update for google code style

src/common/log.h

@@ -51,12 +51,13 @@ struct Print;
 struct Print {
   friend struct ToLog;
 
-  template <typename T> Print &operator<<(T const &value) {
+  template <typename T>
+  Print &operator<<(T const &value) {
     buffer_ << value;
     return *this;
   }
 
-private:
+ private:
   void print(LogLevel level) {
     buffer_ << std::endl;
     if (level == kLOG_ERROR) {
@@ -76,14 +77,15 @@ struct ToLog {
     printer_ << logs[level] << " " << info << ":" << std::string(blanks, ' ');
   }
 
-  template <typename T> ToLog &operator<<(T const &value) {
+  template <typename T>
+  ToLog &operator<<(T const &value) {
     printer_ << value;
     return *this;
   }
 
   ~ToLog() { printer_.print(level_); }
 
-private:
+ private:
   LogLevel level_;
   Print printer_;
 };
@@ -140,15 +142,19 @@ enum LogLevel {
 struct ToLog;
 struct Print {
   friend struct ToLog;
-  template <typename T> Print &operator<<(T const &value) {}
+  template <typename T>
+  Print &operator<<(T const &value) {}
 
-private:
+ private:
 };
 
 struct ToLog {
   ToLog(LogLevel level) {}
 
-  template <typename T> ToLog &operator<<(T const &value) { return *this; }
+  template <typename T>
+  ToLog &operator<<(T const &value) {
+    return *this;
+  }
 };
 
 #define LOG(level) \

src/common/type_define.h

@@ -17,14 +17,15 @@ SOFTWARE.
 ==============================================================================*/
 #pragma once;
 
-#include "framework/attribute.h"
 #include <map>
 #include <string>
+#include "framework/attribute.h"
 
 namespace paddle_mobile {
 
 namespace framework {
-template <typename Dtype> class OperatorBase;
+template <typename Dtype>
+class OperatorBase;
 class OpDesc;
 class BlockDesc;
 class InferShapeContext;

src/common/types.h

@@ -24,7 +24,8 @@ enum class Precision : int { FP32 = 0 };
 //! 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;

src/common/variant.h

@@ -21,9 +21,13 @@ 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 {
+template <typename F, typename... Ts>
+struct VariantHelper {
   static const size_t size = sizeof(F) > VariantHelper<Ts...>::size
                                  ? sizeof(F)
                                  : VariantHelper<Ts...>::size;
@@ -37,7 +41,8 @@ template <typename F, typename... Ts> struct VariantHelper {
   }
 };
 
-template <typename F> struct VariantHelper<F> {
+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()) {
@@ -48,8 +53,9 @@ template <typename F> struct VariantHelper<F> {
   }
 };
 
-template <size_t size> class RawData {
-public:
+template <size_t size>
+class RawData {
+ public:
   char data[size];
   RawData() {}
   RawData(const RawData &raw_data) { strcpy(data, raw_data.data); }
@@ -58,7 +64,8 @@ public:
   //      }
 };
 
-template <typename... Ts> struct Variant {
+template <typename... Ts>
+struct Variant {
   Variant(const Variant &variant) {
     //        std::cout << " 赋值构造函数 " << std::endl;
     type_id = variant.type_id;
@@ -70,13 +77,15 @@ template <typename... Ts> struct Variant {
     //        helper::Destroy(type_id, &data);
   }
 
-  template <typename T, typename... Args> void Set(Args &&... args) {
+  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 {
+  template <typename T>
+  T &Get() const {
     if (type_id == typeid(T).hash_code()) {
       return *const_cast<T *>(reinterpret_cast<const T *>(&data));
     } else {
@@ -87,13 +96,16 @@ template <typename... Ts> struct Variant {
 
   size_t TypeId() const { return type_id; }
 
-private:
+ 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.h

@@ -27,7 +27,7 @@ namespace framework {
 class BlockDesc;
 
 class Attribute {
-public:
+ public:
   static Attribute GetAttrValue(const proto::OpDesc::Attr &attr_desc) {
     //    std::cout << "begin get attr value" << std::endl;
     Attribute attr;
@@ -93,14 +93,18 @@ public:
   }
 
   Attribute() {}
-  template <typename T, typename... Args> Attribute &Set(Args &&... args) {
+  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:
+ private:
   Variant<int, float, std::string, std::vector<int>, std::vector<float>,
           std::vector<std::string>, bool, std::vector<bool>, BlockDesc *,
           int64_t>
@@ -110,10 +114,11 @@ private:
 using AttributeMap = std::unordered_map<std::string, Attribute>;
 
 class AttrReader {
-public:
+ public:
   explicit AttrReader(const AttributeMap &attrs) : attrs_(attrs) {}
 
-  template <typename T> inline T Get(const std::string &name) const {
+  template <typename T>
+  inline T Get(const std::string &name) const {
     //          PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should
     //          be in
     //          AttributeMap",
@@ -121,7 +126,7 @@ public:
     return ((Attribute)attrs_.at(name)).Get<T>();
   }
 
-private:
+ private:
   const AttributeMap &attrs_;
 };
 

src/framework/block_desc.h

@@ -27,7 +27,7 @@ namespace paddle_mobile {
 namespace framework {
 
 class BlockDesc : PaddleMobileObject {
-public:
+ public:
   BlockDesc(const proto::BlockDesc &desc);
 
   const int &ID() const { return desc_.idx(); }
@@ -45,7 +45,7 @@ public:
   std::vector<std::shared_ptr<VarDesc>> Vars() const;
   std::vector<std::shared_ptr<OpDesc>> Ops() const;
 
-private:
+ private:
   proto::BlockDesc desc_;
   std::vector<std::shared_ptr<OpDesc>> ops_;
   std::unordered_map<std::string, std::shared_ptr<VarDesc>> vars_;
@@ -56,7 +56,8 @@ private:
 
 namespace std {
 
-template <> struct hash<paddle_mobile::framework::BlockDesc> {
+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 {

src/framework/ddim.cc

@@ -19,11 +19,15 @@ namespace framework {
 
 /// @cond HIDDEN
 
-template <int i> Dim<i> make_dim(const int64_t *d) {
+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); }
+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) {
@@ -90,24 +94,28 @@ DDim make_ddim(const std::vector<int> &dims) {
 // XXX For some reason, putting this in an anonymous namespace causes
 // errors
 struct DynamicMutableIndexer : Vistor<int64_t &> {
-public:
+ public:
   explicit DynamicMutableIndexer(int idx) : idx_(idx) {}
 
-  template <int D> int64_t &operator()(Dim<D> &dim) const { return dim[idx_]; }
+  template <int D>
+  int64_t &operator()(Dim<D> &dim) const {
+    return dim[idx_];
+  }
 
-private:
+ private:
   int idx_;
 };
 
 struct DynamicConstIndexer : public Vistor<int64_t> {
-public:
+ public:
   explicit DynamicConstIndexer(int idx) : idx_(idx) {}
 
-  template <int D> int64_t operator()(const Dim<D> &dim) const {
+  template <int D>
+  int64_t operator()(const Dim<D> &dim) const {
     return dim[idx_];
   }
 
-private:
+ private:
   int idx_;
 };
 
@@ -182,7 +190,8 @@ struct VectorizeVisitor : Vistor<void> {
 
   explicit VectorizeVisitor(std::vector<int64_t> &v) : vector(v) {}
 
-  template <typename T> void operator()(const T &t) {
+  template <typename T>
+  void operator()(const T &t) {
     vector.push_back(t.head);
     this->operator()(t.tail);
   }
@@ -207,7 +216,8 @@ std::vector<int> vectorize2int(const DDim &ddim) {
 }
 
 struct ProductVisitor : Vistor<int64_t> {
-  template <int D> int64_t operator()(const Dim<D> &dim) {
+  template <int D>
+  int64_t operator()(const Dim<D> &dim) {
     return product(dim);
   }
 };
@@ -233,7 +243,8 @@ struct SliceVectorizeVisitor : Vistor<void> {
     //                   ddim slice.");
   }
 
-  template <int S> void operator()(const Dim<S> &dim) {
+  template <int S>
+  void operator()(const Dim<S> &dim) {
     if (begin == 0) {
       vector.push_back(dim.head);
     } else {
@@ -264,7 +275,10 @@ DDim slice_ddim(const DDim &ddim, int begin, int end) {
 /// \cond HIDDEN
 
 struct ArityVisitor : Vistor<int> {
-  template <int D> int operator()(Dim<D>) const { return D; }
+  template <int D>
+  int operator()(Dim<D>) const {
+    return D;
+  }
 };
 
 /// \endcond
@@ -282,11 +296,12 @@ int arity(const DDim &d) {
 struct OSVistor : Vistor<std::ostream &> {
   OSVistor(std::ostream &os) : os_(os) {}
 
-  template <int D> std::ostream &operator()(Dim<D> dim) const {
+  template <int D>
+  std::ostream &operator()(Dim<D> dim) const {
     return os_ << dim;
   }
 
-private:
+ private:
   std::ostream &os_;
 };
 

src/framework/ddim.h

@@ -14,12 +14,12 @@ limitations under the License. */
 
 #pragma once
 
-#include "common/variant.h"
-#include "dim.h"
 #include <assert.h>
 #include <initializer_list>
 #include <stdexcept>
 #include <vector>
+#include "common/variant.h"
+#include "dim.h"
 
 namespace paddle_mobile {
 namespace framework {
@@ -66,11 +66,15 @@ struct DDim {
 
   DDim() { var.Set<Dim<1>>(Dim<1>()); }
 
-  template <int D> explicit DDim(const Dim<D> &in) { var.Set<Dim<D>>(in); }
+  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) {
+  template <int D>
+  DDim &operator=(const Dim<D> &in) {
     var.Set<Dim<D>>(in);
     return *this;
   }

src/framework/dim.h

@@ -24,7 +24,8 @@ namespace paddle_mobile {
 namespace framework {
 
 // Statically sized, statically indexed dimension
-template <int i> struct Dim {
+template <int i>
+struct Dim {
   static constexpr int dimensions = i;
 
   template <typename... Args>
@@ -70,7 +71,8 @@ template <int i> struct Dim {
 };
 
 // Base case specialization
-template <> struct Dim<0> {
+template <>
+struct Dim<0> {
   static constexpr int dimensions = 0;
 
   HOSTDEVICE
@@ -105,28 +107,37 @@ template <> struct Dim<0> {
 namespace {
 
 // Helper for accessing Dim classes
-template <int i> struct DimGetter {
+template <int i>
+struct DimGetter {
   // Return a copy if Dim is const
-  template <typename D> HOSTDEVICE static int64_t impl(const D &d) {
+  template <typename D>
+  HOSTDEVICE static int64_t impl(const D &d) {
     return DimGetter<i - 1>::impl(d.tail);
   }
   // Return a reference if Dim is mutable
-  template <typename D> HOSTDEVICE static int64_t &impl(D &d) {
+  template <typename D>
+  HOSTDEVICE static int64_t &impl(D &d) {
     return DimGetter<i - 1>::impl(d.tail);
   }
 };
 
 // Eureka! We found the element!
-template <> struct DimGetter<0> {
+template <>
+struct DimGetter<0> {
   // Return a copy if Dim is const
-  template <typename D> HOSTDEVICE static int64_t impl(const D &d) {
+  template <typename D>
+  HOSTDEVICE static int64_t impl(const D &d) {
     return d.head;
   }
   // Return a reference if Dim is mutable
-  template <typename D> HOSTDEVICE static int64_t &impl(D &d) { return d.head; }
+  template <typename D>
+  HOSTDEVICE static int64_t &impl(D &d) {
+    return d.head;
+  }
 };
 
-template <int D> HOSTDEVICE int64_t &indexer(Dim<D> &dim, int idx) {
+template <int D>
+HOSTDEVICE int64_t &indexer(Dim<D> &dim, int idx) {
 #ifndef __CUDA_ARCH__
   if (idx < 0) {
     throw std::invalid_argument("Tried to access a negative dimension");
@@ -140,7 +151,8 @@ template <int D> HOSTDEVICE int64_t &indexer(Dim<D> &dim, int idx) {
   return indexer(dim.tail, idx - 1);
 }
 
-template <> HOSTDEVICE int64_t &indexer<0>(Dim<0> &dim, int idx) {
+template <>
+HOSTDEVICE int64_t &indexer<0>(Dim<0> &dim, int idx) {
 #ifndef __CUDA_ARCH__
   throw std::invalid_argument("Invalid index");
 #else
@@ -156,7 +168,8 @@ template <> HOSTDEVICE int64_t &indexer<0>(Dim<0> &dim, int idx) {
 #endif
 }
 
-template <int D> HOSTDEVICE int64_t indexer(const Dim<D> &dim, int idx) {
+template <int D>
+HOSTDEVICE int64_t indexer(const Dim<D> &dim, int idx) {
 #ifndef __CUDA_ARCH__
   if (idx < 0) {
     throw std::invalid_argument("Tried to access a negative dimension");
@@ -170,7 +183,8 @@ template <int D> HOSTDEVICE int64_t indexer(const Dim<D> &dim, int idx) {
   return indexer(dim.tail, idx - 1);
 }
 
-template <> HOSTDEVICE int64_t indexer<0>(const Dim<0> &dim, int idx) {
+template <>
+HOSTDEVICE int64_t indexer<0>(const Dim<0> &dim, int idx) {
 #ifndef __CUDA_ARCH__
   throw std::invalid_argument("Invalid index");
 #else
@@ -188,23 +202,27 @@ template <> HOSTDEVICE int64_t indexer<0>(const Dim<0> &dim, int idx) {
 
 }  // namespace
 // Static access to constant Dim
-template <int i, int l> HOSTDEVICE int64_t get(const Dim<l> &d) {
+template <int i, int l>
+HOSTDEVICE int64_t get(const Dim<l> &d) {
   return DimGetter<i>::impl(d);
 }
 
 // Static access to mutable Dim
-template <int i, int l> HOSTDEVICE int64_t &get(Dim<l> &d) {
+template <int i, int l>
+HOSTDEVICE int64_t &get(Dim<l> &d) {
   return DimGetter<i>::impl(d);
 }
 
 // Dynamic access to constant Dim
-template <int l> HOSTDEVICE int64_t Dim<l>::operator[](int i) const {
+template <int l>
+HOSTDEVICE int64_t Dim<l>::operator[](int i) const {
   //  std::cout << "l: " << l << std::endl;
   return indexer(*this, i);
 }
 
 // Dynamic access to mutable Dim
-template <int l> HOSTDEVICE int64_t &Dim<l>::operator[](int i) {
+template <int l>
+HOSTDEVICE int64_t &Dim<l>::operator[](int i) {
   return indexer(*this, i);
 }
 
@@ -247,13 +265,15 @@ HOSTDEVICE inline int64_t linearize(const Dim<0> &a, const Dim<0> &b) {
 }
 
 // Product of a Dim
-template <int i> HOSTDEVICE int64_t product(const Dim<i> &a, int prod = 1) {
+template <int i>
+HOSTDEVICE int64_t product(const Dim<i> &a, int prod = 1) {
   return prod * a.head * product(a.tail);
 }
 
 // Base case product of a Dim
 // Notice it is inline because it is no longer a template
-template <> HOSTDEVICE inline int64_t product(const Dim<0> &a, int prod) {
+template <>
+HOSTDEVICE inline int64_t product(const Dim<0> &a, int prod) {
   return prod;
 }
 
@@ -282,7 +302,8 @@ HOSTDEVICE Dim<i> ex_prefix_mul(const Dim<i> &src, int mul = 1) {
 ///\cond HIDDEN
 // Base case of ex_prefix_mul
 // Notice it is inline because it is no longer a template
-template <> HOSTDEVICE inline Dim<0> ex_prefix_mul(const Dim<0> &src, int mul) {
+template <>
+HOSTDEVICE inline Dim<0> ex_prefix_mul(const Dim<0> &src, int mul) {
   return Dim<0>();
 }
 ///\endcond
@@ -290,7 +311,8 @@ template <> HOSTDEVICE inline Dim<0> ex_prefix_mul(const Dim<0> &src, int mul) {
 /**
  * Add two dimensions together
  */
-template <int i> HOSTDEVICE Dim<i> dim_plus(const Dim<i> &a, const Dim<i> &b) {
+template <int i>
+HOSTDEVICE Dim<i> dim_plus(const Dim<i> &a, const Dim<i> &b) {
   return Dim<i>(a.head + b.head, dim_plus(a.tail, b.tail));
 }
 
@@ -308,7 +330,8 @@ HOSTDEVICE Dim<i> operator+(const Dim<i> &lhs, const Dim<i> &rhs) {
 /**
  * Multiply two dimensions together
  */
-template <int i> HOSTDEVICE Dim<i> dim_mult(const Dim<i> &a, const Dim<i> &b) {
+template <int i>
+HOSTDEVICE Dim<i> dim_mult(const Dim<i> &a, const Dim<i> &b) {
   return Dim<i>(a.head * b.head, dim_mult(a.tail, b.tail));
 }
 
@@ -365,8 +388,8 @@ HOSTDEVICE Dim<sizeof...(Args)> make_dim(Args... idxes) {
 // Allows us to output a Dim
 // XXX For some reason, overloading fails to resolve this correctly
 template <int i>
-typename std::enable_if<(i > 1), std::ostream &>::type
-operator<<(std::ostream &os, const Dim<i> &d) {
+typename std::enable_if<(i > 1), std::ostream &>::type operator<<(
+    std::ostream &os, const Dim<i> &d) {
   os << d.head << ", " << d.tail;
   return os;
 }
@@ -374,8 +397,8 @@ operator<<(std::ostream &os, const Dim<i> &d) {
 // Base case that allows us to output a Dim
 // XXX I wish this could be an overload instead of a template
 template <int i>
-typename std::enable_if<(i == 1), std::ostream &>::type
-operator<<(std::ostream &os, const Dim<i> &d) {
+typename std::enable_if<(i == 1), std::ostream &>::type operator<<(
+    std::ostream &os, const Dim<i> &d) {
   os << d.head;
   return os;
 }
@@ -384,7 +407,8 @@ inline std::ostream &operator<<(std::ostream &os, const Dim<0> &d) {
   return os;
 }
 
-template <int i> HOST std::string Dim<i>::to_string() const {
+template <int i>
+HOST std::string Dim<i>::to_string() const {
   std::stringstream stream;
 
   stream << *this;

src/framework/executor.h

@@ -34,15 +34,16 @@ SOFTWARE.
 namespace paddle_mobile {
 namespace framework {
 
-template <typename Dtype> class Executor {
-public:
+template <typename Dtype>
+class Executor {
+ public:
   Executor();
 
   Executor(const Program<Dtype> p);
 
   std::shared_ptr<Tensor> predict(Tensor &t);
 
-public:
+ public:
   const framework::Program<Dtype> program_;
   std::shared_ptr<ProgramDesc> to_predict_program_;
 

src/framework/lod_tensor.cc

@@ -13,10 +13,10 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "lod_tensor.h"
-#include <algorithm>
-#include <iterator>
 #include <stdint.h>
 #include <string.h>
+#include <algorithm>
+#include <iterator>
 
 namespace paddle_mobile {
 namespace framework {
@@ -105,8 +105,7 @@ LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin,
 
 LoD ToAbsOffset(const LoD &in) {
   // the lowest level stores relative offsets
-  if (in.empty() || in.size() == 1)
-    return in;
+  if (in.empty() || in.size() == 1) return in;
   LoD result = in;
   for (auto level = static_cast<int>(in.size() - 2); level >= 0; level--) {
     for (size_t i = 0; i < in[level].size(); ++i) {
@@ -138,23 +137,19 @@ bool operator==(const LoD &a, const LoD &b) {
 }
 
 bool CheckLoD(const LoD &in, int tensor_height) {
-  if (in.empty())
-    return true;
+  if (in.empty()) return true;
   for (const auto &level : in) {
     // check: there should be more than 2 offsets existing in each
     // level.
-    if (level.size() < 2)
-      return false;
+    if (level.size() < 2) return false;
     // check: the first offset(the begin offset) of each level
     // should be 0.
-    if (level.front() != 0)
-      return false;
+    if (level.front() != 0) return false;
     // check: all the offsets in a level should be ascending(no same
     // items
     // allows).
     if (!std::is_sorted(level.begin(), level.begin(), [](size_t a, size_t b) {
-          if (a < b)
-            return true;
+          if (a < b) return true;
           return false;
         })) {
       std::cout << "ascending error";
@@ -174,22 +169,19 @@ bool CheckLoD(const LoD &in, int tensor_height) {
   // goes
   // first.
   for (size_t level = 0; level < in.size() - 1; level++) {
-    if (in[level].back() != in[level + 1].size() - 1)
-      return false;
+    if (in[level].back() != in[level + 1].size() - 1) return false;
   }
   return true;
 }
 
 bool CheckAbsLoD(const LoD &in, int tensor_height) {
-  if (in.empty())
-    return true;
+  if (in.empty()) return true;
   for (const auto &level : in) {
     // check: all the offsets in a level should be ascending(no same
     // items
     // allows).
     if (!std::is_sorted(level.begin(), level.begin(), [](size_t a, size_t b) {
-          if (a < b)
-            return true;
+          if (a < b) return true;
           return false;
         })) {
       return false;
@@ -197,14 +189,12 @@ bool CheckAbsLoD(const LoD &in, int tensor_height) {
 
     // check: there should be more than 2 offsets existing in each
     // level.
-    if (level.size() < 2)
-      return false;
+    if (level.size() < 2) return false;
 
     // check: the first offset of each level should be 0, and the
     // last should be
     // the same(the height of underlying tensor).
-    if (level.front() != 0)
-      return false;
+    if (level.front() != 0) return false;
     if (tensor_height < 0) {
       tensor_height = level.back();
     } else if ((size_t)tensor_height != level.back()) {

src/framework/lod_tensor.h

@@ -14,12 +14,12 @@ limitations under the License. */
 
 #pragma once
 
-#include "tensor.h"
-#include "tensor_util.h"
 #include <memory>
 #include <string>
 #include <utility>
 #include <vector>
+#include "tensor.h"
+#include "tensor_util.h"
 
 namespace paddle_mobile {
 
@@ -102,7 +102,7 @@ bool CheckAbsLoD(const LoD &in, int tensor_height = -1);
  * see https://en.wikipedia.org/wiki/Level_of_details for reference.
  */
 class LoDTensor : public Tensor {
-public:
+ public:
   LoDTensor() : Tensor() {}
 
   explicit LoDTensor(const LoD &lod) : lod_(lod) {}
@@ -139,7 +139,7 @@ public:
     return (lod_)[level].size() - 1;
   }
 
-private:
+ private:
   LoD lod_;
 };
 
@@ -189,9 +189,8 @@ LoDTensor LodExpand(const LoDTensor &source, const LoD &lod, size_t level) {
 // 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);
+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);
 

src/framework/op_desc.h

@@ -26,7 +26,7 @@ namespace paddle_mobile {
 namespace framework {
 
 class OpDesc : PaddleMobileObject {
-public:
+ 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;
@@ -40,7 +40,7 @@ public:
 
   const std::string &Type() { return desc_.type(); };
 
-private:
+ private:
   proto::OpDesc desc_;
   VariableNameMap inputs_;
   VariableNameMap outputs_;

src/framework/op_info.h

@@ -24,7 +24,8 @@ SOFTWARE.
 namespace paddle_mobile {
 namespace framework {
 
-template <typename Dtype> struct OpInfo {
+template <typename Dtype>
+struct OpInfo {
   OpCreator<Dtype> creator_;
   const OpCreator<Dtype> &Creator() const {
     //    PADDLE_ENFORCE_NOT_NULL(creator_,
@@ -34,12 +35,15 @@ template <typename Dtype> struct OpInfo {
   }
 };
 
-template <typename Dtype> class OpInfoMap;
+template <typename Dtype>
+class OpInfoMap;
 
-template <typename Dtype> static OpInfoMap<Dtype> *g_op_info_map = nullptr;
+template <typename Dtype>
+static OpInfoMap<Dtype> *g_op_info_map = nullptr;
 
-template <typename Dtype> class OpInfoMap {
-public:
+template <typename Dtype>
+class OpInfoMap {
+ public:
   static OpInfoMap &Instance() {
     if (g_op_info_map<Dtype> == nullptr) {
       g_op_info_map<Dtype> = new OpInfoMap();
@@ -83,7 +87,7 @@ public:
     return &map_;
   }
 
-private:
+ private:
   OpInfoMap() = default;
   std::unordered_map<std::string, OpInfo<Dtype>> map_;
 

src/framework/operator.cpp

@@ -28,7 +28,10 @@ OperatorBase<Dtype>::OperatorBase(const std::string &type,
                                   const VariableNameMap &outputs,
                                   const AttributeMap &attrs,
                                   std::shared_ptr<Scope> scope)
-    : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs),
+    : type_(type),
+      inputs_(inputs),
+      outputs_(outputs),
+      attrs_(attrs),
       scope_(scope) {
   CheckAllInputOutputSet();
 }

src/framework/operator.h

@@ -48,8 +48,9 @@ static std::unordered_map<
                            {"feed", {{"X"}, {"Out"}}},
                            {"fetch", {{"X"}, {"Out"}}}};
 
-template <typename Dtype> class OperatorBase : PaddleMobileObject {
-public:
+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);
@@ -66,20 +67,20 @@ public:
     }
   }
 
-protected:
+ protected:
   std::shared_ptr<Scope> scope_;
   std::string type_;
   VariableNameMap inputs_;
   VariableNameMap outputs_;
   AttributeMap attrs_;
 
-private:
+ private:
   void CheckAllInputOutputSet() const;
 };
 
 template <typename Dtype>
 class OperatorWithKernel : public OperatorBase<Dtype> {
-public:
+ public:
   OperatorWithKernel(const std::string &type, const VariableNameMap &inputs,
                      const VariableNameMap &outputs, const AttributeMap &attrs,
                      std::shared_ptr<Scope> scope)
@@ -88,8 +89,9 @@ public:
   virtual void Run() const = 0;
 };
 
-template <typename Dtype, typename P> class OpKernelBase : PaddleMobileObject {
-public:
+template <typename Dtype, typename P>
+class OpKernelBase : PaddleMobileObject {
+ public:
   virtual void Compute(const P &para) const = 0;
 
   virtual ~OpKernelBase() = default;

src/framework/paddle_mobile_object.h

@@ -18,19 +18,19 @@ SOFTWARE.
 
 #pragma once
 
-#include "stdio.h"
 #include <string>
+#include "stdio.h"
 
 namespace paddle_mobile {
 
 class PaddleMobileObject {
-public:
+ public:
   virtual std::string ToString() {
     char address[128] = {0};
     sprintf(address, "%p", this);
     return std::string(address);
   }
 
-private:
+ private:
 };
 }  // namespace paddle_mobile

src/framework/program-optimize/node.h

@@ -29,7 +29,7 @@ namespace paddle_mobile {
 namespace framework {
 
 class Node : PaddleMobileObject {
-public:
+ public:
   Node(const std::string &type) : type_(type) {}
   Node(std::shared_ptr<OpDesc> op_desc)
       : op_desc_(op_desc), type_(op_desc->Type()){};
@@ -39,7 +39,7 @@ public:
   Node &To(int index);
   uint depth(uint begin = 0);
 
-private:
+ private:
   std::shared_ptr<OpDesc> op_desc_;
   std::string ToString(std::string blank, const Node *node) const;
   std::vector<std::shared_ptr<Node>> outputs_;

src/framework/program-optimize/program_optimize.cpp

@@ -24,8 +24,8 @@ namespace framework {
 
 std::shared_ptr<ProgramDesc> ProgramOptimize::Optimize() {}
 
-std::shared_ptr<ProgramDesc>
-ProgramOptimize::FushionOptimize(std::shared_ptr<ProgramDesc> ori_des) {
+std::shared_ptr<ProgramDesc> ProgramOptimize::FushionOptimize(
+    std::shared_ptr<ProgramDesc> ori_des) {
   for (int i = 0; i < ori_des->Blocks().size(); ++i) {
     std::unordered_map<std::string, std::shared_ptr<Node>> output_nodes;
     std::shared_ptr<Node> begin_node;

src/framework/program-optimize/program_optimize.h

@@ -26,13 +26,13 @@ namespace paddle_mobile {
 
 namespace framework {
 class ProgramOptimize {
-public:
+ public:
   ProgramOptimize() {}
   std::shared_ptr<ProgramDesc> Optimize();
-  std::shared_ptr<ProgramDesc>
-  FushionOptimize(std::shared_ptr<ProgramDesc> ori_des);
+  std::shared_ptr<ProgramDesc> FushionOptimize(
+      std::shared_ptr<ProgramDesc> ori_des);
 
-private:
+ private:
   //                std::shared_ptr<ProgramDesc> ori_desc_;
   std::vector<std::unordered_map<std::string, std::shared_ptr<Node>>>
       outputs_nodes_;

src/framework/program.h

@@ -28,12 +28,12 @@ namespace framework {
 
 template <typename Dtype, Precision P = Precision::FP32>
 class Program : PaddleMobileObject {
-public:
+ public:
   std::shared_ptr<ProgramDesc> originProgram;
   std::shared_ptr<ProgramDesc> optimizeProgram;
   std::shared_ptr<Scope> scope;
 
-private:
+ private:
 };
 
 }  // namespace framework

src/framework/program_desc.h

@@ -28,12 +28,12 @@ namespace paddle_mobile {
 namespace framework {
 
 class ProgramDesc : PaddleMobileObject {
-public:
+ 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:
+ private:
   std::vector<std::shared_ptr<BlockDesc>> blocks_;
   proto::ProgramDesc desc_;
 };

src/framework/scope.h

@@ -18,15 +18,15 @@ SOFTWARE.
 ==============================================================================*/
 #pragma once
 
-#include "variable.h"
 #include <list>           //std::list
 #include <mutex>          //std::mutex
 #include <unordered_map>  //std::unordered_map
+#include "variable.h"
 
 namespace paddle_mobile {
 namespace framework {
 class Scope {
-public:
+ public:
   Scope() {}
   ~Scope() {}
 
@@ -67,7 +67,7 @@ public:
 
   Variable *FindVarLocally(const std::string &name) const;
 
-private:
+ private:
   // Call Scope::NewScope for a sub-scope.
   explicit Scope(Scope const *parent) : parent_(parent) {}
 

src/framework/selected_rows.h

@@ -27,7 +27,7 @@ namespace paddle_mobile {
 namespace framework {
 
 class SelectedRows {
-public:
+ public:
   SelectedRows(const std::vector<int64_t> &rows, const int64_t &height)
       : rows_(rows), height_(height) {
     value_.reset(new Tensor());
@@ -67,7 +67,7 @@ public:
     return make_ddim(dims);
   }
 
-private:
+ 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

src/framework/tensor.h

@@ -26,9 +26,11 @@ limitations under the License. */
 
 namespace paddle_mobile {
 namespace framework {
-template <typename... T> struct SizeOfTypeFunctor;
+template <typename... T>
+struct SizeOfTypeFunctor;
 
-template <typename T> struct SizeOfTypeFunctor<T> {
+template <typename T>
+struct SizeOfTypeFunctor<T> {
   size_t operator()(std::type_index type) const {
     if (typeid(T).hash_code() == type.hash_code()) {
       return sizeof(T);
@@ -38,7 +40,8 @@ template <typename T> struct SizeOfTypeFunctor<T> {
   }
 };
 
-template <> struct SizeOfTypeFunctor<> {
+template <>
+struct SizeOfTypeFunctor<> {
   size_t operator()(std::type_index type) const { return 0UL; }
 };
 
@@ -66,11 +69,12 @@ static inline size_t SizeOfType(std::type_index type) {
 class LoDTensor;
 
 class Tensor {
-public:
+ public:
   Tensor() : offset_(0) {}
 
   /*! Return a pointer to mutable memory block. */
-  template <typename T> inline T *data() {
+  template <typename T>
+  inline T *data() {
     check_memory_size();
     //  PADDLE_ENFORCE(std::is_same<T, void>::value ||
     //                     holder_->type().hash_code() ==
@@ -82,7 +86,8 @@ public:
   }
 
   /*! Return a pointer to constant memory block. */
-  template <typename T> inline const T *data() const {
+  template <typename T>
+  inline const T *data() const {
     check_memory_size();
     //  PADDLE_ENFORCE(std::is_same<T, void>::value ||
     //                     holder_->type().hash_code() ==
@@ -100,7 +105,8 @@ public:
    * @brief   Return a pointer to mutable memory block.
    * @note    If not exist, then allocation.
    */
-  template <typename T> inline T *mutable_data() {
+  template <typename T>
+  inline T *mutable_data() {
     static_assert(std::is_pod<T>::value, "T must be POD");
     return reinterpret_cast<T *>(mutable_data(typeid(T)));
   }
@@ -141,7 +147,8 @@ public:
    *
    * @note      If not exist, then allocation.
    */
-  template <typename T> inline T *mutable_data(DDim dims) {
+  template <typename T>
+  inline T *mutable_data(DDim dims) {
     static_assert(std::is_pod<T>::value, "T must be POD");
     Resize(dims);
     return mutable_data<T>();
@@ -235,7 +242,7 @@ public:
 
   inline void set_layout(const DataLayout layout) { layout_ = layout; }
 
-private:
+ private:
   /**
    * @note    Placeholder hides type T, so it doesn't appear as a
    * template
@@ -257,7 +264,8 @@ private:
     PlaceholderImpl(size_t size, std::type_index type)
         : ptr_(static_cast<uint8_t *>(memory::Alloc(size)),
                memory::PODDeleter<uint8_t>()),
-          size_(size), type_(type) {
+          size_(size),
+          type_(type) {
       //                    PADDLE_ENFORCE_NOT_NULL(ptr_,
       //                    "Insufficient %s
       //                    memory to allocation.",

src/framework/tensor_util.cc

@@ -51,7 +51,8 @@ void TensorCopySync(const Tensor &src, Tensor *dst) {
   memory::Copy(dst_ptr, src_ptr, size);
 }
 
-template <typename Predicate> struct AnyDTypeVisitor {
+template <typename Predicate>
+struct AnyDTypeVisitor {
   Predicate predicate_;
   const Tensor &tensor_;
   Tensor *out_;
@@ -59,7 +60,8 @@ template <typename Predicate> struct AnyDTypeVisitor {
   AnyDTypeVisitor(Predicate predicate, const Tensor &tensor, Tensor *out)
       : predicate_(predicate), tensor_(tensor), out_(out) {}
 
-  template <typename T> void operator()() const {
+  template <typename T>
+  void operator()() const {
     //    auto t = EigenVector<T>::Flatten(tensor_);
     //    auto o = EigenScalar<bool>::From(*out_);
     // return any of predicate_(t) is true.
@@ -74,7 +76,8 @@ inline void AnyImpl(Predicate predicate, const Tensor &tensor,
                 AnyDTypeVisitor<Predicate>(predicate, tensor, out));
 }
 
-template <typename Predicate> struct AnyVisitor {
+template <typename Predicate>
+struct AnyVisitor {
   const framework::Tensor &tensor_;
   Predicate predicate_;
 
@@ -164,7 +167,8 @@ struct DeserializedDataFunctor {
   DeserializedDataFunctor(void **buf, Tensor *tensor)
       : buf_(buf), tensor_(tensor) {}
 
-  template <typename T> void operator()() {
+  template <typename T>
+  void operator()() {
     *buf_ = tensor_->mutable_data<T>();
   }
 

src/framework/tensor_util.h

@@ -13,11 +13,11 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #pragma once
+#include <vector>
 #include "framework.pb.h"
 #include "memory/t_malloc.h"
 #include "platform/data_type.h"
 #include "tensor.h"
-#include <vector>
 
 namespace paddle_mobile {
 namespace framework {

src/framework/var_desc.h

@@ -25,7 +25,7 @@ namespace paddle_mobile {
 namespace framework {
 
 class VarDesc {
-public:
+ public:
   VarDesc(const proto::VarDesc &desc);
 
   std::string Name() const { return desc_.name(); }
@@ -80,7 +80,7 @@ public:
     return this->RepeatedToVector(tensor_desc().dims());
   }
 
-private:
+ private:
   proto::VarDesc desc_;
 };
 

src/framework/variable.h

@@ -18,18 +18,19 @@ SOFTWARE.
 ==============================================================================*/
 #pragma once
 
-#include "paddle_mobile_object.h"
 #include <iostream>
 #include <memory>
 #include <string>
 #include <typeindex>
 #include <typeinfo>
+#include "paddle_mobile_object.h"
 
 namespace paddle_mobile {
 namespace framework {
 class Variable : public PaddleMobileObject {
-public:
-  template <typename T> const T *Get() const {
+ public:
+  template <typename T>
+  const T *Get() const {
     return static_cast<const T *>(holder_->Ptr());
   }
 
@@ -37,7 +38,8 @@ public:
 
   const std::string *Name() { return name_; }
 
-  template <typename T> T *GetMutable() {
+  template <typename T>
+  T *GetMutable() {
     if (!IsType<T>()) {
       if (*Name() == "pixel") {
         //        std::cout << " reset " << *Name() <<
@@ -48,7 +50,8 @@ public:
     return static_cast<T *>(holder_->Ptr());
   }
 
-  template <typename T> bool IsType() const {
+  template <typename T>
+  bool IsType() const {
     if (holder_) {
       //                printf("not null \n");
       printf(" holder type : %s, this type %s \n", holder_->Type().name(),
@@ -67,7 +70,7 @@ public:
 
   void SetName(const std::string *name) { name_ = name; }
 
-private:
+ private:
   struct Placeholder {
     Placeholder() = default;
     virtual ~Placeholder() = default;
@@ -76,7 +79,8 @@ private:
     virtual void *Ptr() const = 0;
   };
 
-  template <typename T> struct PlaceholderImp : public Placeholder {
+  template <typename T>
+  struct PlaceholderImp : public Placeholder {
     explicit PlaceholderImp(T *ptr) : ptr_(ptr), type_(typeid(T)) {}
 
     virtual const std::type_info &Type() const { return type_; }

src/io.cpp

@@ -18,13 +18,13 @@ SOFTWARE.
 
 #include <fstream>
 
+#include "../src/io.h"
 #include "common/log.h"
 #include "framework/framework.pb.h"
 #include "framework/lod_tensor.h"
 #include "framework/program_desc.h"
 #include "framework/scope.h"
 #include "framework/tensor.h"
-#include "io.h"
 
 namespace paddle_mobile {
 
@@ -41,26 +41,20 @@ void ReadBinaryFile(const std::string &filename, std::string *contents) {
 template <typename Dtype, Precision P>
 void Loader<Dtype, P>::LoadVar(framework::LoDTensor *tensor,
                                const std::string &file_path) {
-  //        LOG(kLOG_DEBUG) << "  to load " << file_path;
-  //  Log(kLOG_DEBUG) << "123";
-
   std::ifstream is(file_path);
 
-  std::streampos pos = is.tellg(); //   save   current   position
+  std::fpos<mbstate_t> pos;
+  pos = is.tellg();  // save   current   position
   is.seekg(0, std::ios::end);
-  //        LOG(kLOG_DEBUG) << "  file length = " << is.tellg();
   is.seekg(pos);  // restore   saved   position
 
   // 1. version
   uint32_t version;
   is.read(reinterpret_cast<char *>(&version), sizeof(version));
-  //        LOG(kLOG_INFO) << "   version: " << version;
 
   // 2 Lod information
   uint64_t lod_level;
   is.read(reinterpret_cast<char *>(&lod_level), sizeof(lod_level));
-  //        LOG(kLOG_DEBUG) << "   load level: " << lod_level;
-  //        LOG(kLOG_DEBUG) << "   lod info: ";
   auto &lod = *tensor->mutable_lod();
   lod.resize(lod_level);
   for (uint64_t i = 0; i < lod_level; ++i) {
@@ -69,8 +63,8 @@ void Loader<Dtype, P>::LoadVar(framework::LoDTensor *tensor,
     std::vector<size_t> tmp(size / sizeof(size_t));
     is.read(reinterpret_cast<char *>(tmp.data()),
             static_cast<std::streamsize>(size));
-    for (int j = 0; j < tmp.size(); ++j) {
-      LOG(kLOG_DEBUG1) << "    lod - " << tmp[j];
+    for (auto j : tmp) {
+      LOG(kLOG_DEBUG1) << "    lod - " << j;
     }
     lod[i] = tmp;
   }
@@ -78,26 +72,19 @@ void Loader<Dtype, P>::LoadVar(framework::LoDTensor *tensor,
   // 3. tensor version
   uint32_t tensor_version;
   is.read(reinterpret_cast<char *>(&tensor_version), sizeof(tensor_version));
-  //  std::cout << "   tensor_version: " << tensor_version << std::endl;
 
   // 4. tensor desc
   int32_t size;
   is.read(reinterpret_cast<char *>(&size), sizeof(size));
-  //  std::cout << "   tensor desc size: " << size << std::endl;
   std::unique_ptr<char[]> buf(new char[size]);
   is.read(reinterpret_cast<char *>(buf.get()), size);
 
   framework::proto::VarType::TensorDesc desc;
   desc.ParseFromArray(buf.get(), size);
 
-  //  std::cout << "   desc dims size " << desc.dims().size() <<
-  //  std::endl;
   int memory_size = 1;
-  for (int l = 0; l < desc.dims().size(); ++l) {
-    //    std::cout << "    dim " << l << " value: " << desc.dims()[l]
-    //    <<
-    //    std::endl;
-    memory_size *= desc.dims()[l];
+  for (auto l : desc.dims()) {
+    memory_size *= l;
   }
 
   std::vector<int64_t> dims;
@@ -105,50 +92,39 @@ void Loader<Dtype, P>::LoadVar(framework::LoDTensor *tensor,
   std::copy(desc.dims().begin(), desc.dims().end(), std::back_inserter(dims));
   tensor->Resize(framework::make_ddim(dims));
 
-  void *memory;
+  void *memory = tensor;
   int type_size = 0;
-  //  std::cout << "    desc pre type: ";
   switch (desc.data_type()) {
     case framework::proto::VarType::FP16:
-    //      std::cout << "FP16" << std::endl;
       type_size = 2;
       break;
     case framework::proto::VarType::FP32:
       type_size = 4;
       memory = tensor->mutable_data<float>();
-    //      std::cout << "FP32" << std::endl;
       break;
     case framework::proto::VarType::FP64:
       type_size = 8;
-    //      std::cout << "FP64" << std::endl;
       break;
     case framework::proto::VarType::INT32:
       type_size = 4;
-    //      std::cout << "INT32" << std::endl;
       break;
     case framework::proto::VarType::INT64:
       type_size = 8;
-    //      std::cout << "INT64" << std::endl;
       break;
     case framework::proto::VarType::BOOL:
       type_size = 1;
-    //      std::cout << "BOOL" << std::endl;
       break;
     default:
       break;
-    //      std::cout << "    not support" << std::endl;
   }
 
-  //  std::cout << "    malloc size: " << memory_size * type_size <<
-  //  std::endl;
   is.read(static_cast<char *>(memory), memory_size * type_size);
-  //  std::cout << "    memory: " << memory << std::endl;
   is.close();
-};
+}
 
 template <typename Dtype, Precision P>
-const framework::Program<Dtype, P>
-Loader<Dtype, P>::Load(const std::string &dirname) {
+const framework::Program<Dtype, P> Loader<Dtype, P>::Load(
+    const std::string &dirname) {
   std::string model_filename = dirname + "/__model__";
   std::string program_desc_str;
   ReadBinaryFile(model_filename, &program_desc_str);
@@ -165,10 +141,9 @@ Loader<Dtype, P>::Load(const std::string &dirname) {
       std::make_shared<framework::Scope>();
   program.scope = scope;
 
-  auto block = originProgramDesc->Block(0);
+  originProgramDesc->Block(0);
 
-  for (auto block : originProgramDesc->Blocks()) {
-    //    std::cout << "for block" << std::endl;
+  for (const auto &block : originProgramDesc->Blocks()) {
     for (int i = 0; i < block->Vars().size(); ++i) {
       std::shared_ptr<framework::VarDesc> var_desc = block->Vars()[i];
       auto var = scope->Var(var_desc->Name());
@@ -176,20 +151,18 @@ Loader<Dtype, P>::Load(const std::string &dirname) {
         if (var_desc->Persistable() &&
             var_desc->GetType() != framework::proto::VarType::FEED_MINIBATCH &&
             var_desc->GetType() != framework::proto::VarType::FETCH_LIST) {
-          framework::LoDTensor *tensor =
-              var->GetMutable<framework::LoDTensor>();
+          auto tensor = var->GetMutable<framework::LoDTensor>();
           // to load
           LoadVar(tensor, dirname + "/" + var_desc->Name());
         }
       } else {
-        //        std::cout << "非 lod" << std::endl;
+        //  TODO by someone
       }
     }
   }
 
 #ifdef PADDLE_MOBILE_DEBUG
-  for (int i = 0; i < program_desc_proto.blocks().size(); ++i) {
-    framework::proto::BlockDesc block = program_desc_proto.blocks()[i];
+  for (const auto &block : program_desc_proto.blocks()) {
     LOG(kLOG_DEBUG) << "block: " << block.idx();
     for (int j = 0; j < block.ops().size(); ++j) {
       if (j == 2) {
@@ -200,21 +173,20 @@ Loader<Dtype, P>::Load(const std::string &dirname) {
       for (int m = 0; m < op.inputs_size(); ++m) {
         const framework::proto::OpDesc::Var &var = op.inputs(m);
         LOG(kLOG_DEBUG2) << "input parameter: " << var.parameter();
-        for (int n = 0; n < var.arguments().size(); ++n) {
-          LOG(kLOG_DEBUG3) << "argument - " << var.arguments()[n];
+        for (const auto &n : var.arguments()) {
+          LOG(kLOG_DEBUG3) << "argument - " << n;
         }
       }
 
       for (int y = 0; y < op.outputs_size(); ++y) {
         const framework::proto::OpDesc::Var &var = op.outputs(y);
         LOG(kLOG_DEBUG2) << "out parameter: " << var.parameter();
-        for (int z = 0; z < var.arguments().size(); ++z) {
-          LOG(kLOG_DEBUG3) << "argument - " << var.arguments()[z];
+        for (const auto &z : var.arguments()) {
+          LOG(kLOG_DEBUG3) << "argument - " << z;
         }
       }
 
-      for (int x = 0; x < op.attrs().size(); ++x) {
-        const framework::proto::OpDesc_Attr attr = op.attrs()[x];
+      for (const auto &attr : op.attrs()) {
         LOG(kLOG_DEBUG2) << "attr name: " << attr.name();
 
         switch (attr.type()) {
@@ -246,19 +218,19 @@ Loader<Dtype, P>::Load(const std::string &dirname) {
             for (int y = 0; y < attr.strings_size(); ++y) {
               LOG(kLOG_DEBUG3) << "strings: " << attr.strings(y);
             }
+          case framework::proto::BLOCK:
+            break;
         }
       }
     }
 
-    for (int k = 0; k < block.vars().size(); ++k) {
-      framework::proto::VarDesc var = block.vars()[k];
+    for (const auto &var : block.vars()) {
       if (var.type().type() == framework::proto::VarType::LOD_TENSOR) {
         LOG(kLOG_DEBUG1) << "var name: " << var.name();
         const framework::proto::VarType::TensorDesc &tensor_desc =
             var.type().lod_tensor().tensor();
         LOG(kLOG_DEBUG2) << "in var tensor desc dims size: "
                          << tensor_desc.dims().size();
-        int memory_size = 1;
         for (int l = 0; l < tensor_desc.dims().size(); ++l) {
           LOG(kLOG_DEBUG3) << "var tensor desc dim " << l
                            << " value: " << tensor_desc.dims()[l];
@@ -268,28 +240,20 @@ Loader<Dtype, P>::Load(const std::string &dirname) {
       if (var.persistable() &&
           var.type().type() != framework::proto::VarType::FEED_MINIBATCH &&
           var.type().type() != framework::proto::VarType::FETCH_LIST) {
-        //        std::cout << "  to load " << var.name() <<
-        //        std::endl;
         std::string file_path = dirname + "/" + var.name();
         std::ifstream is(file_path);
-        std::streampos pos = is.tellg(); //   save   current   position
+        std::fpos<mbstate_t> pos;
+        pos = is.tellg();  // save   current   position
         is.seekg(0, std::ios::end);
-        //        std::cout << "  file length = " << is.tellg() <<
-        //        std::endl;
         is.seekg(pos);  // restore   saved   position
 
         // 1. version
         uint32_t version;
         is.read(reinterpret_cast<char *>(&version), sizeof(version));
-        //        std::cout << "   version: " << version <<
-        //        std::endl;
 
         // 2 Lod information
         uint64_t lod_level;
         is.read(reinterpret_cast<char *>(&lod_level), sizeof(lod_level));
-        //        std::cout << "   load level: " << lod_level <<
-        //        std::endl;
-        //        std::cout << "   lod info: " << std::endl;
         for (uint64_t i = 0; i < lod_level; ++i) {
           uint64_t size;
           is.read(reinterpret_cast<char *>(&size), sizeof(size));
@@ -297,83 +261,53 @@ Loader<Dtype, P>::Load(const std::string &dirname) {
           is.read(reinterpret_cast<char *>(tmp.data()),
                   static_cast<std::streamsize>(size));
           for (int j = 0; j < tmp.size(); ++j) {
-            //            std::cout << "    lod - " << tmp[j] <<
-            //            std::endl;
           }
         }
 
-        uint32_t tensor_version;
         is.read(reinterpret_cast<char *>(&version), sizeof(version));
-        //        std::cout << "   tensor_version: " <<
-        //        tensor_version <<
-        //        std::endl;
 
         int32_t size;
         is.read(reinterpret_cast<char *>(&size), sizeof(size));
-        //        std::cout << "   tensor desc size: " << size <<
-        //        std::endl;
         std::unique_ptr<char[]> buf(new char[size]);
         is.read(reinterpret_cast<char *>(buf.get()), size);
 
         framework::proto::VarType::TensorDesc desc;
         desc.ParseFromArray(buf.get(), size);
 
-        //        std::cout << "   desc dims size " <<
-        //        desc.dims().size() <<
-        //        std::endl;
         int memory_size = 1;
-        for (int l = 0; l < desc.dims().size(); ++l) {
-          //          std::cout << "    dim " << l << " value: "
-          //          <<
-          //          desc.dims()[l]
-          //                    << std::endl;
-          memory_size *= desc.dims()[l];
+        for (long long l : desc.dims()) {
+          memory_size *= l;
         }
 
         int type_size = 0;
-        //        std::cout << "    desc pre type: ";
         switch (desc.data_type()) {
           case framework::proto::VarType::FP16:
-          //            std::cout << "FP16" << std::endl;
             type_size = 2;
             break;
           case framework::proto::VarType::FP32:
             type_size = 4;
-          //            std::cout << "FP32" << std::endl;
             break;
           case framework::proto::VarType::FP64:
             type_size = 8;
-          //            std::cout << "FP64" << std::endl;
             break;
           case framework::proto::VarType::INT32:
             type_size = 4;
-          //            std::cout << "INT32" << std::endl;
             break;
           case framework::proto::VarType::INT64:
             type_size = 8;
-          //            std::cout << "INT64" << std::endl;
             break;
           case framework::proto::VarType::BOOL:
             type_size = 1;
-          //            std::cout << "BOOL" << std::endl;
             break;
           default:
             break;
-          //            std::cout << "    not support" <<
-          //            std::endl;
         }
 
-        //        std::cout << "    malloc size: " << memory_size *
-        //        type_size
-        //                  << std::endl;
         void *memory = malloc(memory_size * type_size);
         is.read(static_cast<char *>(memory), memory_size * type_size);
-        //        std::cout << "    memory: " << memory <<
-        //        std::endl;
         is.close();
       } else {
-        //        std::cout << "  *not load "
-        //                  << " var : " << var.name() << std::endl;
+        //  TODO
       }
     }
   }

src/io.h

@@ -29,10 +29,10 @@ namespace paddle_mobile {
 
 template <typename Dtype, Precision P = Precision::FP32>
 class Loader : PaddleMobileObject {
-public:
+ public:
   const framework::Program<Dtype, P> Load(const std::string &dirname);
 
-private:
+ private:
   void LoadVar(framework::LoDTensor *tensor, const std::string &file_path);
 };
 

src/memory/t_malloc.h

@@ -37,10 +37,11 @@ void Free(void *ptr);
  *          std::unique_ptr<T> in tensor.h.
  *          static_cast
  */
-template <typename T> class PODDeleter {
+template <typename T>
+class PODDeleter {
   static_assert(std::is_pod<T>::value, "T must be POD");
 
-public:
+ public:
   explicit PODDeleter(){};
 
   void operator()(T *ptr) { Free(static_cast<void *>(ptr)); }
@@ -54,8 +55,9 @@ public:
  *          std::unique_ptr<T> in tensor.h.
  *          reinterpret_cast
  */
-template <typename T> class PlainDeleter {
-public:
+template <typename T>
+class PlainDeleter {
+ public:
   explicit PlainDeleter(){};
 
   void operator()(T *ptr) { Free(reinterpret_cast<void *>(ptr)); }

src/operators/batchnorm_op.h

@@ -27,7 +27,7 @@ using namespace framework;
 
 template <typename DeviceType, typename T>
 class BatchNormOp : public framework::OperatorWithKernel<DeviceType> {
-public:
+ public:
   BatchNormOp(const std::string &type, const VariableNameMap &inputs,
               const VariableNameMap &outputs,
               const framework::AttributeMap attrs,
@@ -44,7 +44,7 @@ public:
   using framework::OperatorWithKernel<DeviceType>::OperatorWithKernel;
   void InferShape() const override;
 
-protected:
+ protected:
   BatchNormParam param_;
 };
 

src/operators/concat_op.h

@@ -26,7 +26,7 @@ using namespace framework;
 
 template <typename DeviceType, typename T>
 class ConcatOp : public framework::OperatorWithKernel<DeviceType> {
-public:
+ public:
   ConcatOp(const std::string &type, const VariableNameMap &inputs,
            const VariableNameMap &outputs, const framework::AttributeMap attrs,
            std::shared_ptr<framework::Scope> scope)
@@ -42,7 +42,7 @@ public:
   using framework::OperatorWithKernel<DeviceType>::OperatorWithKernel;
   void InferShape() const override;
 
-protected:
+ protected:
   ConcatParam param_;
 };
 

src/operators/conv_op.h

@@ -28,7 +28,7 @@ using namespace framework;
 
 template <typename DeviceType, typename T>
 class ConvOp : public framework::OperatorWithKernel<DeviceType> {
-public:
+ public:
   ConvOp(const std::string &type, const VariableNameMap &inputs,
          const VariableNameMap &outputs, const framework::AttributeMap &attrs,
          std::shared_ptr<framework::Scope> scope)
@@ -45,7 +45,7 @@ public:
     this->ClearVariables({"Filter", "Input"});
   }
 
-private:
+ private:
   ConvParam param_;
 };
 

src/operators/elementwise_add_op.h

@@ -27,7 +27,7 @@ using namespace framework;
 
 template <typename DeviceType, typename T>
 class ElementwiseAddOp : public framework::OperatorWithKernel<DeviceType> {
-public:
+ public:
   ElementwiseAddOp(const std::string &type, const VariableNameMap &inputs,
                    const VariableNameMap &outputs,
                    const framework::AttributeMap attrs,
@@ -44,7 +44,7 @@ public:
   using framework::OperatorWithKernel<DeviceType>::OperatorWithKernel;
   void InferShape() const override;
 
-protected:
+ protected:
   ElementwiseAddParam param_;
 };
 }  // namespace operators

src/operators/kernel/arm/concat_kernel.cpp

@@ -18,8 +18,9 @@ limitations under the License. */
 
 namespace paddle_mobile {
 namespace operators {
-template <typename T> class ConcatFunctor {
-public:
+template <typename T>
+class ConcatFunctor {
+ public:
   void operator()(const std::vector<framework::Tensor> &input, const int axis,
                   framework::Tensor *output) {
     size_t num = input.size();

src/operators/kernel/arm/conv_kernel.cpp

@@ -34,7 +34,8 @@ bool IsExpand(const std::vector<int64_t> &filter_dim,
   return !(filter_1 && strides_1 && padding_0 && dilation_1);
 }
 
-template <> void ConvKernel<CPU, float>::Compute(const ConvParam &param) const {
+template <>
+void ConvKernel<CPU, float>::Compute(const ConvParam &param) const {
   LOG(kLOG_DEBUG) << param;
 
   const Tensor *input = param.Input();

src/operators/kernel/arm/elementwise_add_kernel.cpp

@@ -19,7 +19,8 @@ limitations under the License. */
 namespace paddle_mobile {
 namespace operators {
 
-template <typename T> struct AddFunctor {
+template <typename T>
+struct AddFunctor {
   inline T operator()(T a, T b) const { return a + b; }
 };
 

src/operators/kernel/arm/lrn_kernel.cpp

@@ -23,7 +23,8 @@ SOFTWARE.
 namespace paddle_mobile {
 namespace operators {
 
-template <> void LrnKernel<CPU, float>::Compute(const LrnParam &param) const {
+template <>
+void LrnKernel<CPU, float>::Compute(const LrnParam &param) const {
   const Tensor *input_x = param.InputX();
   auto x_dims = input_x->dims();
   /// data_format = NCHW

src/operators/kernel/arm/mul_kernel.cpp

@@ -23,7 +23,8 @@ SOFTWARE.
 namespace paddle_mobile {
 namespace operators {
 
-template <> void MulKernel<CPU, float>::Compute(const MulParam &param) const {
+template <>
+void MulKernel<CPU, float>::Compute(const MulParam &param) const {
   const Tensor *input_x = param.InputX();
   const Tensor *input_y = param.InputY();
   Tensor *out = param.Out();

src/operators/kernel/batchnorm_kernel.h

@@ -28,7 +28,7 @@ using namespace framework;
 template <typename DeviceType, typename T>
 class BatchNormKernel
     : public framework::OpKernelBase<DeviceType, BatchNormParam> {
-public:
+ public:
   void Compute(const BatchNormParam &param) const;
 };