lod);
+            auto dims = source.dims();
+            dims[0] = lod_level.back();
+            tensor.Resize(dims);
+            tensor.mutable_data<T>();
+
+            //  PADDLE_ENFORCE_EQ(num_instances, lod_level.size() - 1);
+            for (size_t ins = 0; ins < num_instances; ins++) {
+                for (size_t elem = lod_level[ins]; elem < lod_level[ins + 1];
+                     elem++) {
+                    auto slice = tensor.Slice(elem, elem + 1);
+                    TensorCopy(source.Slice(ins, ins + 1), &slice);
+                }
+            }
+            return tensor;
+        }
+
+        // Get the absolute offset of a lod[start_level][start_idx:end_idx] and
+        // relative length of details for every levels(i.e., [start_level: ]).
+        //
+        // For example,
+        //   lod = [[0, 3, 4, 8], [0, 9, 10, 11, 13, 17, 19, 22, 24]]
+        //   start_level = 0
+        //   start_idx = 1
+        //   end_idx = 3
+        //
+        // Returns:
+        //  LoD = [[1, 4], [2, 4, 2, 3, 2]]
+        //  pair<size_t, size_t> = {11, 24}
+        std::pair<LoD, std::pair<size_t, size_t>>
+        GetSubLoDAndAbsoluteOffset(const LoD &lod, size_t start_idx,
+                                   size_t end_idx, size_t start_level);
+
+        void AppendLoD(LoD *lod, const LoD &lod_length);
+
+        /*
+         * Serialize/Desiralize LoDTensor to std::ostream
+         * You can pass ofstream or ostringstream to serilize to file
+         * or to a in memory string. GPU tensor will be copied to CPU.
+         */
+        void SerializeToStream(std::ostream &os, const LoDTensor &tensor);
+
+        void DeserializeFromStream(std::istream &is, LoDTensor *tensor);
+
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/op_desc.cpp

@@ -5,55 +5,58 @@
 #include "op_desc.h"
 
 namespace paddle_mobile {
-namespace framework {
-
-OpDesc::OpDesc(const proto::OpDesc &desc) : desc_(desc) {
-  for (int i = 0; i < desc_.inputs_size(); ++i) {
-    const proto::OpDesc::Var &var = desc_.inputs(i);
-    std::vector<std::string> &args = inputs_[var.parameter()];
-    int arg_size = var.arguments_size();
-    for (int j = 0; j < arg_size; ++j) {
-      args.push_back(var.arguments(j));
-    }
-  }
-
-  for (int i = 0; i < desc_.outputs_size(); ++i) {
-    const proto::OpDesc::Var &var = desc_.outputs(i);
-    std::vector<std::string> &args = outputs_[var.parameter()];
-    int arg_size = var.arguments_size();
-    for (int j = 0; j < arg_size; ++j) {
-      args.push_back(var.arguments(j));
-    }
-  }
-
-  for (const proto::OpDesc::Attr &attr : desc_.attrs()) {
-    std::string attr_name = attr.name();
-    if (attr.type() != proto::AttrType::BLOCK) {
-      attrs_[attr_name] = Attribute::GetAttrValue(attr);
-      //      if (attr.type() == proto::AttrType::INT){
-      //        std::cout << " attrName " << attr_name << " " <<
-      //        attrs_[attr_name].Get<int>() << std::endl;
-      //      }
-    }
-  }
-}
-
-const std::vector<std::string> &OpDesc::Input(const std::string &name) const {
-  return inputs_.find(name)->second;
-}
-
-const std::vector<std::string> &OpDesc::Output(const std::string &name) const {
-  return outputs_.find(name)->second;
-}
-
-Attribute OpDesc::GetAttr(const std::string &name) const {
-  auto it = attrs_.find(name);
-  return it->second;
-}
-
-const std::unordered_map<std::string, Attribute> &OpDesc::GetAttrMap() const {
-  return attrs_;
-}
-
-} // namespace framework
+    namespace framework {
+
+        OpDesc::OpDesc(const proto::OpDesc &desc) : desc_(desc) {
+            for (int i = 0; i < desc_.inputs_size(); ++i) {
+                const proto::OpDesc::Var &var = desc_.inputs(i);
+                std::vector<std::string> &args = inputs_[var.parameter()];
+                int arg_size = var.arguments_size();
+                for (int j = 0; j < arg_size; ++j) {
+                    args.push_back(var.arguments(j));
+                }
+            }
+
+            for (int i = 0; i < desc_.outputs_size(); ++i) {
+                const proto::OpDesc::Var &var = desc_.outputs(i);
+                std::vector<std::string> &args = outputs_[var.parameter()];
+                int arg_size = var.arguments_size();
+                for (int j = 0; j < arg_size; ++j) {
+                    args.push_back(var.arguments(j));
+                }
+            }
+
+            for (const proto::OpDesc::Attr &attr : desc_.attrs()) {
+                std::string attr_name = attr.name();
+                if (attr.type() != proto::AttrType::BLOCK) {
+                    attrs_[attr_name] = Attribute::GetAttrValue(attr);
+                    //      if (attr.type() == proto::AttrType::INT){
+                    //        std::cout << " attrName " << attr_name << " " <<
+                    //        attrs_[attr_name].Get<int>() << std::endl;
+                    //      }
+                }
+            }
+        }
+
+        const std::vector<std::string> &
+        OpDesc::Input(const std::string &name) const {
+            return inputs_.find(name)->second;
+        }
+
+        const std::vector<std::string> &
+        OpDesc::Output(const std::string &name) const {
+            return outputs_.find(name)->second;
+        }
+
+        Attribute OpDesc::GetAttr(const std::string &name) const {
+            auto it = attrs_.find(name);
+            return it->second;
+        }
+
+        const std::unordered_map<std::string, Attribute> &
+        OpDesc::GetAttrMap() const {
+            return attrs_;
+        }
+
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/op_desc.h

@@ -23,29 +23,31 @@ SOFTWARE.
 #include "paddle_mobile_object.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-class OpDesc : PaddleMobileObject {
-public:
-  OpDesc(const proto::OpDesc &desc);
-  const std::vector<std::string> &Input(const std::string &name) const;
-  const std::vector<std::string> &Output(const std::string &name) const;
-  Attribute GetAttr(const std::string &name) const;
+        class OpDesc : PaddleMobileObject {
+          public:
+            OpDesc(const proto::OpDesc &desc);
+            const std::vector<std::string> &
+            Input(const std::string &name) const;
+            const std::vector<std::string> &
+            Output(const std::string &name) const;
+            Attribute GetAttr(const std::string &name) const;
 
-  const VariableNameMap &GetInputs() { return inputs_; }
+            const VariableNameMap &GetInputs() { return inputs_; }
 
-  const VariableNameMap &GetOutputs() { return outputs_; }
+            const VariableNameMap &GetOutputs() { return outputs_; }
 
-  const AttributeMap &GetAttrMap() const;
+            const AttributeMap &GetAttrMap() const;
 
-  const std::string &Type() { return desc_.type(); };
+            const std::string &Type() { return desc_.type(); };
 
-private:
-  proto::OpDesc desc_;
-  VariableNameMap inputs_;
-  VariableNameMap outputs_;
-  AttributeMap attrs_;
-};
+          private:
+            proto::OpDesc desc_;
+            VariableNameMap inputs_;
+            VariableNameMap outputs_;
+            AttributeMap attrs_;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/op_info.h

@@ -22,70 +22,74 @@ SOFTWARE.
 #include "framework.pb.h"
 
 namespace paddle_mobile {
-namespace framework {
-
-template <typename Dtype> struct OpInfo {
-  OpCreator<Dtype> creator_;
-  const OpCreator<Dtype> &Creator() const {
-    //    PADDLE_ENFORCE_NOT_NULL(creator_,
-    //                            "Operator Creator has not been registered");
-    return creator_;
-  }
-};
-
-template <typename Dtype> class OpInfoMap;
-
-template <typename Dtype> static OpInfoMap<Dtype> *g_op_info_map = nullptr;
-
-template <typename Dtype> class OpInfoMap {
-public:
-  static OpInfoMap &Instance() {
-    if (g_op_info_map<Dtype> == nullptr) {
-      g_op_info_map<Dtype> = new OpInfoMap();
-    }
-    return *g_op_info_map<Dtype>;
-  };
-
-  bool Has(const std::string &op_type) const {
-    return map_.find(op_type) != map_.end();
-  }
-
-  void Insert(const std::string &type, const OpInfo<Dtype> &info) {
-    //    PADDLE_ENFORCE(!Has(type), "Operator %s has been registered", type);
-    map_.insert({type, info});
-  }
-
-  const OpInfo<Dtype> &Get(const std::string &type) const {
-    auto op_info_ptr = GetNullable(type);
-    //    PADDLE_ENFORCE_NOT_NULL(op_info_ptr, "Operator %s has not been
-    //    registered",
-    //                            type);
-    return *op_info_ptr;
-  }
-
-  const OpInfo<Dtype> *GetNullable(const std::string &type) const {
-    auto it = map_.find(type);
-    if (it == map_.end()) {
-      return nullptr;
-    } else {
-      return &it->second;
-    }
-  }
-
-  const std::unordered_map<std::string, OpInfo<Dtype>> &map() const {
-    return map_;
-  }
-
-  std::unordered_map<std::string, OpInfo<Dtype>> *mutable_map() {
-    return &map_;
-  }
-
-private:
-  OpInfoMap() = default;
-  std::unordered_map<std::string, OpInfo<Dtype>> map_;
-
-  //  DISABLE_COPY_AND_ASSIGN(OpInfoMap);
-};
-
-} // namespace framework
+    namespace framework {
+
+        template <typename Dtype> struct OpInfo {
+            OpCreator<Dtype> creator_;
+            const OpCreator<Dtype> &Creator() const {
+                //    PADDLE_ENFORCE_NOT_NULL(creator_,
+                //                            "Operator Creator has not been
+                //                            registered");
+                return creator_;
+            }
+        };
+
+        template <typename Dtype> class OpInfoMap;
+
+        template <typename Dtype>
+        static OpInfoMap<Dtype> *g_op_info_map = nullptr;
+
+        template <typename Dtype> class OpInfoMap {
+          public:
+            static OpInfoMap &Instance() {
+                if (g_op_info_map<Dtype> == nullptr) {
+                    g_op_info_map<Dtype> = new OpInfoMap();
+                }
+                return *g_op_info_map<Dtype>;
+            };
+
+            bool Has(const std::string &op_type) const {
+                return map_.find(op_type) != map_.end();
+            }
+
+            void Insert(const std::string &type, const OpInfo<Dtype> &info) {
+                //    PADDLE_ENFORCE(!Has(type), "Operator %s has been
+                //    registered", type);
+                map_.insert({type, info});
+            }
+
+            const OpInfo<Dtype> &Get(const std::string &type) const {
+                auto op_info_ptr = GetNullable(type);
+                //    PADDLE_ENFORCE_NOT_NULL(op_info_ptr, "Operator %s has not
+                //    been
+                //    registered",
+                //                            type);
+                return *op_info_ptr;
+            }
+
+            const OpInfo<Dtype> *GetNullable(const std::string &type) const {
+                auto it = map_.find(type);
+                if (it == map_.end()) {
+                    return nullptr;
+                } else {
+                    return &it->second;
+                }
+            }
+
+            const std::unordered_map<std::string, OpInfo<Dtype>> &map() const {
+                return map_;
+            }
+
+            std::unordered_map<std::string, OpInfo<Dtype>> *mutable_map() {
+                return &map_;
+            }
+
+          private:
+            OpInfoMap() = default;
+            std::unordered_map<std::string, OpInfo<Dtype>> map_;
+
+            //  DISABLE_COPY_AND_ASSIGN(OpInfoMap);
+        };
+
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/op_kernel_type.h

@@ -22,43 +22,51 @@ SOFTWARE.
 #include "framework.pb.h"
 
 namespace paddle_mobile {
-namespace framework {
-struct OpKernelType {
-  struct Hash {
-    size_t operator()(const OpKernelType &key) const {
-      int data_type = static_cast<int>(key.data_type_) << LEFT_SHIFT;
-      int data_layout = static_cast<int>(key.data_layout_) << (LEFT_SHIFT * 2);
+    namespace framework {
+        struct OpKernelType {
+            struct Hash {
+                size_t operator()(const OpKernelType &key) const {
+                    int data_type = static_cast<int>(key.data_type_)
+                                    << LEFT_SHIFT;
+                    int data_layout = static_cast<int>(key.data_layout_)
+                                      << (LEFT_SHIFT * 2);
 
-      std::hash<int> hasher;
-      return hasher(data_type + data_layout);
-    }
-  };
+                    std::hash<int> hasher;
+                    return hasher(data_type + data_layout);
+                }
+            };
 
-  // place, data_type, library_type kinds less than 2^8
-  constexpr static int LEFT_SHIFT = 8;
+            // place, data_type, library_type kinds less than 2^8
+            constexpr static int LEFT_SHIFT = 8;
 
-  proto::VarType::Type data_type_;
-  DataLayout data_layout_;
+            proto::VarType::Type data_type_;
+            DataLayout data_layout_;
 
-  OpKernelType(proto::VarType::Type data_type,
-               DataLayout data_layout = DataLayout::kAnyLayout)
-      : data_type_(data_type), data_layout_(data_layout) {}
+            OpKernelType(proto::VarType::Type data_type,
+                         DataLayout data_layout = DataLayout::kAnyLayout)
+                : data_type_(data_type), data_layout_(data_layout) {}
 
-  bool operator==(const OpKernelType &o) const {
-    return data_type_ == o.data_type_ && data_layout_ == o.data_layout_;
-  }
+            bool operator==(const OpKernelType &o) const {
+                return data_type_ == o.data_type_ &&
+                       data_layout_ == o.data_layout_;
+            }
 
-  bool operator!=(const OpKernelType &o) const { return !(*this == o); }
-};
+            bool operator!=(const OpKernelType &o) const {
+                return !(*this == o);
+            }
+        };
 
-inline bool NeedTransformLayout(const DataLayout &l, const DataLayout &r) {
-  return l != DataLayout::kAnyLayout && r != DataLayout::kAnyLayout && l != r;
-}
+        inline bool NeedTransformLayout(const DataLayout &l,
+                                        const DataLayout &r) {
+            return l != DataLayout::kAnyLayout && r != DataLayout::kAnyLayout &&
+                   l != r;
+        }
 
-inline bool TransFromNeeded(const OpKernelType &l, const OpKernelType &r) {
-  return (l.data_type_ != r.data_type_) ||
-         NeedTransformLayout(l.data_layout_, r.data_layout_);
-}
+        inline bool TransFromNeeded(const OpKernelType &l,
+                                    const OpKernelType &r) {
+            return (l.data_type_ != r.data_type_) ||
+                   NeedTransformLayout(l.data_layout_, r.data_layout_);
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/op_proto_maker.h

@@ -19,8 +19,8 @@ SOFTWARE.
 #pragma once
 
 namespace paddle_mobile {
-namespace framework {
-// this class not only make proto but also init attribute checkers.
-class OpProtoAndCheckerMaker {};
-} // namespace framework
+    namespace framework {
+        // this class not only make proto but also init attribute checkers.
+        class OpProtoAndCheckerMaker {};
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/operator.cpp

@@ -20,26 +20,26 @@ SOFTWARE.
 #include "op_info.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-template <typename Dtype>
-OperatorBase<Dtype>::OperatorBase(const std::string &type,
-                                  const VariableNameMap &inputs,
-                                  const VariableNameMap &outputs,
-                                  const AttributeMap &attrs,
-                                  std::shared_ptr<Scope> scope)
-    : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs),
-      scope_(scope) {
-  CheckAllInputOutputSet();
-}
+        template <typename Dtype>
+        OperatorBase<Dtype>::OperatorBase(const std::string &type,
+                                          const VariableNameMap &inputs,
+                                          const VariableNameMap &outputs,
+                                          const AttributeMap &attrs,
+                                          std::shared_ptr<Scope> scope)
+            : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs),
+              scope_(scope) {
+            CheckAllInputOutputSet();
+        }
 
-template <typename Dtype> void OperatorBase<Dtype>::Run() { RunImpl(); }
+        template <typename Dtype> void OperatorBase<Dtype>::Run() { RunImpl(); }
 
-template <typename Dtype>
-void OperatorBase<Dtype>::CheckAllInputOutputSet() const {}
+        template <typename Dtype>
+        void OperatorBase<Dtype>::CheckAllInputOutputSet() const {}
 
-template class OperatorBase<CPU>;
-template class OperatorWithKernel<CPU>;
+        template class OperatorBase<CPU>;
+        template class OperatorWithKernel<CPU>;
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/operator.h

@@ -33,53 +33,57 @@ SOFTWARE.
 #include "variable.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-template <typename Dtype> class OperatorBase : PaddleMobileObject {
-public:
-  OperatorBase(const std::string &type, const VariableNameMap &inputs,
-               const VariableNameMap &outputs, const AttributeMap &attrs,
-               std::shared_ptr<Scope> scope);
-  virtual ~OperatorBase() {}
-  virtual void Run();
-  const VariableNameMap &Inputs() const { return inputs_; }
-  const VariableNameMap &Outputs() const { return outputs_; }
-  const std::string &Type() const { return type_; }
-  const AttributeMap &Attrs() const { return attrs_; }
+        template <typename Dtype> class OperatorBase : PaddleMobileObject {
+          public:
+            OperatorBase(const std::string &type, const VariableNameMap &inputs,
+                         const VariableNameMap &outputs,
+                         const AttributeMap &attrs,
+                         std::shared_ptr<Scope> scope);
+            virtual ~OperatorBase() {}
+            virtual void Run();
+            const VariableNameMap &Inputs() const { return inputs_; }
+            const VariableNameMap &Outputs() const { return outputs_; }
+            const std::string &Type() const { return type_; }
+            const AttributeMap &Attrs() const { return attrs_; }
 
-protected:
-  std::shared_ptr<Scope> scope_;
-  std::string type_;
-  VariableNameMap inputs_;
-  VariableNameMap outputs_;
-  AttributeMap attrs_;
+          protected:
+            std::shared_ptr<Scope> scope_;
+            std::string type_;
+            VariableNameMap inputs_;
+            VariableNameMap outputs_;
+            AttributeMap attrs_;
 
-private:
-  void CheckAllInputOutputSet() const;
-  virtual void RunImpl() const = 0;
-};
+          private:
+            void CheckAllInputOutputSet() const;
+            virtual void RunImpl() const = 0;
+        };
 
-template <typename Dtype>
-class OperatorWithKernel : public OperatorBase<Dtype> {
-public:
-  OperatorWithKernel(const std::string &type, const VariableNameMap &inputs,
-                     const VariableNameMap &outputs, const AttributeMap &attrs,
-                     std::shared_ptr<Scope> scope)
-      : OperatorBase<Dtype>(type, inputs, outputs, attrs, scope) {}
-  virtual void InferShape() const = 0;
+        template <typename Dtype>
+        class OperatorWithKernel : public OperatorBase<Dtype> {
+          public:
+            OperatorWithKernel(const std::string &type,
+                               const VariableNameMap &inputs,
+                               const VariableNameMap &outputs,
+                               const AttributeMap &attrs,
+                               std::shared_ptr<Scope> scope)
+                : OperatorBase<Dtype>(type, inputs, outputs, attrs, scope) {}
+            virtual void InferShape() const = 0;
 
-protected:
-  virtual void RunImpl() const = 0;
+          protected:
+            virtual void RunImpl() const = 0;
 
-private:
-};
+          private:
+        };
 
-template <typename Dtype, typename P> class OpKernelBase : PaddleMobileObject {
-public:
-  virtual void Compute(const P &para) const = 0;
+        template <typename Dtype, typename P>
+        class OpKernelBase : PaddleMobileObject {
+          public:
+            virtual void Compute(const P &para) const = 0;
 
-  virtual ~OpKernelBase() = default;
-};
+            virtual ~OpKernelBase() = default;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/paddle_mobile_object.h

@@ -23,14 +23,14 @@ SOFTWARE.
 
 namespace paddle_mobile {
 
-class PaddleMobileObject {
-public:
-  virtual inline const std::string &ToString() {
-    char address[128] = {0};
-    sprintf(address, "%p", this);
-    return std::string(address);
-  }
+    class PaddleMobileObject {
+      public:
+        virtual inline const std::string &ToString() {
+            char address[128] = {0};
+            sprintf(address, "%p", this);
+            return std::string(address);
+        }
 
-private:
-};
+      private:
+    };
 } // namespace paddle_mobile

src/framework/program.cpp

@@ -17,5 +17,5 @@ SOFTWARE.
 ==============================================================================*/
 
 namespace paddle_mobile {
-namespace framework {}
+    namespace framework {}
 } // namespace paddle_mobile

src/framework/program.h

@@ -24,17 +24,17 @@ SOFTWARE.
 #include "scope.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-template <typename Dtype, Precision P = Precision::FP32>
-class Program : PaddleMobileObject {
-public:
-  std::shared_ptr<ProgramDesc> originProgram;
-  std::shared_ptr<ProgramDesc> optimizeProgram;
-  std::shared_ptr<Scope> scope;
+        template <typename Dtype, Precision P = Precision::FP32>
+        class Program : PaddleMobileObject {
+          public:
+            std::shared_ptr<ProgramDesc> originProgram;
+            std::shared_ptr<ProgramDesc> optimizeProgram;
+            std::shared_ptr<Scope> scope;
 
-private:
-};
+          private:
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/program_desc.cpp

@@ -5,18 +5,18 @@
 #include "program_desc.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-ProgramDesc::ProgramDesc(const proto::ProgramDesc &desc) : desc_(desc) {
-  for (auto &block_desc : *desc_.mutable_blocks()) {
-    // new framework::BlockDesc(block_desc)
-    blocks_.emplace_back(std::make_shared<BlockDesc>(block_desc));
-  }
-}
+        ProgramDesc::ProgramDesc(const proto::ProgramDesc &desc) : desc_(desc) {
+            for (auto &block_desc : *desc_.mutable_blocks()) {
+                // new framework::BlockDesc(block_desc)
+                blocks_.emplace_back(std::make_shared<BlockDesc>(block_desc));
+            }
+        }
 
-std::shared_ptr<BlockDesc> ProgramDesc::Block(size_t idx) {
-  return blocks_[idx];
-}
+        std::shared_ptr<BlockDesc> ProgramDesc::Block(size_t idx) {
+            return blocks_[idx];
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/program_desc.h

@@ -25,18 +25,20 @@ SOFTWARE.
 #include "paddle_mobile_object.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-class ProgramDesc : PaddleMobileObject {
-public:
-  ProgramDesc(const proto::ProgramDesc &desc);
-  std::shared_ptr<BlockDesc> Block(size_t idx);
-  const std::vector<std::shared_ptr<BlockDesc>> &Blocks() { return blocks_; };
+        class ProgramDesc : PaddleMobileObject {
+          public:
+            ProgramDesc(const proto::ProgramDesc &desc);
+            std::shared_ptr<BlockDesc> Block(size_t idx);
+            const std::vector<std::shared_ptr<BlockDesc>> &Blocks() {
+                return blocks_;
+            };
 
-private:
-  std::vector<std::shared_ptr<BlockDesc>> blocks_;
-  proto::ProgramDesc desc_;
-};
+          private:
+            std::vector<std::shared_ptr<BlockDesc>> blocks_;
+            proto::ProgramDesc desc_;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/scope.cc

@@ -4,113 +4,116 @@
 #include <vector>
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-Scope &Scope::NewScope() const {
-  std::unique_lock<std::mutex> lock(mutex_);
-  kids_.push_back(new Scope(this));
-  return *kids_.back();
-}
+        Scope &Scope::NewScope() const {
+            std::unique_lock<std::mutex> lock(mutex_);
+            kids_.push_back(new Scope(this));
+            return *kids_.back();
+        }
 
-Variable *Scope::Var(const std::string &name) {
-  auto *pvar = FindVarLocally(name);
-  if (pvar != nullptr) {
-    return pvar;
-  };
-  pvar = new Variable;
-  vars_[name] = pvar;
-  pvar->name_ = &(vars_.find(name)->first);
-  return pvar;
-}
+        Variable *Scope::Var(const std::string &name) {
+            auto *pvar = FindVarLocally(name);
+            if (pvar != nullptr) {
+                return pvar;
+            };
+            pvar = new Variable;
+            vars_[name] = pvar;
+            pvar->name_ = &(vars_.find(name)->first);
+            return pvar;
+        }
 
-//            Variable* Scope::Var(std::string* name) {
-//                auto var_name = string::Sprintf("%p.%d", this, vars_.size());
-//                if (name != nullptr) {
-//                    *name = var_name;
-//                }
-//                return Var(var_name);
-//            }
+        //            Variable* Scope::Var(std::string* name) {
+        //                auto var_name = string::Sprintf("%p.%d", this,
+        //                vars_.size());
+        //                if (name != nullptr) {
+        //                    *name = var_name;
+        //                }
+        //                return Var(var_name);
+        //            }
 
-Variable *Scope::FindVar(const std::string &name) const {
-  auto *pvar = FindVarLocally(name);
-  if (pvar != nullptr) {
-    return pvar;
-  }
-  return (parent_ == nullptr) ? nullptr : parent_->FindVar(name);
-}
+        Variable *Scope::FindVar(const std::string &name) const {
+            auto *pvar = FindVarLocally(name);
+            if (pvar != nullptr) {
+                return pvar;
+            }
+            return (parent_ == nullptr) ? nullptr : parent_->FindVar(name);
+        }
 
-const Scope *Scope::FindScope(const Variable *var) const {
-  for (auto &name_var : vars_) {
-    if (name_var.second == var) {
-      return this;
-    }
-  }
-  return (parent_ == nullptr) ? nullptr : parent_->FindScope(var);
-}
+        const Scope *Scope::FindScope(const Variable *var) const {
+            for (auto &name_var : vars_) {
+                if (name_var.second == var) {
+                    return this;
+                }
+            }
+            return (parent_ == nullptr) ? nullptr : parent_->FindScope(var);
+        }
 
-void Scope::DropKids() {
-  for (Scope *s : kids_) {
-    delete s;
-  }
-  kids_.clear();
-}
+        void Scope::DropKids() {
+            for (Scope *s : kids_) {
+                delete s;
+            }
+            kids_.clear();
+        }
 
-std::vector<std::string> Scope::LocalVarNames() const {
-  std::vector<std::string> known_vars;
-  known_vars.reserve(vars_.size());
-  for (auto &name_var : vars_) {
-    known_vars.emplace_back(name_var.first);
-  }
-  return known_vars;
-}
+        std::vector<std::string> Scope::LocalVarNames() const {
+            std::vector<std::string> known_vars;
+            known_vars.reserve(vars_.size());
+            for (auto &name_var : vars_) {
+                known_vars.emplace_back(name_var.first);
+            }
+            return known_vars;
+        }
 
-void Scope::DeleteScope(Scope *scope) const {
-  std::unique_lock<std::mutex> lock(mutex_);
-  auto it = std::find(kids_.begin(), kids_.end(), scope);
-  kids_.erase(it);
-  delete scope;
-  // deferent
-}
+        void Scope::DeleteScope(Scope *scope) const {
+            std::unique_lock<std::mutex> lock(mutex_);
+            auto it = std::find(kids_.begin(), kids_.end(), scope);
+            kids_.erase(it);
+            delete scope;
+            // deferent
+        }
 
-void Scope::EraseVars(const std::vector<std::string> &var_names) {
-  std::set<std::string> var_set(var_names.begin(), var_names.end());
-  for (auto it = vars_.begin(); it != vars_.end();) {
-    if (var_set.find(it->first) != var_set.end()) {
-      delete it->second;
-      it = vars_.erase(it);
-    } else {
-      ++it;
-    }
-  }
-}
+        void Scope::EraseVars(const std::vector<std::string> &var_names) {
+            std::set<std::string> var_set(var_names.begin(), var_names.end());
+            for (auto it = vars_.begin(); it != vars_.end();) {
+                if (var_set.find(it->first) != var_set.end()) {
+                    delete it->second;
+                    it = vars_.erase(it);
+                } else {
+                    ++it;
+                }
+            }
+        }
 
-void Scope::Rename(const std::string &origin_name,
-                   const std::string &new_name) const {
-  auto origin_it = vars_.find(origin_name);
-  if (origin_it == vars_.end()) {
-    return;
-  }
-  auto new_it = vars_.find(new_name);
-  if (new_it != vars_.end()) {
-    return;
-  }
-  vars_[new_name] = origin_it->second;
-  vars_.erase(origin_it);
-}
-//
-//            std::string Scope::Rename(const std::string& origin_name) const {
-//                auto var_name = string::Sprintf("%p.%d", this, vars_.size());
-//                Rename(origin_name, var_name);
-//                return var_name;
-//            }
+        void Scope::Rename(const std::string &origin_name,
+                           const std::string &new_name) const {
+            auto origin_it = vars_.find(origin_name);
+            if (origin_it == vars_.end()) {
+                return;
+            }
+            auto new_it = vars_.find(new_name);
+            if (new_it != vars_.end()) {
+                return;
+            }
+            vars_[new_name] = origin_it->second;
+            vars_.erase(origin_it);
+        }
+        //
+        //            std::string Scope::Rename(const std::string& origin_name)
+        //            const {
+        //                auto var_name = string::Sprintf("%p.%d", this,
+        //                vars_.size());
+        //                Rename(origin_name, var_name);
+        //                return var_name;
+        //            }
 
-Variable *Scope::FindVarLocally(const std::string &name) const {
-  auto it = vars_.find(name);
-  if (it != vars_.end()) {
-    return it->second;
-  }
-  return nullptr;
-}
+        Variable *Scope::FindVarLocally(const std::string &name) const {
+            auto it = vars_.find(name);
+            if (it != vars_.end()) {
+                return it->second;
+            }
+            return nullptr;
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/scope.h

@@ -24,57 +24,58 @@ SOFTWARE.
 #include <unordered_map> //std::unordered_map
 
 namespace paddle_mobile {
-namespace framework {
-class Scope {
-public:
-  Scope() {}
-  ~Scope() {}
+    namespace framework {
+        class Scope {
+          public:
+            Scope() {}
+            ~Scope() {}
 
-  Scope &NewScope() const;
+            Scope &NewScope() const;
 
-  /// Create a variable with given name if it doesn't exist.
-  Variable *Var(const std::string &name);
+            /// Create a variable with given name if it doesn't exist.
+            Variable *Var(const std::string &name);
 
-  /// Create a variable with a scope-unique name.
-  Variable *Var(std::string *name = nullptr);
+            /// Create a variable with a scope-unique name.
+            Variable *Var(std::string *name = nullptr);
 
-  void EraseVars(const std::vector<std::string> &var_names);
+            void EraseVars(const std::vector<std::string> &var_names);
 
-  /// Find a variable in the scope or any of its ancestors.  Returns
-  /// nullptr if cannot find.
-  Variable *FindVar(const std::string &name) const;
+            /// Find a variable in the scope or any of its ancestors.  Returns
+            /// nullptr if cannot find.
+            Variable *FindVar(const std::string &name) const;
 
-  const Scope *parent() const { return parent_; }
+            const Scope *parent() const { return parent_; }
 
-  /// Find the scope or an ancestor scope that contains the given variable.
-  const Scope *FindScope(const Variable *var) const;
+            /// Find the scope or an ancestor scope that contains the given
+            /// variable.
+            const Scope *FindScope(const Variable *var) const;
 
-  void DeleteScope(Scope *scope) const;
+            void DeleteScope(Scope *scope) const;
 
-  /// Drop all kids scopes belonged to this scope.
-  void DropKids();
+            /// Drop all kids scopes belonged to this scope.
+            void DropKids();
 
-  // enumerate all the variables current contains.
-  std::vector<std::string> LocalVarNames() const;
+            // enumerate all the variables current contains.
+            std::vector<std::string> LocalVarNames() const;
 
-  // Rename variable to a new name
-  void Rename(const std::string &origin_name,
-              const std::string &new_name) const;
+            // Rename variable to a new name
+            void Rename(const std::string &origin_name,
+                        const std::string &new_name) const;
 
-  // Rename variable to a new name and return the new name
-  std::string Rename(const std::string &origin_name) const;
+            // Rename variable to a new name and return the new name
+            std::string Rename(const std::string &origin_name) const;
 
-  Variable *FindVarLocally(const std::string &name) const;
+            Variable *FindVarLocally(const std::string &name) const;
 
-private:
-  // Call Scope::NewScope for a sub-scope.
-  explicit Scope(Scope const *parent) : parent_(parent) {}
+          private:
+            // Call Scope::NewScope for a sub-scope.
+            explicit Scope(Scope const *parent) : parent_(parent) {}
 
-  mutable std::unordered_map<std::string, Variable *> vars_;
-  mutable std::list<Scope *> kids_;
-  Scope const *parent_{nullptr};
+            mutable std::unordered_map<std::string, Variable *> vars_;
+            mutable std::list<Scope *> kids_;
+            Scope const *parent_{nullptr};
 
-  mutable std::mutex mutex_;
-};
-} // namespace framework
+            mutable std::mutex mutex_;
+        };
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/selected_rows.h

@@ -24,57 +24,59 @@ SOFTWARE.
 #include "tensor.h"
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-class SelectedRows {
-public:
-  SelectedRows(const std::vector<int64_t> &rows, const int64_t &height)
-      : rows_(rows), height_(height) {
-    value_.reset(new Tensor());
-  }
+        class SelectedRows {
+          public:
+            SelectedRows(const std::vector<int64_t> &rows,
+                         const int64_t &height)
+                : rows_(rows), height_(height) {
+                value_.reset(new Tensor());
+            }
 
-  SelectedRows() {
-    height_ = 0;
-    value_.reset(new Tensor());
-  }
+            SelectedRows() {
+                height_ = 0;
+                value_.reset(new Tensor());
+            }
 
-  const Tensor &value() const { return *value_; }
+            const Tensor &value() const { return *value_; }
 
-  Tensor *mutable_value() { return value_.get(); }
+            Tensor *mutable_value() { return value_.get(); }
 
-  int64_t height() const { return height_; }
+            int64_t height() const { return height_; }
 
-  void set_height(int64_t height) { height_ = height; }
+            void set_height(int64_t height) { height_ = height; }
 
-  const std::vector<int64_t> &rows() const { return rows_; }
+            const std::vector<int64_t> &rows() const { return rows_; }
 
-  std::vector<int64_t> *mutable_rows() { return &rows_; }
+            std::vector<int64_t> *mutable_rows() { return &rows_; }
 
-  void set_rows(const std::vector<int64_t> &rows) { rows_ = rows; }
+            void set_rows(const std::vector<int64_t> &rows) { rows_ = rows; }
 
-  /**
-   * get the index of id in rows
-   */
-  int64_t index(int64_t id) const {
-    auto it = std::find(rows_.begin(), rows_.end(), id);
-    //    PADDLE_ENFORCE(it != rows_.end(), "id should be in rows");
-    return static_cast<int64_t>(std::distance(rows_.begin(), it));
-  }
+            /**
+             * get the index of id in rows
+             */
+            int64_t index(int64_t id) const {
+                auto it = std::find(rows_.begin(), rows_.end(), id);
+                //    PADDLE_ENFORCE(it != rows_.end(), "id should be in rows");
+                return static_cast<int64_t>(std::distance(rows_.begin(), it));
+            }
 
-  DDim GetCompleteDims() const {
-    std::vector<int64_t> dims = vectorize(value_->dims());
-    dims[0] = height_;
-    return make_ddim(dims);
-  }
+            DDim GetCompleteDims() const {
+                std::vector<int64_t> dims = vectorize(value_->dims());
+                dims[0] = height_;
+                return make_ddim(dims);
+            }
 
-private:
-  // Notice: rows can be duplicate. We can have {0, 4, 7, 0, 5, 7, 9} here.
-  // SelectedRows are simply concated when adding together. Until a
-  // SelectedRows add a Tensor, will the duplicate rows be handled.
-  std::vector<int64_t> rows_;
-  std::unique_ptr<Tensor> value_{nullptr};
-  int64_t height_;
-};
+          private:
+            // Notice: rows can be duplicate. We can have {0, 4, 7, 0, 5, 7, 9}
+            // here.
+            // SelectedRows are simply concated when adding together. Until a
+            // SelectedRows add a Tensor, will the duplicate rows be handled.
+            std::vector<int64_t> rows_;
+            std::unique_ptr<Tensor> value_{nullptr};
+            int64_t height_;
+        };
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/tensor_util.h

@@ -20,47 +20,47 @@ limitations under the License. */
 #include <vector>
 
 namespace paddle_mobile {
-namespace framework {
+    namespace framework {
 
-void TensorCopy(const Tensor &src, Tensor *dst);
-void TensorCopySync(const Tensor &src, Tensor *dst);
+        void TensorCopy(const Tensor &src, Tensor *dst);
+        void TensorCopySync(const Tensor &src, Tensor *dst);
 
-template <typename T>
-void TensorFromVector(const std::vector<T> &src, Tensor *dst);
+        template <typename T>
+        void TensorFromVector(const std::vector<T> &src, Tensor *dst);
 
-template <typename T>
-void TesnorToVector(const Tensor &src, std::vector<T> *dst);
+        template <typename T>
+        void TesnorToVector(const Tensor &src, std::vector<T> *dst);
 
-bool TensorContainsNAN(const framework::Tensor &tensor);
-bool TensorContainsInf(const framework::Tensor &tensor);
+        bool TensorContainsNAN(const framework::Tensor &tensor);
+        bool TensorContainsInf(const framework::Tensor &tensor);
 
-void TensorToStream(std::ostream &os, const Tensor &tensor);
-void TensorFromStream(std::istream &is, Tensor *tensor);
+        void TensorToStream(std::ostream &os, const Tensor &tensor);
+        void TensorFromStream(std::istream &is, Tensor *tensor);
 
-//
-// The implementation of template functions.
-//
+        //
+        // The implementation of template functions.
+        //
 
-template <typename T>
-void TensorFromVector(const std::vector<T> &src, Tensor *dst) {
-  auto src_ptr = static_cast<const void *>(src.data());
-  dst->Resize({static_cast<int64_t>(src.size())});
-  auto dst_ptr = static_cast<void *>(dst->mutable_data<T>());
-  auto size = src.size() * sizeof(T);
+        template <typename T>
+        void TensorFromVector(const std::vector<T> &src, Tensor *dst) {
+            auto src_ptr = static_cast<const void *>(src.data());
+            dst->Resize({static_cast<int64_t>(src.size())});
+            auto dst_ptr = static_cast<void *>(dst->mutable_data<T>());
+            auto size = src.size() * sizeof(T);
 
-  memory::Copy(dst_ptr, src_ptr, size);
-}
+            memory::Copy(dst_ptr, src_ptr, size);
+        }
 
-template <typename T>
-void TensorToVector(const Tensor &src, std::vector<T> *dst) {
-  auto src_ptr = static_cast<const void *>(src.data<T>());
-  auto size = src.numel() * sizeof(T);
+        template <typename T>
+        void TensorToVector(const Tensor &src, std::vector<T> *dst) {
+            auto src_ptr = static_cast<const void *>(src.data<T>());
+            auto size = src.numel() * sizeof(T);
 
-  dst->resize(src.numel());
-  auto dst_ptr = static_cast<void *>(dst->data());
+            dst->resize(src.numel());
+            auto dst_ptr = static_cast<void *>(dst->data());
 
-  memory::Copy(dst_ptr, src_ptr, size);
-}
+            memory::Copy(dst_ptr, src_ptr, size);
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/var_desc.cpp

@@ -20,9 +20,9 @@ SOFTWARE.
 
 namespace paddle_mobile {
 
-namespace framework {
+    namespace framework {
 
-VarDesc::VarDesc(const proto::VarDesc &desc) : desc_(desc) {}
+        VarDesc::VarDesc(const proto::VarDesc &desc) : desc_(desc) {}
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/framework/var_type.h

@@ -23,16 +23,17 @@ SOFTWARE.
 #include "variable.h"
 
 namespace paddle_mobile {
-namespace framework {
-inline proto::VarType::Type ToVarType(std::type_index type) {
-  if (type.hash_code() == typeid(LoDTensor).hash_code()) {
-    return proto::VarType_Type_LOD_TENSOR;
-  } else if (type.hash_code() == typeid(SelectedRows).hash_code()) {
-    return proto::VarType_Type_SELECTED_ROWS;
-  } else {
-    //    PADDLE_THROW("ToVarType:Unsupported type %s", type.name());
-  }
-}
+    namespace framework {
+        inline proto::VarType::Type ToVarType(std::type_index type) {
+            if (type.hash_code() == typeid(LoDTensor).hash_code()) {
+                return proto::VarType_Type_LOD_TENSOR;
+            } else if (type.hash_code() == typeid(SelectedRows).hash_code()) {
+                return proto::VarType_Type_SELECTED_ROWS;
+            } else {
+                //    PADDLE_THROW("ToVarType:Unsupported type %s",
+                //    type.name());
+            }
+        }
 
-} // namespace framework
+    } // namespace framework
 } // namespace paddle_mobile

src/io.h

@@ -27,13 +27,14 @@ SOFTWARE.
 
 namespace paddle_mobile {
 
-template <typename Dtype, Precision P = Precision::FP32>
-class Loader : PaddleMobileObject {
-public:
-  const framework::Program<Dtype, P> Load(const std::string &dirname);
+    template <typename Dtype, Precision P = Precision::FP32>
+    class Loader : PaddleMobileObject {
+      public:
+        const framework::Program<Dtype, P> Load(const std::string &dirname);
 
-private:
-  void LoadVar(framework::LoDTensor *tensor, const std::string &file_path);
-};
+      private:
+        void LoadVar(framework::LoDTensor *tensor,
+                     const std::string &file_path);
+    };
 
 } // namespace paddle_mobile

src/memory/t_malloc.cc

@@ -22,30 +22,30 @@ SOFTWARE.
 #include <cstring>
 
 namespace paddle_mobile {
-namespace memory {
-const int MALLOC_ALIGN = 16;
+    namespace memory {
+        const int MALLOC_ALIGN = 16;
 
-void Copy(void *dst, const void *src, size_t num) {
-  std::memcpy(dst, src, num);
-};
+        void Copy(void *dst, const void *src, size_t num) {
+            std::memcpy(dst, src, num);
+        };
 
-void *Alloc(size_t size) {
-  size_t offset = sizeof(void *) + MALLOC_ALIGN - 1;
-  char *p = static_cast<char *>(malloc(offset + size));
-  if (!p) {
-    return nullptr;
-  }
-  void *r = reinterpret_cast<void *>(reinterpret_cast<size_t>(p + offset) &
-                                     (~(MALLOC_ALIGN - 1)));
-  static_cast<void **>(r)[-1] = p;
-  return r;
-}
+        void *Alloc(size_t size) {
+            size_t offset = sizeof(void *) + MALLOC_ALIGN - 1;
+            char *p = static_cast<char *>(malloc(offset + size));
+            if (!p) {
+                return nullptr;
+            }
+            void *r = reinterpret_cast<void *>(
+                reinterpret_cast<size_t>(p + offset) & (~(MALLOC_ALIGN - 1)));
+            static_cast<void **>(r)[-1] = p;
+            return r;
+        }
 
-void Free(void *ptr) {
-  if (ptr) {
-    free(static_cast<void **>(ptr)[-1]);
-  }
-}
+        void Free(void *ptr) {
+            if (ptr) {
+                free(static_cast<void **>(ptr)[-1]);
+            }
+        }
 
-} // namespace memory
+    } // namespace memory
 } // namespace paddle_mobile