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提交 1ad8f821 编写于 作者: 朔-望's avatar 朔-望
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modify to 2 spaces indent & format code & rm build folder

上级 e35ef6fe
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Showing with 13543 addition and 14086 deletion
.clang-format
浏览文件 @ 1ad8f821
...@@ -2,5 +2,4 @@ ...@@ -2,5 +2,4 @@
Language: Cpp Language: Cpp
BasedOnStyle: LLVM BasedOnStyle: LLVM
Standard: Cpp11 Standard: Cpp11
IndentWidth: 4
... ...
cmake-build-release/compile_commands.json 已删除 100644 → 0
浏览文件 @ e35ef6fe
此差异已折叠。
src/common/log.h
浏览文件 @ 1ad8f821
...@@ -28,15 +28,15 @@ SOFTWARE. ...@@ -28,15 +28,15 @@ SOFTWARE.
namespace paddle_mobile { namespace paddle_mobile {
enum LogLevel { enum LogLevel {
kNO_LOG, kNO_LOG,
kLOG_ERROR, kLOG_ERROR,
kLOG_WARNING, kLOG_WARNING,
kLOG_INFO, kLOG_INFO,
kLOG_DEBUG, kLOG_DEBUG,
kLOG_DEBUG1, kLOG_DEBUG1,
kLOG_DEBUG2, kLOG_DEBUG2,
kLOG_DEBUG3, kLOG_DEBUG3,
kLOG_DEBUG4 kLOG_DEBUG4
}; };
// log level // log level
...@@ -49,119 +49,117 @@ struct ToLog; ...@@ -49,119 +49,117 @@ struct ToLog;
struct Print; struct Print;
struct Print { struct Print {
friend struct ToLog; friend struct ToLog;
template <typename T> Print &operator<<(T const &value) { template <typename T> Print &operator<<(T const &value) {
buffer_ << value; buffer_ << value;
return *this; return *this;
} }
private: private:
void print(LogLevel level) { void print(LogLevel level) {
buffer_ << std::endl; buffer_ << std::endl;
if (level == kLOG_ERROR) { if (level == kLOG_ERROR) {
std::cerr << buffer_.str(); std::cerr << buffer_.str();
} else { } else {
std::cout << buffer_.str(); std::cout << buffer_.str();
}
} }
std::ostringstream buffer_; }
std::ostringstream buffer_;
}; };
struct ToLog { struct ToLog {
ToLog(LogLevel level = kLOG_DEBUG, const std::string &info = "") ToLog(LogLevel level = kLOG_DEBUG, const std::string &info = "")
: level_(level) { : level_(level) {
unsigned blanks = unsigned blanks =
(unsigned)(level > kLOG_DEBUG ? (level - kLOG_DEBUG) * 4 : 1); (unsigned)(level > kLOG_DEBUG ? (level - kLOG_DEBUG) * 4 : 1);
printer_ << logs[level] << " " << info << ":" printer_ << logs[level] << " " << info << ":" << std::string(blanks, ' ');
<< std::string(blanks, ' '); }
}
template <typename T> ToLog &operator<<(T const &value) {
template <typename T> ToLog &operator<<(T const &value) { printer_ << value;
printer_ << value; return *this;
return *this; }
}
~ToLog() { printer_.print(level_); }
~ToLog() { printer_.print(level_); }
private:
private: LogLevel level_;
LogLevel level_; Print printer_;
Print printer_;
}; };
#define LOG(level) \ #define LOG(level) \
if (level > paddle_mobile::log_level) { \ if (level > paddle_mobile::log_level) { \
} else \ } else \
paddle_mobile::ToLog( \ paddle_mobile::ToLog( \
level, (std::stringstream() \ level, \
<< "[file: " \ (std::stringstream() \
<< (strrchr(__FILE__, '/') ? (strrchr(__FILE__, '/') + 1) \ << "[file: " \
: __FILE__) \ << (strrchr(__FILE__, '/') ? (strrchr(__FILE__, '/') + 1) : __FILE__) \
<< "] [line: " << __LINE__ << "] ") \ << "] [line: " << __LINE__ << "] ") \
.str()) .str())
#define DLOG \ #define DLOG \
if (paddle_mobile::kLOG_DEBUG > paddle_mobile::log_level) { \ if (paddle_mobile::kLOG_DEBUG > paddle_mobile::log_level) { \
} else \ } else \
paddle_mobile::ToLog( \ paddle_mobile::ToLog( \
paddle_mobile::kLOG_DEBUG, \ paddle_mobile::kLOG_DEBUG, \
(std::stringstream() \ (std::stringstream() \
<< "[file: " \ << "[file: " \
<< (strrchr(__FILE__, '/') ? (strrchr(__FILE__, '/') + 1) \ << (strrchr(__FILE__, '/') ? (strrchr(__FILE__, '/') + 1) : __FILE__) \
: __FILE__) \ << "] [line: " << __LINE__ << "] ") \
<< "] [line: " << __LINE__ << "] ") \ .str())
.str())
} // namespace paddle_mobile } // namespace paddle_mobile
#define LOGF(level, format, ...) \ #define LOGF(level, format, ...) \
if (level > paddle_mobile::log_level) { \ if (level > paddle_mobile::log_level) { \
} else \ } else \
printf(format, ##__VA_ARGS__) printf(format, ##__VA_ARGS__)
#define DLOGF(format, ...) \ #define DLOGF(format, ...) \
if (paddle_mobile::kLOG_DEBUG > paddle_mobile::log_level) { \ if (paddle_mobile::kLOG_DEBUG > paddle_mobile::log_level) { \
} else \ } else \
printf(format, ##__VA_ARGS__) printf(format, ##__VA_ARGS__)
#else #else
namespace paddle_mobile { namespace paddle_mobile {
enum LogLevel { enum LogLevel {
kNO_LOG, kNO_LOG,
kLOG_ERROR, kLOG_ERROR,
kLOG_WARNING, kLOG_WARNING,
kLOG_INFO, kLOG_INFO,
kLOG_DEBUG, kLOG_DEBUG,
kLOG_DEBUG1, kLOG_DEBUG1,
kLOG_DEBUG2, kLOG_DEBUG2,
kLOG_DEBUG3, kLOG_DEBUG3,
kLOG_DEBUG4 kLOG_DEBUG4
}; };
struct ToLog; struct ToLog;
struct Print { struct Print {
friend struct ToLog; friend struct ToLog;
template <typename T> Print &operator<<(T const &value) {} template <typename T> Print &operator<<(T const &value) {}
private: private:
}; };
struct ToLog { struct ToLog {
ToLog(LogLevel level) {} 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) \ #define LOG(level) \
if (true) { \ if (true) { \
} else \ } else \
paddle_mobile::ToLog(level) paddle_mobile::ToLog(level)
#define DLOG \ #define DLOG \
if (true) { \ if (true) { \
} else \ } else \
paddle_mobile::ToLog(paddle_mobile::kLOG_DEBUG) paddle_mobile::ToLog(paddle_mobile::kLOG_DEBUG)
#define LOGF(level, format, ...) #define LOGF(level, format, ...)
......
src/common/types.h
浏览文件 @ 1ad8f821
...@@ -32,32 +32,32 @@ typedef DeviceType<kGPU_MALI> GPU_MALI; ...@@ -32,32 +32,32 @@ typedef DeviceType<kGPU_MALI> GPU_MALI;
//! data type //! data type
enum DataType { enum DataType {
PM_INVALID = -1, PM_INVALID = -1,
PM_HALF = 0, PM_HALF = 0,
PM_FLOAT = 1, PM_FLOAT = 1,
PM_DOUBLE = 2, PM_DOUBLE = 2,
PM_INT8 = 3, PM_INT8 = 3,
PM_INT16 = 4, PM_INT16 = 4,
PM_INT32 = 5, PM_INT32 = 5,
PM_INT64 = 6, PM_INT64 = 6,
PM_UINT8 = 7, PM_UINT8 = 7,
PM_UINT16 = 8, PM_UINT16 = 8,
PM_UINT32 = 9, PM_UINT32 = 9,
PM_STRING = 10, PM_STRING = 10,
PM_BOOL = 11, PM_BOOL = 11,
PM_SHAPE = 12, PM_SHAPE = 12,
PM_TENSOR = 13 PM_TENSOR = 13
}; };
//! //!
enum PMStatus { enum PMStatus {
PMSuccess = 0xFF, /*!< No errors */ PMSuccess = 0xFF, /*!< No errors */
PMNotInitialized = 0x01, /*!< Data not initialized. */ PMNotInitialized = 0x01, /*!< Data not initialized. */
PMInvalidValue = 0x02, /*!< Incorrect variable value. */ PMInvalidValue = 0x02, /*!< Incorrect variable value. */
PMMemAllocFailed = 0x03, /*!< Memory allocation error. */ PMMemAllocFailed = 0x03, /*!< Memory allocation error. */
PMUnKownError = 0x04, /*!< Unknown error. */ PMUnKownError = 0x04, /*!< Unknown error. */
PMOutOfAuthority = 0x05, /*!< Try to modified data not your own*/ PMOutOfAuthority = 0x05, /*!< Try to modified data not your own*/
PMOutOfMem = 0x06, /*!< OOM error*/ PMOutOfMem = 0x06, /*!< OOM error*/
PMUnImplError = 0x07, /*!< Unimplement error. */ PMUnImplError = 0x07, /*!< Unimplement error. */
PMWrongDevice = 0x08 /*!< un-correct device. */ PMWrongDevice = 0x08 /*!< un-correct device. */
}; };
} // namespace paddle_mobile } // namespace paddle_mobile
src/common/variant.h
浏览文件 @ 1ad8f821
...@@ -24,74 +24,74 @@ namespace paddle_mobile { ...@@ -24,74 +24,74 @@ 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 static const size_t size = sizeof(F) > VariantHelper<Ts...>::size
? sizeof(F) ? sizeof(F)
: VariantHelper<Ts...>::size; : VariantHelper<Ts...>::size;
inline static void Destroy(size_t id, void *data) { inline static void Destroy(size_t id, void *data) {
if (id == typeid(F).hash_code()) { if (id == typeid(F).hash_code()) {
reinterpret_cast<F *>(data)->~F(); reinterpret_cast<F *>(data)->~F();
} else { } else {
VariantHelper<Ts...>::Destroy(id, data); VariantHelper<Ts...>::Destroy(id, data);
}
} }
}
}; };
template <typename F> struct VariantHelper<F> { template <typename F> struct VariantHelper<F> {
static const size_t size = sizeof(F); static const size_t size = sizeof(F);
inline static void Destroy(size_t id, void *data) { inline static void Destroy(size_t id, void *data) {
if (id == typeid(F).hash_code()) { if (id == typeid(F).hash_code()) {
// reinterpret_cast<F*>(data)->~F(); // reinterpret_cast<F*>(data)->~F();
} else { } else {
// std::cout << "未匹配到 " << std::endl; // std::cout << "未匹配到 " << std::endl;
}
} }
}
}; };
template <size_t size> class RawData { template <size_t size> class RawData {
public: public:
char data[size]; char data[size];
RawData() {} RawData() {}
RawData(const RawData &raw_data) { strcpy(data, raw_data.data); } RawData(const RawData &raw_data) { strcpy(data, raw_data.data); }
// void operator=(const RawData &raw_data){ // void operator=(const RawData &raw_data){
// strcpy(data, raw_data.data); // strcpy(data, raw_data.data);
// } // }
}; };
template <typename... Ts> struct Variant { template <typename... Ts> struct Variant {
Variant(const Variant &variant) { Variant(const Variant &variant) {
// std::cout << " 赋值构造函数 " << std::endl; // std::cout << " 赋值构造函数 " << std::endl;
type_id = variant.type_id; type_id = variant.type_id;
data = variant.data; data = variant.data;
} }
Variant() : type_id(invalid_type()) {} Variant() : type_id(invalid_type()) {}
~Variant() { ~Variant() {
// helper::Destroy(type_id, &data); // 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); helper::Destroy(type_id, &data);
new (&data) T(std::forward<Args>(args)...); new (&data) T(std::forward<Args>(args)...);
type_id = typeid(T).hash_code(); 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()) { if (type_id == typeid(T).hash_code()) {
return *const_cast<T *>(reinterpret_cast<const T *>(&data)); return *const_cast<T *>(reinterpret_cast<const T *>(&data));
} else { } else {
// std::cout << " bad cast in variant " << std::endl; // std::cout << " bad cast in variant " << std::endl;
throw std::bad_cast(); throw std::bad_cast();
}
} }
}
size_t TypeId() const { return type_id; } size_t TypeId() const { return type_id; }
private: private:
static inline size_t invalid_type() { return typeid(void).hash_code(); } static inline size_t invalid_type() { return typeid(void).hash_code(); }
typedef VariantHelper<Ts...> helper; typedef VariantHelper<Ts...> helper;
size_t type_id; size_t type_id;
RawData<helper::size> data; RawData<helper::size> data;
}; };
template <typename T> struct Vistor { typedef T type_t; }; template <typename T> struct Vistor { typedef T type_t; };
......
src/framework/attribute.h
浏览文件 @ 1ad8f821
...@@ -27,102 +27,102 @@ namespace framework { ...@@ -27,102 +27,102 @@ namespace framework {
class BlockDesc; class BlockDesc;
class Attribute { class Attribute {
public: public:
static Attribute GetAttrValue(const proto::OpDesc::Attr &attr_desc) { static Attribute GetAttrValue(const proto::OpDesc::Attr &attr_desc) {
// std::cout << "begin get attr value" << std::endl; // std::cout << "begin get attr value" << std::endl;
Attribute attr; Attribute attr;
switch (attr_desc.type()) { switch (attr_desc.type()) {
case proto::AttrType::BOOLEAN: { case proto::AttrType::BOOLEAN: {
attr.Set<bool>(attr_desc.b()); attr.Set<bool>(attr_desc.b());
break; 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;
} }
case proto::AttrType::INT: {
Attribute() {} attr.Set<int>(attr_desc.i());
template <typename T, typename... Args> Attribute &Set(Args &&... args) { break;
variant_.Set<T>(args...); }
return *this; 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;
}
template <typename T> T &Get() const { return variant_.Get<T>(); } Attribute() {}
template <typename T, typename... Args> Attribute &Set(Args &&... args) {
variant_.Set<T>(args...);
return *this;
}
private: template <typename T> T &Get() const { return variant_.Get<T>(); }
Variant<int, float, std::string, std::vector<int>, std::vector<float>,
std::vector<std::string>, bool, std::vector<bool>, BlockDesc *, private:
int64_t> Variant<int, float, std::string, std::vector<int>, std::vector<float>,
variant_; 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 { class AttrReader {
public: public:
explicit AttrReader(const AttributeMap &attrs) : attrs_(attrs) {} 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 // PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should
// be in // be in
// AttributeMap", // AttributeMap",
// name); // name);
return ((Attribute)attrs_.at(name)).Get<T>(); return ((Attribute)attrs_.at(name)).Get<T>();
} }
private: private:
const AttributeMap &attrs_; const AttributeMap &attrs_;
}; };
} // namespace framework } // namespace framework
......
src/framework/block_desc.cpp
浏览文件 @ 1ad8f821
...@@ -22,28 +22,28 @@ namespace paddle_mobile { ...@@ -22,28 +22,28 @@ namespace paddle_mobile {
namespace framework { namespace framework {
std::vector<std::shared_ptr<VarDesc>> BlockDesc::Vars() const { std::vector<std::shared_ptr<VarDesc>> BlockDesc::Vars() const {
std::vector<std::shared_ptr<VarDesc>> res; std::vector<std::shared_ptr<VarDesc>> res;
for (const auto &p : vars_) { for (const auto &p : vars_) {
res.push_back(p.second); res.push_back(p.second);
} }
return res; return res;
} }
std::vector<std::shared_ptr<OpDesc>> BlockDesc::Ops() const { std::vector<std::shared_ptr<OpDesc>> BlockDesc::Ops() const {
std::vector<std::shared_ptr<OpDesc>> res; std::vector<std::shared_ptr<OpDesc>> res;
for (const auto &op : ops_) { for (const auto &op : ops_) {
res.push_back(op); res.push_back(op);
} }
return res; return res;
} }
BlockDesc::BlockDesc(const proto::BlockDesc &desc) : desc_(desc) { BlockDesc::BlockDesc(const proto::BlockDesc &desc) : desc_(desc) {
for (const proto::VarDesc &var_desc : desc_.vars()) { for (const proto::VarDesc &var_desc : desc_.vars()) {
vars_[var_desc.name()].reset(new VarDesc(var_desc)); vars_[var_desc.name()].reset(new VarDesc(var_desc));
} }
for (const proto::OpDesc &op_desc : desc_.ops()) { for (const proto::OpDesc &op_desc : desc_.ops()) {
ops_.emplace_back(new framework::OpDesc(op_desc)); ops_.emplace_back(new framework::OpDesc(op_desc));
} }
} }
} // namespace framework } // namespace framework
......
src/framework/block_desc.h
浏览文件 @ 1ad8f821
...@@ -27,29 +27,28 @@ namespace paddle_mobile { ...@@ -27,29 +27,28 @@ namespace paddle_mobile {
namespace framework { namespace framework {
class BlockDesc : PaddleMobileObject { class BlockDesc : PaddleMobileObject {
public: public:
BlockDesc(const proto::BlockDesc &desc); 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 { bool operator==(const paddle_mobile::framework::BlockDesc &in_block) const {
return this->ID() == in_block.ID() && return this->ID() == in_block.ID() && this->Parent() == in_block.Parent();
this->Parent() == in_block.Parent(); }
}
bool operator<(const paddle_mobile::framework::BlockDesc &in_block) const { bool operator<(const paddle_mobile::framework::BlockDesc &in_block) const {
return this->ID() < in_block.ID() && this->Parent() < in_block.Parent(); return this->ID() < in_block.ID() && this->Parent() < in_block.Parent();
} }
std::vector<std::shared_ptr<VarDesc>> Vars() const; std::vector<std::shared_ptr<VarDesc>> Vars() const;
std::vector<std::shared_ptr<OpDesc>> Ops() const; std::vector<std::shared_ptr<OpDesc>> Ops() const;
private: private:
proto::BlockDesc desc_; proto::BlockDesc desc_;
std::vector<std::shared_ptr<OpDesc>> ops_; std::vector<std::shared_ptr<OpDesc>> ops_;
std::unordered_map<std::string, std::shared_ptr<VarDesc>> vars_; std::unordered_map<std::string, std::shared_ptr<VarDesc>> vars_;
}; };
} // namespace framework } // namespace framework
...@@ -58,13 +57,13 @@ class BlockDesc : PaddleMobileObject { ...@@ -58,13 +57,13 @@ class BlockDesc : PaddleMobileObject {
namespace std { namespace std {
template <> struct hash<paddle_mobile::framework::BlockDesc> { template <> struct hash<paddle_mobile::framework::BlockDesc> {
typedef paddle_mobile::framework::BlockDesc argument_type; typedef paddle_mobile::framework::BlockDesc argument_type;
typedef std::size_t result_type; typedef std::size_t result_type;
result_type operator()(argument_type const &s) const noexcept { result_type operator()(argument_type const &s) const noexcept {
result_type const h1(std::hash<int>{}(s.ID())); result_type const h1(std::hash<int>{}(s.ID()));
result_type const h2(std::hash<int>{}(s.ID())); result_type const h2(std::hash<int>{}(s.ID()));
return h1 ^ (h2 << 1); return h1 ^ (h2 << 1);
} }
}; };
} // namespace std } // namespace std
src/framework/data_layout.h
浏览文件 @ 1ad8f821
...@@ -22,45 +22,45 @@ namespace paddle_mobile { ...@@ -22,45 +22,45 @@ namespace paddle_mobile {
namespace framework { namespace framework {
enum class DataLayout { enum class DataLayout {
kNHWC = 0, kNHWC = 0,
kNCHW = 1, kNCHW = 1,
kAnyLayout = 2, kAnyLayout = 2,
}; };
inline DataLayout StringToDataLayout(const std::string &str) { inline DataLayout StringToDataLayout(const std::string &str) {
std::string s(str); std::string s(str);
for (size_t i = 0; i < s.size(); ++i) { for (size_t i = 0; i < s.size(); ++i) {
s[i] = toupper(s[i]); s[i] = toupper(s[i]);
} }
if (s == "NHWC") { if (s == "NHWC") {
return DataLayout::kNHWC; return DataLayout::kNHWC;
} else if (s == "NCHW") { } else if (s == "NCHW") {
return DataLayout::kNCHW; return DataLayout::kNCHW;
} else if (s == "ANYLAYOUT") { } else if (s == "ANYLAYOUT") {
return DataLayout::kAnyLayout; return DataLayout::kAnyLayout;
} else { } else {
// std::cout << "Unknown storage order string: %s", s; // std::cout << "Unknown storage order string: %s", s;
} }
} }
inline std::string DataLayoutToString(const DataLayout &data_layout) { inline std::string DataLayoutToString(const DataLayout &data_layout) {
switch (data_layout) { switch (data_layout) {
case DataLayout::kNHWC: case DataLayout::kNHWC:
return "NHWC"; return "NHWC";
case DataLayout::kNCHW: case DataLayout::kNCHW:
return "NCHW"; return "NCHW";
case DataLayout::kAnyLayout: case DataLayout::kAnyLayout:
return "ANY_LAYOUT"; return "ANY_LAYOUT";
default: default:
break; break;
// std::cout << "unknown DataLayou %d", data_layout; // std::cout << "unknown DataLayou %d", data_layout;
} }
} }
inline std::ostream &operator<<(std::ostream &out, const DataLayout &l) { inline std::ostream &operator<<(std::ostream &out, const DataLayout &l) {
out << DataLayoutToString(l); out << DataLayoutToString(l);
return out; return out;
} }
} // namespace framework } // namespace framework
......
src/framework/data_transform.cpp
浏览文件 @ 1ad8f821
...@@ -24,68 +24,68 @@ namespace paddle_mobile { ...@@ -24,68 +24,68 @@ namespace paddle_mobile {
namespace framework { namespace framework {
static void PassTensorData(Tensor *from, Tensor *to) { static void PassTensorData(Tensor *from, Tensor *to) {
to->ShareDataWith(*from); to->ShareDataWith(*from);
*from = Tensor(); *from = Tensor();
} }
void DataTransform(const OpKernelType &expected_kernel_type, void DataTransform(const OpKernelType &expected_kernel_type,
const OpKernelType &kernel_type_for_var, const OpKernelType &kernel_type_for_var,
const Tensor &input_tensor, Tensor *output_tensor) { const Tensor &input_tensor, Tensor *output_tensor) {
bool transformed = false; bool transformed = false;
Tensor in; Tensor in;
in.ShareDataWith(input_tensor); in.ShareDataWith(input_tensor);
Tensor out; Tensor out;
// // do layout transform // // do layout transform
// if (NeedTransformLayout(expected_kernel_type.data_layout_, // if (NeedTransformLayout(expected_kernel_type.data_layout_,
// kernel_type_for_var.data_layout_)) { // kernel_type_for_var.data_layout_)) {
// TransDataLayout(kernel_type_for_var, expected_kernel_type, in, // TransDataLayout(kernel_type_for_var, expected_kernel_type, in,
// &out); // &out);
// transformed = true; // transformed = true;
// PassTensorData(&out, &in); // PassTensorData(&out, &in);
// } // }
// //
// // do data type transform // // do data type transform
// if (expected_kernel_type.data_type_ != // if (expected_kernel_type.data_type_ !=
// kernel_type_for_var.data_type_) { // kernel_type_for_var.data_type_) {
// TransDataType(kernel_type_for_var, expected_kernel_type, in, // TransDataType(kernel_type_for_var, expected_kernel_type, in,
// &out); // &out);
// transformed = true; // transformed = true;
// PassTensorData(&out, &in); // PassTensorData(&out, &in);
// } // }
// //
// // do device transform // // do device transform
// if (!platform::is_same_place(kernel_type_for_var.place_, // if (!platform::is_same_place(kernel_type_for_var.place_,
// expected_kernel_type.place_)) { // expected_kernel_type.place_)) {
// TransDataDevice(in, expected_kernel_type.place_, &out); // TransDataDevice(in, expected_kernel_type.place_, &out);
// transformed = true; // transformed = true;
// PassTensorData(&out, &in); // PassTensorData(&out, &in);
// } // }
// //
// PADDLE_ENFORCE(transformed, "No transform is applied, please // PADDLE_ENFORCE(transformed, "No transform is applied, please
// check!"); // check!");
// get output data // get output data
output_tensor->ShareDataWith(in); output_tensor->ShareDataWith(in);
} }
void CopyVariableWithTensor(const Variable &in_var, const Tensor &tensor, void CopyVariableWithTensor(const Variable &in_var, const Tensor &tensor,
Variable &out_var) { Variable &out_var) {
// if (in_var.IsType<LoDTensor>()) { // if (in_var.IsType<LoDTensor>()) {
// auto& in_lod_tensor = in_var.Get<LoDTensor>(); // auto& in_lod_tensor = in_var.Get<LoDTensor>();
// auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>(); // auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>();
// tran_lod_tensor->set_lod(in_lod_tensor.lod()); // tran_lod_tensor->set_lod(in_lod_tensor.lod());
// tran_lod_tensor->set_layout(in_lod_tensor.layout()); // tran_lod_tensor->set_layout(in_lod_tensor.layout());
// tran_lod_tensor->ShareDataWith(tensor); // tran_lod_tensor->ShareDataWith(tensor);
// } else if (in_var.IsType<SelectedRows>()) { // } else if (in_var.IsType<SelectedRows>()) {
// auto& in_selected_rows = in_var.Get<SelectedRows>(); // auto& in_selected_rows = in_var.Get<SelectedRows>();
// auto* trans_selected_rows = // auto* trans_selected_rows =
// out_var.GetMutable<SelectedRows>(); // out_var.GetMutable<SelectedRows>();
// trans_selected_rows->set_height(in_selected_rows.height()); // trans_selected_rows->set_height(in_selected_rows.height());
// trans_selected_rows->set_rows(in_selected_rows.rows()); // trans_selected_rows->set_rows(in_selected_rows.rows());
// trans_selected_rows->mutable_value()->ShareDataWith(tensor); // trans_selected_rows->mutable_value()->ShareDataWith(tensor);
// } else { // } else {
// PADDLE_THROW("unknown var type"); // PADDLE_THROW("unknown var type");
// } // }
} }
} // namespace framework } // namespace framework
......
src/framework/ddim.cc
浏览文件 @ 1ad8f821
...@@ -20,158 +20,156 @@ namespace framework { ...@@ -20,158 +20,156 @@ namespace framework {
/// @cond HIDDEN /// @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)); 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) { void make_ddim(DDim &ddim, const int64_t *dims, int n) {
switch (n) { switch (n) {
case 0: case 0:
ddim = make_dim<0>(dims); ddim = make_dim<0>(dims);
break; break;
case 1: case 1:
ddim = make_dim<1>(dims); ddim = make_dim<1>(dims);
break; break;
case 2: case 2:
ddim = make_dim<2>(dims); ddim = make_dim<2>(dims);
break; break;
case 3: case 3:
ddim = make_dim<3>(dims); ddim = make_dim<3>(dims);
break; break;
case 4: case 4:
ddim = make_dim<4>(dims); ddim = make_dim<4>(dims);
break; break;
case 5: case 5:
ddim = make_dim<5>(dims); ddim = make_dim<5>(dims);
break; break;
case 6: case 6:
ddim = make_dim<6>(dims); ddim = make_dim<6>(dims);
break; break;
case 7: case 7:
ddim = make_dim<7>(dims); ddim = make_dim<7>(dims);
break; break;
case 8: case 8:
ddim = make_dim<8>(dims); ddim = make_dim<8>(dims);
break; break;
case 9: case 9:
ddim = make_dim<9>(dims); ddim = make_dim<9>(dims);
break; break;
default: default:
// std::cout << "Dynamic dimensions must have between [1, // std::cout << "Dynamic dimensions must have between [1,
// 9] // 9]
// dimensions."; // dimensions.";
break; break;
} }
} }
/// @endcond /// @endcond
DDim make_ddim(std::initializer_list<int64_t> dims) { DDim make_ddim(std::initializer_list<int64_t> dims) {
DDim result(make_dim(0)); DDim result(make_dim(0));
make_ddim(result, dims.begin(), dims.size()); make_ddim(result, dims.begin(), dims.size());
return result; return result;
} }
DDim make_ddim(const std::vector<int64_t> &dims) { DDim make_ddim(const std::vector<int64_t> &dims) {
DDim result(make_dim(0)); DDim result(make_dim(0));
make_ddim(result, &dims[0], dims.size()); make_ddim(result, &dims[0], dims.size());
return result; return result;
} }
DDim make_ddim(const std::vector<int> &dims) { DDim make_ddim(const std::vector<int> &dims) {
std::vector<int64_t> res(dims.size()); std::vector<int64_t> res(dims.size());
std::transform(dims.begin(), dims.end(), res.begin(), std::transform(dims.begin(), dims.end(), res.begin(),
[](int d) { return static_cast<int64_t>(d); }); [](int d) { return static_cast<int64_t>(d); });
return make_ddim(res); return make_ddim(res);
} }
/// @cond HIDDEN /// @cond HIDDEN
// XXX For some reason, putting this in an anonymous namespace causes // XXX For some reason, putting this in an anonymous namespace causes
// errors // errors
struct DynamicMutableIndexer : Vistor<int64_t &> { struct DynamicMutableIndexer : Vistor<int64_t &> {
public: public:
explicit DynamicMutableIndexer(int idx) : idx_(idx) {} explicit DynamicMutableIndexer(int idx) : idx_(idx) {}
template <int D> int64_t &operator()(Dim<D> &dim) const { template <int D> int64_t &operator()(Dim<D> &dim) const { return dim[idx_]; }
return dim[idx_];
}
private: private:
int idx_; int idx_;
}; };
struct DynamicConstIndexer : public Vistor<int64_t> { struct DynamicConstIndexer : public Vistor<int64_t> {
public: public:
explicit DynamicConstIndexer(int idx) : idx_(idx) {} 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_]; return dim[idx_];
} }
private: private:
int idx_; int idx_;
}; };
/// @endcond /// @endcond
int64_t &DDim::operator[](int idx) { int64_t &DDim::operator[](int idx) {
return DDim::ApplyVistor(DynamicMutableIndexer(idx), *this); return DDim::ApplyVistor(DynamicMutableIndexer(idx), *this);
} }
int64_t DDim::operator[](int idx) const { int64_t DDim::operator[](int idx) const {
return DDim::ApplyVistor(DynamicConstIndexer(idx), *this); return DDim::ApplyVistor(DynamicConstIndexer(idx), *this);
} }
int DDim::size() const { return arity(*this); } int DDim::size() const { return arity(*this); }
bool DDim::operator==(DDim d) const { bool DDim::operator==(DDim d) const {
// if (var.which() != d.getVar().which()) { // if (var.which() != d.getVar().which()) {
// return false; // return false;
// } else { // } else {
std::vector<int64_t> v1 = vectorize(*this); std::vector<int64_t> v1 = vectorize(*this);
std::vector<int64_t> v2 = vectorize(d); std::vector<int64_t> v2 = vectorize(d);
for (unsigned int i = 0; i < v1.size(); i++) { for (unsigned int i = 0; i < v1.size(); i++) {
if (v1[i] != v2[i]) { if (v1[i] != v2[i]) {
return false; return false;
}
} }
}
return true; return true;
// } // }
} }
bool DDim::operator!=(DDim d) const { return !(*this == d); } bool DDim::operator!=(DDim d) const { return !(*this == d); }
DDim DDim::operator+(DDim d) const { DDim DDim::operator+(DDim d) const {
std::vector<int64_t> v1 = vectorize(*this); std::vector<int64_t> v1 = vectorize(*this);
std::vector<int64_t> v2 = vectorize(d); std::vector<int64_t> v2 = vectorize(d);
std::vector<int64_t> v3; std::vector<int64_t> v3;
assert(v1.size() == v2.size()); assert(v1.size() == v2.size());
for (unsigned int i = 0; i < v1.size(); i++) { for (unsigned int i = 0; i < v1.size(); i++) {
v3.push_back(v1[i] + v2[i]); v3.push_back(v1[i] + v2[i]);
} }
return make_ddim(v3); return make_ddim(v3);
} }
DDim DDim::operator*(DDim d) const { DDim DDim::operator*(DDim d) const {
std::vector<int64_t> v1 = vectorize(*this); std::vector<int64_t> v1 = vectorize(*this);
std::vector<int64_t> v2 = vectorize(d); std::vector<int64_t> v2 = vectorize(d);
std::vector<int64_t> v3; std::vector<int64_t> v3;
assert(v1.size() == v2.size()); assert(v1.size() == v2.size());
for (unsigned int i = 0; i < v1.size(); i++) { for (unsigned int i = 0; i < v1.size(); i++) {
v3.push_back(v1[i] * v2[i]); v3.push_back(v1[i] * v2[i]);
} }
return make_ddim(v3); return make_ddim(v3);
} }
int64_t get(const DDim &ddim, int idx) { return ddim[idx]; } int64_t get(const DDim &ddim, int idx) { return ddim[idx]; }
...@@ -180,152 +178,152 @@ void set(DDim &ddim, int idx, int value) { ddim[idx] = value; } ...@@ -180,152 +178,152 @@ void set(DDim &ddim, int idx, int value) { ddim[idx] = value; }
/// @cond HIDDEN /// @cond HIDDEN
struct VectorizeVisitor : Vistor<void> { struct VectorizeVisitor : Vistor<void> {
std::vector<int64_t> &vector; std::vector<int64_t> &vector;
explicit VectorizeVisitor(std::vector<int64_t> &v) : vector(v) {} 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); vector.push_back(t.head);
this->operator()(t.tail); this->operator()(t.tail);
} }
void operator()(const Dim<0> &t) {} void operator()(const Dim<0> &t) {}
}; };
/// @endcond /// @endcond
std::vector<int64_t> vectorize(const DDim &ddim) { std::vector<int64_t> vectorize(const DDim &ddim) {
std::vector<int64_t> result; std::vector<int64_t> result;
VectorizeVisitor visitor(result); VectorizeVisitor visitor(result);
DDim::ApplyVistor(visitor, ddim); DDim::ApplyVistor(visitor, ddim);
return result; return result;
} }
// NOTE: framework::vectorize converts to type int64_t // NOTE: framework::vectorize converts to type int64_t
// which does not fit cudnn inputs. // which does not fit cudnn inputs.
std::vector<int> vectorize2int(const DDim &ddim) { std::vector<int> vectorize2int(const DDim &ddim) {
std::vector<int64_t> temp = vectorize(ddim); std::vector<int64_t> temp = vectorize(ddim);
std::vector<int> result(temp.begin(), temp.end()); std::vector<int> result(temp.begin(), temp.end());
return result; return result;
} }
struct ProductVisitor : Vistor<int64_t> { 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); return product(dim);
} }
}; };
int64_t product(const DDim &ddim) { int64_t product(const DDim &ddim) {
ProductVisitor visitor; ProductVisitor visitor;
return DDim::ApplyVistor(visitor, ddim); return DDim::ApplyVistor(visitor, ddim);
} }
struct SliceVectorizeVisitor : Vistor<void> { struct SliceVectorizeVisitor : Vistor<void> {
std::vector<int64_t> &vector; std::vector<int64_t> &vector;
int begin; int begin;
int end; int end;
SliceVectorizeVisitor(std::vector<int64_t> &v, int b, int e) SliceVectorizeVisitor(std::vector<int64_t> &v, int b, int e)
: vector(v), begin(b), end(e) { : vector(v), begin(b), end(e) {
// PADDLE_ENFORCE(begin < end, // PADDLE_ENFORCE(begin < end,
// "Begin index must be less than end index in // "Begin index must be less than end index in
// ddim // ddim
// slice."); // slice.");
// PADDLE_ENFORCE(begin >= 0, // PADDLE_ENFORCE(begin >= 0,
// "Begin index can't be less than zero in // "Begin index can't be less than zero in
// ddim slice."); // ddim slice.");
}
template <int S> void operator()(const Dim<S> &dim) {
if (begin == 0) {
vector.push_back(dim.head);
} else {
--begin;
} }
--end;
template <int S> void operator()(const Dim<S> &dim) { if (end > 0) {
if (begin == 0) { this->operator()(dim.tail);
vector.push_back(dim.head);
} else {
--begin;
}
--end;
if (end > 0) {
this->operator()(dim.tail);
}
} }
}
void operator()(const Dim<0> &dim) { void operator()(const Dim<0> &dim) {
// PADDLE_ENFORCE(end == 0, "End index in ddim slice is out // PADDLE_ENFORCE(end == 0, "End index in ddim slice is out
// of bound."); // of bound.");
} }
}; };
DDim slice_ddim(const DDim &ddim, int begin, int end) { DDim slice_ddim(const DDim &ddim, int begin, int end) {
std::vector<int64_t> vec; std::vector<int64_t> vec;
vec.reserve(end - begin); vec.reserve(end - begin);
SliceVectorizeVisitor visitor(vec, begin, end); SliceVectorizeVisitor visitor(vec, begin, end);
// boost::apply_visitor(visitor, dim); // boost::apply_visitor(visitor, dim);
DDim::ApplyVistor(visitor, ddim); DDim::ApplyVistor(visitor, ddim);
// visitor(ddim.var.Get<Dim<4>>()); // visitor(ddim.var.Get<Dim<4>>());
return make_ddim(vec); return make_ddim(vec);
} }
/// \cond HIDDEN /// \cond HIDDEN
struct ArityVisitor : Vistor<int> { 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 /// \endcond
int arity(const DDim &d) { int arity(const DDim &d) {
ArityVisitor arityVisitor = ArityVisitor(); ArityVisitor arityVisitor = ArityVisitor();
return DDim::ApplyVistor(arityVisitor, d); return DDim::ApplyVistor(arityVisitor, d);
// return arityVisitor(d.var.Get<Dim<4>>()); // return arityVisitor(d.var.Get<Dim<4>>());
// return boost::apply_visitor(ArityVisitor(), d); } // return boost::apply_visitor(ArityVisitor(), d); }
} }
/// \cond HIDDEN /// \cond HIDDEN
/// \endcond /// \endcond
struct OSVistor : Vistor<std::ostream &> { struct OSVistor : Vistor<std::ostream &> {
OSVistor(std::ostream &os) : os_(os) {} 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; return os_ << dim;
} }
private: private:
std::ostream &os_; std::ostream &os_;
}; };
std::ostream &operator<<(std::ostream &os, const DDim &ddim) { std::ostream &operator<<(std::ostream &os, const DDim &ddim) {
auto vistor = OSVistor(os); auto vistor = OSVistor(os);
DDim::ApplyVistor(vistor, ddim); DDim::ApplyVistor(vistor, ddim);
return os; return os;
} }
DDim::DDim(std::initializer_list<int64_t> init_list) { DDim::DDim(std::initializer_list<int64_t> init_list) {
*this = make_ddim(init_list); *this = make_ddim(init_list);
} }
DDim flatten_to_2d(const DDim &src, int num_col_dims) { DDim flatten_to_2d(const DDim &src, int num_col_dims) {
int rank = src.size(); int rank = src.size();
return make_ddim({product(slice_ddim(src, 0, num_col_dims)), return make_ddim({product(slice_ddim(src, 0, num_col_dims)),
product(slice_ddim(src, num_col_dims, rank))}); product(slice_ddim(src, num_col_dims, rank))});
} }
DDim flatten_to_1d(const DDim &src) { return make_ddim({product(src)}); } DDim flatten_to_1d(const DDim &src) { return make_ddim({product(src)}); }
DDim stride(const DDim &ddim) { DDim stride(const DDim &ddim) {
std::vector<int64_t> strides(ddim.size()); std::vector<int64_t> strides(ddim.size());
strides[ddim.size() - 1] = 1; strides[ddim.size() - 1] = 1;
for (int i = ddim.size() - 2; i >= 0; --i) { for (int i = ddim.size() - 2; i >= 0; --i) {
strides[i] = strides[i + 1] * ddim[i + 1]; strides[i] = strides[i + 1] * ddim[i + 1];
} }
return framework::make_ddim(strides); return framework::make_ddim(strides);
} }
DDim stride_numel(const framework::DDim &ddim) { DDim stride_numel(const framework::DDim &ddim) {
std::vector<int64_t> strides(ddim.size()); std::vector<int64_t> strides(ddim.size());
strides[ddim.size() - 1] = ddim[ddim.size() - 1]; strides[ddim.size() - 1] = ddim[ddim.size() - 1];
for (int i = ddim.size() - 2; i >= 0; --i) { for (int i = ddim.size() - 2; i >= 0; --i) {
strides[i] = strides[i + 1] * ddim[i]; strides[i] = strides[i + 1] * ddim[i];
} }
return framework::make_ddim(strides); return framework::make_ddim(strides);
} }
} // namespace framework } // namespace framework
......
src/framework/ddim.h
浏览文件 @ 1ad8f821
...@@ -30,77 +30,77 @@ namespace framework { ...@@ -30,77 +30,77 @@ namespace framework {
* The number of dimensions must be between [1, 9]. * The number of dimensions must be between [1, 9].
*/ */
struct DDim { struct DDim {
typedef Variant<Dim<0>, Dim<1>, Dim<2>, Dim<3>, Dim<4>, Dim<5>, Dim<6>, typedef Variant<Dim<0>, Dim<1>, Dim<2>, Dim<3>, Dim<4>, Dim<5>, Dim<6>,
Dim<7>, Dim<8>, Dim<9>> Dim<7>, Dim<8>, Dim<9>>
DDimVar; DDimVar;
DDimVar var; DDimVar var;
template <typename Vistor> template <typename Vistor>
static typename Vistor::type_t ApplyVistor(Vistor vistor, const DDim &d) { static typename Vistor::type_t ApplyVistor(Vistor vistor, const DDim &d) {
if (d.var.TypeId() == typeid(Dim<0>).hash_code()) { if (d.var.TypeId() == typeid(Dim<0>).hash_code()) {
return vistor(d.var.Get<Dim<0>>()); return vistor(d.var.Get<Dim<0>>());
} else if (d.var.TypeId() == typeid(Dim<1>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<1>).hash_code()) {
return vistor(d.var.Get<Dim<1>>()); return vistor(d.var.Get<Dim<1>>());
} else if (d.var.TypeId() == typeid(Dim<2>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<2>).hash_code()) {
return vistor(d.var.Get<Dim<2>>()); return vistor(d.var.Get<Dim<2>>());
} else if (d.var.TypeId() == typeid(Dim<3>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<3>).hash_code()) {
return vistor(d.var.Get<Dim<3>>()); return vistor(d.var.Get<Dim<3>>());
} else if (d.var.TypeId() == typeid(Dim<4>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<4>).hash_code()) {
return vistor(d.var.Get<Dim<4>>()); return vistor(d.var.Get<Dim<4>>());
} else if (d.var.TypeId() == typeid(Dim<5>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<5>).hash_code()) {
return vistor(d.var.Get<Dim<5>>()); return vistor(d.var.Get<Dim<5>>());
} else if (d.var.TypeId() == typeid(Dim<6>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<6>).hash_code()) {
return vistor(d.var.Get<Dim<6>>()); return vistor(d.var.Get<Dim<6>>());
} else if (d.var.TypeId() == typeid(Dim<7>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<7>).hash_code()) {
return vistor(d.var.Get<Dim<7>>()); return vistor(d.var.Get<Dim<7>>());
} else if (d.var.TypeId() == typeid(Dim<8>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<8>).hash_code()) {
return vistor(d.var.Get<Dim<8>>()); return vistor(d.var.Get<Dim<8>>());
} else if (d.var.TypeId() == typeid(Dim<9>).hash_code()) { } else if (d.var.TypeId() == typeid(Dim<9>).hash_code()) {
return vistor(d.var.Get<Dim<9>>()); return vistor(d.var.Get<Dim<9>>());
} else { } else {
printf(" dim not support \n"); printf(" dim not support \n");
throw std::bad_exception(); throw std::bad_exception();
// return typename Vistor::type_t(); // return typename Vistor::type_t();
}
} }
}
DDim() { var.Set<Dim<1>>(Dim<1>()); } 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); /*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); var.Set<Dim<D>>(in);
return *this; return *this;
} }
int64_t &operator[](int idx); int64_t &operator[](int idx);
int64_t operator[](int idx) const; int64_t operator[](int idx) const;
// template <typename Visitor> // template <typename Visitor>
// typename Visitor::result_type apply_visitor(Visitor& visitor) { // typename Visitor::result_type apply_visitor(Visitor& visitor) {
// return var.apply_visitor(visitor); // return var.apply_visitor(visitor);
// } // }
// //
// template <typename Visitor> // template <typename Visitor>
// typename Visitor::result_type apply_visitor(Visitor& visitor) // typename Visitor::result_type apply_visitor(Visitor& visitor)
// const { // const {
// return var.apply_visitor(visitor); // return var.apply_visitor(visitor);
// } // }
DDimVar getVar() { return var; } DDimVar getVar() { return var; }
bool operator==(DDim d) const; bool operator==(DDim d) const;
bool operator!=(DDim d) const; bool operator!=(DDim d) const;
DDim operator+(DDim d) const; DDim operator+(DDim d) const;
DDim operator*(DDim d) const; DDim operator*(DDim d) const;
int size() const; int size() const;
}; };
/** /**
......
src/framework/dim.h
浏览文件 @ 1ad8f821
...@@ -25,199 +25,197 @@ namespace framework { ...@@ -25,199 +25,197 @@ namespace framework {
// Statically sized, statically indexed dimension // Statically sized, statically indexed dimension
template <int i> struct Dim { template <int i> struct Dim {
static constexpr int dimensions = i; static constexpr int dimensions = i;
template <typename... Args> template <typename... Args>
HOSTDEVICE Dim(int64_t _head, Args... _tail) : head(_head), tail(_tail...) { HOSTDEVICE Dim(int64_t _head, Args... _tail) : head(_head), tail(_tail...) {
static_assert(sizeof...(_tail) == i - 1, static_assert(sizeof...(_tail) == i - 1,
"Dim initialized with the wrong number of parameters"); "Dim initialized with the wrong number of parameters");
} }
HOSTDEVICE HOSTDEVICE
Dim(int64_t _head, const Dim<i - 1> &_tail) : head(_head), tail(_tail) {} Dim(int64_t _head, const Dim<i - 1> &_tail) : head(_head), tail(_tail) {}
HOSTDEVICE HOSTDEVICE
Dim() : head(0), tail() {} Dim() : head(0), tail() {}
/** Construct a Dim from a linear index and size. Uses Fortran /** Construct a Dim from a linear index and size. Uses Fortran
* order * order
* indexing. */ * indexing. */
HOSTDEVICE HOSTDEVICE
Dim(int64_t idx, const Dim<i> &size) Dim(int64_t idx, const Dim<i> &size)
: head(idx % size.head), tail(idx / size.head, size.tail) {} : head(idx % size.head), tail(idx / size.head, size.tail) {}
/** Construct a Dim with each dimension set to the given index */ /** Construct a Dim with each dimension set to the given index */
HOSTDEVICE HOSTDEVICE
Dim(int64_t idx) : head(idx), tail(idx) {} Dim(int64_t idx) : head(idx), tail(idx) {}
HOSTDEVICE HOSTDEVICE
bool operator==(const Dim<i> &o) const { bool operator==(const Dim<i> &o) const {
return (head == o.head) && (tail == o.tail); return (head == o.head) && (tail == o.tail);
} }
HOSTDEVICE HOSTDEVICE
bool operator!=(const Dim<i> &o) const { return !(*this == o); } bool operator!=(const Dim<i> &o) const { return !(*this == o); }
HOSTDEVICE HOSTDEVICE
int64_t &operator[](int idx); int64_t &operator[](int idx);
HOSTDEVICE HOSTDEVICE
int64_t operator[](int idx) const; int64_t operator[](int idx) const;
HOST std::string to_string() const; HOST std::string to_string() const;
int64_t head; int64_t head;
Dim<i - 1> tail; Dim<i - 1> tail;
}; };
// Base case specialization // Base case specialization
template <> struct Dim<0> { template <> struct Dim<0> {
static constexpr int dimensions = 0; static constexpr int dimensions = 0;
HOSTDEVICE HOSTDEVICE
Dim(int64_t _head) {} Dim(int64_t _head) {}
HOSTDEVICE HOSTDEVICE
Dim() {} Dim() {}
HOSTDEVICE HOSTDEVICE
Dim(int idx, const Dim<0> &size) { Dim(int idx, const Dim<0> &size) {
#ifndef __CUDA_ARCH__ #ifndef __CUDA_ARCH__
if (idx > 0) { if (idx > 0) {
throw std::invalid_argument("Index out of range."); throw std::invalid_argument("Index out of range.");
} }
#else #else
PADDLE_ASSERT(idx == 0); PADDLE_ASSERT(idx == 0);
#endif #endif
} }
HOSTDEVICE HOSTDEVICE
bool operator==(const Dim<0> &o) const { return true; } bool operator==(const Dim<0> &o) const { return true; }
HOSTDEVICE HOSTDEVICE
bool operator!=(const Dim<0> &o) const { return false; } bool operator!=(const Dim<0> &o) const { return false; }
HOSTDEVICE HOSTDEVICE
int64_t &operator[](int idx); int64_t &operator[](int idx);
HOSTDEVICE HOSTDEVICE
int64_t operator[](int idx) const; int64_t operator[](int idx) const;
}; };
namespace { namespace {
// Helper for accessing Dim classes // Helper for accessing Dim classes
template <int i> struct DimGetter { template <int i> struct DimGetter {
// Return a copy if Dim is const // 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 DimGetter<i - 1>::impl(d.tail);
} }
// Return a reference if Dim is mutable // 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); return DimGetter<i - 1>::impl(d.tail);
} }
}; };
// Eureka! We found the element! // Eureka! We found the element!
template <> struct DimGetter<0> { template <> struct DimGetter<0> {
// Return a copy if Dim is const // 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 d.head;
} }
// Return a reference if Dim is mutable // 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 d.head; }
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__ #ifndef __CUDA_ARCH__
if (idx < 0) { if (idx < 0) {
throw std::invalid_argument("Tried to access a negative dimension"); throw std::invalid_argument("Tried to access a negative dimension");
} }
#else #else
PADDLE_ASSERT(idx >= 0); PADDLE_ASSERT(idx >= 0);
#endif #endif
if (idx == 0) { if (idx == 0) {
return dim.head; return dim.head;
} }
return indexer(dim.tail, idx - 1); 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__ #ifndef __CUDA_ARCH__
throw std::invalid_argument("Invalid index"); throw std::invalid_argument("Invalid index");
#else #else
PADDLE_ASSERT(false); PADDLE_ASSERT(false);
#if CUDA_VERSION < 8000 #if CUDA_VERSION < 8000
// On CUDA versions previous to 8.0, only __shared__ variables // On CUDA versions previous to 8.0, only __shared__ variables
// could be declared as static in the device code. // could be declared as static in the device code.
int64_t head = 0; int64_t head = 0;
#else #else
static int64_t head = 0; static int64_t head = 0;
#endif #endif
return head; return head;
#endif #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__ #ifndef __CUDA_ARCH__
if (idx < 0) { if (idx < 0) {
throw std::invalid_argument("Tried to access a negative dimension"); throw std::invalid_argument("Tried to access a negative dimension");
} }
#else #else
PADDLE_ASSERT(idx >= 0); PADDLE_ASSERT(idx >= 0);
#endif #endif
if (idx == 0) { if (idx == 0) {
return dim.head; return dim.head;
} }
return indexer(dim.tail, idx - 1); 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__ #ifndef __CUDA_ARCH__
throw std::invalid_argument("Invalid index"); throw std::invalid_argument("Invalid index");
#else #else
PADDLE_ASSERT(false); PADDLE_ASSERT(false);
#if CUDA_VERSION < 8000 #if CUDA_VERSION < 8000
// On CUDA versions previous to 8.0, only __shared__ variables // On CUDA versions previous to 8.0, only __shared__ variables
// could be declared as static in the device code. // could be declared as static in the device code.
int64_t head = 0; int64_t head = 0;
#else #else
static int64_t head = 0; static int64_t head = 0;
#endif #endif
return head; return head;
#endif #endif
} }
} // namespace } // namespace
// Static access to constant Dim // 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); return DimGetter<i>::impl(d);
} }
// Static access to mutable Dim // 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); return DimGetter<i>::impl(d);
} }
// Dynamic access to constant Dim // 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; // std::cout << "l: " << l << std::endl;
return indexer(*this, i); return indexer(*this, i);
} }
// Dynamic access to mutable Dim // 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); return indexer(*this, i);
} }
// Dynamic access to constant Dim // Dynamic access to constant Dim
inline HOSTDEVICE int64_t Dim<0>::operator[](int i) const { inline HOSTDEVICE int64_t Dim<0>::operator[](int i) const {
return indexer(*this, i); return indexer(*this, i);
} }
// Dynamic access to mutable Dim // Dynamic access to mutable Dim
inline HOSTDEVICE int64_t &Dim<0>::operator[](int i) { inline HOSTDEVICE int64_t &Dim<0>::operator[](int i) {
return indexer(*this, i); return indexer(*this, i);
} }
// Dynamic access to constant Dim // Dynamic access to constant Dim
...@@ -225,52 +223,52 @@ inline HOSTDEVICE int64_t &Dim<0>::operator[](int i) { ...@@ -225,52 +223,52 @@ inline HOSTDEVICE int64_t &Dim<0>::operator[](int i) {
template <int l> template <int l>
HOSTDEVICE typename std::enable_if<(l > 0), int64_t>::type get(const Dim<l> &d, HOSTDEVICE typename std::enable_if<(l > 0), int64_t>::type get(const Dim<l> &d,
int i) { int i) {
return d[i]; return d[i];
} }
// Dynamic access to mutable Dim // Dynamic access to mutable Dim
template <int l> template <int l>
HOSTDEVICE typename std::enable_if<(l > 0), int64_t &>::type get(Dim<l> &d, HOSTDEVICE typename std::enable_if<(l > 0), int64_t &>::type get(Dim<l> &d,
int i) { int i) {
return d[i]; return d[i];
} }
// Dot product of two dims // Dot product of two dims
template <int i> template <int i>
HOSTDEVICE int64_t linearize(const Dim<i> &a, const Dim<i> &b) { HOSTDEVICE int64_t linearize(const Dim<i> &a, const Dim<i> &b) {
return a.head * b.head + linearize(a.tail, b.tail); return a.head * b.head + linearize(a.tail, b.tail);
} }
// Base case dot product of two Dims // Base case dot product of two Dims
// Notice it is inline because it is no longer a template // Notice it is inline because it is no longer a template
template <> template <>
HOSTDEVICE inline int64_t linearize(const Dim<0> &a, const Dim<0> &b) { HOSTDEVICE inline int64_t linearize(const Dim<0> &a, const Dim<0> &b) {
return 0; return 0;
} }
// Product of a Dim // 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); return prod * a.head * product(a.tail);
} }
// Base case product of a Dim // Base case product of a Dim
// Notice it is inline because it is no longer a template // 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; return prod;
} }
// Is 0 <= idx_i < size_i for all i? // Is 0 <= idx_i < size_i for all i?
template <int i> template <int i>
HOSTDEVICE bool contained(const Dim<i> &idx, const Dim<i> &size) { HOSTDEVICE bool contained(const Dim<i> &idx, const Dim<i> &size) {
return ((0 <= idx.head) && (idx.head < size.head) && return ((0 <= idx.head) && (idx.head < size.head) &&
contained(idx.tail, size.tail)); contained(idx.tail, size.tail));
} }
// Base case of is 0 <= idx_i < size_i ? // Base case of is 0 <= idx_i < size_i ?
// Notice it is inline because it is no longer a template // Notice it is inline because it is no longer a template
template <> template <>
HOSTDEVICE inline bool contained(const Dim<0> &idx, const Dim<0> &size) { HOSTDEVICE inline bool contained(const Dim<0> &idx, const Dim<0> &size) {
return true; return true;
} }
/** /**
...@@ -278,14 +276,14 @@ HOSTDEVICE inline bool contained(const Dim<0> &idx, const Dim<0> &size) { ...@@ -278,14 +276,14 @@ HOSTDEVICE inline bool contained(const Dim<0> &idx, const Dim<0> &size) {
*/ */
template <int i> template <int i>
HOSTDEVICE Dim<i> ex_prefix_mul(const Dim<i> &src, int mul = 1) { HOSTDEVICE Dim<i> ex_prefix_mul(const Dim<i> &src, int mul = 1) {
return Dim<i>(mul, ex_prefix_mul(src.tail, mul * src.head)); return Dim<i>(mul, ex_prefix_mul(src.tail, mul * src.head));
} }
///\cond HIDDEN ///\cond HIDDEN
// Base case of ex_prefix_mul // Base case of ex_prefix_mul
// Notice it is inline because it is no longer a template // 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>(); return Dim<0>();
} }
///\endcond ///\endcond
...@@ -293,36 +291,36 @@ template <> HOSTDEVICE inline Dim<0> ex_prefix_mul(const Dim<0> &src, int mul) { ...@@ -293,36 +291,36 @@ template <> HOSTDEVICE inline Dim<0> ex_prefix_mul(const Dim<0> &src, int mul) {
* Add two dimensions together * 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)); return Dim<i>(a.head + b.head, dim_plus(a.tail, b.tail));
} }
// Base case // Base case
template <> template <>
HOSTDEVICE inline Dim<0> dim_plus(const Dim<0> &a, const Dim<0> &b) { HOSTDEVICE inline Dim<0> dim_plus(const Dim<0> &a, const Dim<0> &b) {
return Dim<0>(); return Dim<0>();
} }
template <int i> template <int i>
HOSTDEVICE Dim<i> operator+(const Dim<i> &lhs, const Dim<i> &rhs) { HOSTDEVICE Dim<i> operator+(const Dim<i> &lhs, const Dim<i> &rhs) {
return dim_plus(lhs, rhs); return dim_plus(lhs, rhs);
} }
/** /**
* Multiply two dimensions together * 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)); return Dim<i>(a.head * b.head, dim_mult(a.tail, b.tail));
} }
// Base case // Base case
template <> template <>
HOSTDEVICE inline Dim<0> dim_mult(const Dim<0> &a, const Dim<0> &b) { HOSTDEVICE inline Dim<0> dim_mult(const Dim<0> &a, const Dim<0> &b) {
return Dim<0>(); return Dim<0>();
} }
template <int i> template <int i>
HOSTDEVICE Dim<i> operator*(const Dim<i> &lhs, const Dim<i> &rhs) { HOSTDEVICE Dim<i> operator*(const Dim<i> &lhs, const Dim<i> &rhs) {
return dim_mult(lhs, rhs); return dim_mult(lhs, rhs);
} }
/** /**
...@@ -337,8 +335,8 @@ HOSTDEVICE Dim<i> operator*(const Dim<i> &lhs, const Dim<i> &rhs) { ...@@ -337,8 +335,8 @@ HOSTDEVICE Dim<i> operator*(const Dim<i> &lhs, const Dim<i> &rhs) {
template <int i> template <int i>
HOSTDEVICE Dim<i> normalize_strides(const Dim<i> &size, const Dim<i> &stride) { HOSTDEVICE Dim<i> normalize_strides(const Dim<i> &size, const Dim<i> &stride) {
int norm_stride = size.head == 1 ? 0 : stride.head; int norm_stride = size.head == 1 ? 0 : stride.head;
return Dim<i>(norm_stride, normalize_strides(size.tail, stride.tail)); return Dim<i>(norm_stride, normalize_strides(size.tail, stride.tail));
} }
///\cond HIDDEN ///\cond HIDDEN
...@@ -346,7 +344,7 @@ HOSTDEVICE Dim<i> normalize_strides(const Dim<i> &size, const Dim<i> &stride) { ...@@ -346,7 +344,7 @@ HOSTDEVICE Dim<i> normalize_strides(const Dim<i> &size, const Dim<i> &stride) {
template <> template <>
HOSTDEVICE inline Dim<0> normalize_strides(const Dim<0> &size, HOSTDEVICE inline Dim<0> normalize_strides(const Dim<0> &size,
const Dim<0> &stride) { const Dim<0> &stride) {
return Dim<0>(); return Dim<0>();
} }
///\endcond ///\endcond
...@@ -361,7 +359,7 @@ HOSTDEVICE inline Dim<0> normalize_strides(const Dim<0> &size, ...@@ -361,7 +359,7 @@ HOSTDEVICE inline Dim<0> normalize_strides(const Dim<0> &size,
template <typename... Args> template <typename... Args>
HOSTDEVICE Dim<sizeof...(Args)> make_dim(Args... idxes) { HOSTDEVICE Dim<sizeof...(Args)> make_dim(Args... idxes) {
return Dim<sizeof...(Args)>(idxes...); return Dim<sizeof...(Args)>(idxes...);
} }
// Allows us to output a Dim // Allows us to output a Dim
...@@ -369,8 +367,8 @@ HOSTDEVICE Dim<sizeof...(Args)> make_dim(Args... idxes) { ...@@ -369,8 +367,8 @@ HOSTDEVICE Dim<sizeof...(Args)> make_dim(Args... idxes) {
template <int i> template <int i>
typename std::enable_if<(i > 1), std::ostream &>::type typename std::enable_if<(i > 1), std::ostream &>::type
operator<<(std::ostream &os, const Dim<i> &d) { operator<<(std::ostream &os, const Dim<i> &d) {
os << d.head << ", " << d.tail; os << d.head << ", " << d.tail;
return os; return os;
} }
// Base case that allows us to output a Dim // Base case that allows us to output a Dim
...@@ -378,34 +376,34 @@ operator<<(std::ostream &os, const Dim<i> &d) { ...@@ -378,34 +376,34 @@ operator<<(std::ostream &os, const Dim<i> &d) {
template <int i> template <int i>
typename std::enable_if<(i == 1), std::ostream &>::type typename std::enable_if<(i == 1), std::ostream &>::type
operator<<(std::ostream &os, const Dim<i> &d) { operator<<(std::ostream &os, const Dim<i> &d) {
os << d.head; os << d.head;
return os; return os;
} }
inline std::ostream &operator<<(std::ostream &os, const Dim<0> &d) { inline std::ostream &operator<<(std::ostream &os, const Dim<0> &d) {
return os; 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; std::stringstream stream;
stream << *this; stream << *this;
return stream.str(); return stream.str();
} }
template <int D> template <int D>
HOSTDEVICE Dim<D> linear_to_dimension(int linear_index, Dim<D> extents) { HOSTDEVICE Dim<D> linear_to_dimension(int linear_index, Dim<D> extents) {
Dim<D> result; Dim<D> result;
for (int i = 0; i < D - 1; ++i) { for (int i = 0; i < D - 1; ++i) {
result[i] = linear_index % extents[i]; result[i] = linear_index % extents[i];
linear_index /= extents[i]; linear_index /= extents[i];
} }
result[D - 1] = linear_index; result[D - 1] = linear_index;
return result; return result;
} }
} // namespace framework } // namespace framework
......
src/framework/executor.cpp
浏览文件 @ 1ad8f821
...@@ -26,66 +26,66 @@ namespace framework { ...@@ -26,66 +26,66 @@ namespace framework {
template <typename Dtype> template <typename Dtype>
Executor<Dtype>::Executor(const Program<Dtype> p) : program_(p) { Executor<Dtype>::Executor(const Program<Dtype> p) : program_(p) {
if (use_optimize_) { if (use_optimize_) {
to_predict_program_ = program_.optimizeProgram; to_predict_program_ = program_.optimizeProgram;
} else { } else {
to_predict_program_ = program_.originProgram; to_predict_program_ = program_.originProgram;
} }
// const std::vector<std::shared_ptr<BlockDesc>> blocks = // const std::vector<std::shared_ptr<BlockDesc>> blocks =
to_predict_program_->Blocks(); to_predict_program_->Blocks();
// for (int i = 0; i < blocks.size(); ++i) { // for (int i = 0; i < blocks.size(); ++i) {
// std::shared_ptr<BlockDesc> block_desc = blocks[i]; // std::shared_ptr<BlockDesc> block_desc = blocks[i];
// std::vector<std::shared_ptr<OpDesc>> ops = block_desc->Ops(); // std::vector<std::shared_ptr<OpDesc>> ops = block_desc->Ops();
// for (int j = 0; j < ops.size(); ++j) { // for (int j = 0; j < ops.size(); ++j) {
// std::shared_ptr<OpDesc> op = ops[j]; // std::shared_ptr<OpDesc> op = ops[j];
// if (op->Type() == "conv2d" && op->Input("Input")[0] == // if (op->Type() == "conv2d" && op->Input("Input")[0] ==
// "pixel") { // "pixel") {
// Attribute strides_attr = op->GetAttrMap().at("strides"); // Attribute strides_attr = op->GetAttrMap().at("strides");
// std::vector<int> stride = // std::vector<int> stride =
// strides_attr.Get<std::vector<int>>(); for (int k = 0; k < // strides_attr.Get<std::vector<int>>(); for (int k = 0; k <
// stride.size(); ++k) { // stride.size(); ++k) {
// } // }
// std::shared_ptr<operators::ConvOp<Dtype, float>> conv = // std::shared_ptr<operators::ConvOp<Dtype, float>> conv =
// std::make_shared<operators::ConvOp<Dtype, float>>( // std::make_shared<operators::ConvOp<Dtype, float>>(
// op->Type(), op->GetInputs(), op->GetOutputs(), // op->Type(), op->GetInputs(), op->GetOutputs(),
// op->GetAttrMap(), program_.scope); // op->GetAttrMap(), program_.scope);
// ops_of_block_[*block_desc.get()].push_back(conv); // ops_of_block_[*block_desc.get()].push_back(conv);
// } // }
// } // }
// } // }
} }
template <typename Dtype> template <typename Dtype>
std::shared_ptr<Tensor> Executor<Dtype>::predict(Tensor &t) { std::shared_ptr<Tensor> Executor<Dtype>::predict(Tensor &t) {
// feed // feed
auto scope = program_.scope; auto scope = program_.scope;
Variable *g_feed_value = scope->Var("pixel"); Variable *g_feed_value = scope->Var("pixel");
auto tensor = g_feed_value->GetMutable<Tensor>(); auto tensor = g_feed_value->GetMutable<Tensor>();
tensor->ShareDataWith(t); tensor->ShareDataWith(t);
Variable *con_output = scope->Var("conv2d_0.tmp_0"); Variable *con_output = scope->Var("conv2d_0.tmp_0");
Tensor *output_tensor = con_output->GetMutable<Tensor>(); Tensor *output_tensor = con_output->GetMutable<Tensor>();
output_tensor->mutable_data<float>({1, 16, 32, 32}); output_tensor->mutable_data<float>({1, 16, 32, 32});
// std::cout << typeid(output_tensor).name() << std::endl; // std::cout << typeid(output_tensor).name() << std::endl;
// std::cout << "output_tensor dims: " << output_tensor->dims() << // std::cout << "output_tensor dims: " << output_tensor->dims() <<
// std::endl; // std::endl;
std::shared_ptr<Tensor> out_tensor = std::make_shared<LoDTensor>(); std::shared_ptr<Tensor> out_tensor = std::make_shared<LoDTensor>();
out_tensor.reset(output_tensor); out_tensor.reset(output_tensor);
predict(t, 0); predict(t, 0);
return out_tensor; return out_tensor;
} }
template <typename Dtype> template <typename Dtype>
void Executor<Dtype>::predict(const Tensor &t, int block_id) { void Executor<Dtype>::predict(const Tensor &t, int block_id) {
std::shared_ptr<BlockDesc> to_predict_block = std::shared_ptr<BlockDesc> to_predict_block =
to_predict_program_->Block(block_id); to_predict_program_->Block(block_id);
for (int j = 0; j < ops_of_block_[*to_predict_block.get()].size(); ++j) { for (int j = 0; j < ops_of_block_[*to_predict_block.get()].size(); ++j) {
auto op = ops_of_block_[*to_predict_block.get()][j]; auto op = ops_of_block_[*to_predict_block.get()][j];
op->Run(); op->Run();
} }
} }
template class Executor<CPU>; template class Executor<CPU>;
......
src/framework/executor.h
浏览文件 @ 1ad8f821
...@@ -35,23 +35,23 @@ namespace paddle_mobile { ...@@ -35,23 +35,23 @@ namespace paddle_mobile {
namespace framework { namespace framework {
template <typename Dtype> class Executor { template <typename Dtype> class Executor {
public: public:
Executor(); Executor();
Executor(const Program<Dtype> p); Executor(const Program<Dtype> p);
std::shared_ptr<Tensor> predict(Tensor &t); std::shared_ptr<Tensor> predict(Tensor &t);
public: public:
const framework::Program<Dtype> program_; const framework::Program<Dtype> program_;
std::shared_ptr<ProgramDesc> to_predict_program_; std::shared_ptr<ProgramDesc> to_predict_program_;
void predict(const Tensor &t, int block_id); void predict(const Tensor &t, int block_id);
std::map<framework::BlockDesc, std::map<framework::BlockDesc,
std::vector<std::shared_ptr<OperatorBase<Dtype>>>> std::vector<std::shared_ptr<OperatorBase<Dtype>>>>
ops_of_block_; ops_of_block_;
bool use_optimize_ = false; bool use_optimize_ = false;
}; };
} // namespace framework } // namespace framework
......
src/framework/framework.pb.cpp
浏览文件 @ 1ad8f821
此差异已折叠。
src/framework/framework.pb.h
浏览文件 @ 1ad8f821
此差异已折叠。
src/framework/lod_tensor.cc
浏览文件 @ 1ad8f821
...@@ -22,291 +22,289 @@ namespace paddle_mobile { ...@@ -22,291 +22,289 @@ namespace paddle_mobile {
namespace framework { namespace framework {
std::ostream &operator<<(std::ostream &os, const LoD &lod) { std::ostream &operator<<(std::ostream &os, const LoD &lod) {
os << "{";
for (auto &v : lod) {
os << "{"; os << "{";
for (auto &v : lod) { bool is_first = true;
os << "{"; for (auto &i : v) {
bool is_first = true; if (is_first) {
for (auto &i : v) { os << i;
if (is_first) { is_first = false;
os << i; } else {
is_first = false; os << ", " << i;
} else { }
os << ", " << i;
}
}
os << "}";
} }
os << "}"; os << "}";
}
os << "}";
return os; return os;
} }
std::ostream &operator<<(std::ostream &os, const LoDTensor &t) { std::ostream &operator<<(std::ostream &os, const LoDTensor &t) {
// PADDLE_ENFORCE(t.type().hash_code() == // PADDLE_ENFORCE(t.type().hash_code() ==
// typeid(float).hash_code()); // typeid(float).hash_code());
// if (!platform::is_cpu_place(t.place())) { // if (!platform::is_cpu_place(t.place())) {
// LoDTensor tt; // LoDTensor tt;
// framework::TensorCopy(t, platform::CPUPlace(), &tt); // framework::TensorCopy(t, platform::CPUPlace(), &tt);
// platform::DeviceContextPool &pool = // platform::DeviceContextPool &pool =
// platform::DeviceContextPool::Instance(); auto &dev_ctx = // platform::DeviceContextPool::Instance(); auto &dev_ctx =
// *pool.Get(t.place()); dev_ctx.Wait(); // *pool.Get(t.place()); dev_ctx.Wait();
// //
// os << tt; // os << tt;
// return os; // return os;
// } // }
os << "dim: " << t.dims() << "\n"; os << "dim: " << t.dims() << "\n";
os << "lod: " << t.lod() << "\n"; os << "lod: " << t.lod() << "\n";
// only print first ten elements // only print first ten elements
int64_t size = t.numel() < 10 ? t.numel() : 10; int64_t size = t.numel() < 10 ? t.numel() : 10;
for (int64_t i = 0; i < size; ++i) { for (int64_t i = 0; i < size; ++i) {
os << t.data<float>()[i] << " "; os << t.data<float>()[i] << " ";
} }
return os; return os;
} }
std::string LoDToString(const LoD &lod) { std::string LoDToString(const LoD &lod) {
std::ostringstream stream; std::ostringstream stream;
stream << lod; stream << lod;
return stream.str(); return stream.str();
} }
LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin, LoD SliceInLevel(const LoD &in, size_t level, size_t elem_begin,
size_t elem_end) { size_t elem_end) {
// PADDLE_ENFORCE_LT(level, in.size()); // PADDLE_ENFORCE_LT(level, in.size());
// PADDLE_ENFORCE_LT(elem_end, in[level].size()); // PADDLE_ENFORCE_LT(elem_end, in[level].size());
LoD res; LoD res;
res.resize(in.size() - level); res.resize(in.size() - level);
// copy the first level // copy the first level
res[0].assign(in[level].begin() + elem_begin, res[0].assign(in[level].begin() + elem_begin,
in[level].begin() + elem_end + 1); in[level].begin() + elem_end + 1);
for (size_t lvl = 1; lvl < res.size(); lvl++) { for (size_t lvl = 1; lvl < res.size(); lvl++) {
const auto &in_level = in[level + lvl]; const auto &in_level = in[level + lvl];
const auto &above_level = res[lvl - 1]; const auto &above_level = res[lvl - 1];
auto &out_level = res[lvl]; auto &out_level = res[lvl];
out_level.assign(in_level.begin() + above_level.front(), out_level.assign(in_level.begin() + above_level.front(),
in_level.begin() + above_level.back() + 1); in_level.begin() + above_level.back() + 1);
} }
for (size_t lvl = 0; lvl < res.size(); lvl++) { for (size_t lvl = 0; lvl < res.size(); lvl++) {
// to make the first offset equals 0, all the elements minus the // to make the first offset equals 0, all the elements minus the
// first // first
// element // element
size_t front = res[lvl].front(); size_t front = res[lvl].front();
for (auto &ele : res[lvl]) { for (auto &ele : res[lvl]) {
ele -= front; ele -= front;
}
} }
return res; }
return res;
} }
LoD ToAbsOffset(const LoD &in) { LoD ToAbsOffset(const LoD &in) {
// the lowest level stores relative offsets // the lowest level stores relative offsets
if (in.empty() || in.size() == 1) if (in.empty() || in.size() == 1)
return in; return in;
LoD result = in; LoD result = in;
for (auto level = static_cast<int>(in.size() - 2); level >= 0; level--) { for (auto level = static_cast<int>(in.size() - 2); level >= 0; level--) {
for (size_t i = 0; i < in[level].size(); ++i) { for (size_t i = 0; i < in[level].size(); ++i) {
size_t index = in[level][i]; size_t index = in[level][i];
result[level][i] = result[level + 1][index]; result[level][i] = result[level + 1][index];
}
} }
return result; }
return result;
} }
bool operator==(const LoD &a, const LoD &b) { bool operator==(const LoD &a, const LoD &b) {
if (a.size() != b.size()) { if (a.size() != b.size()) {
return false; return false;
}
for (size_t i = 0; i < a.size(); i++) {
const auto &a_level = a[i];
const auto &b_level = b[i];
if (a_level.size() != b_level.size()) {
return false;
} }
for (size_t j = 0; j < a_level.size(); j++) {
for (size_t i = 0; i < a.size(); i++) { if (a_level[j] != b_level[j]) {
const auto &a_level = a[i]; return false;
const auto &b_level = b[i]; }
if (a_level.size() != b_level.size()) {
return false;
}
for (size_t j = 0; j < a_level.size(); j++) {
if (a_level[j] != b_level[j]) {
return false;
}
}
} }
return true; }
return true;
} }
bool CheckLoD(const LoD &in, int tensor_height) { bool CheckLoD(const LoD &in, int tensor_height) {
if (in.empty()) 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;
// check: the first offset(the begin offset) of each level
// should be 0.
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;
return false;
})) {
std::cout << "ascending error";
return false;
}
}
// check: the lowest level's last offset should equals
// `tensor_height` if
// tensor_height>0.
if (tensor_height > 0 && (size_t)tensor_height != in.back().back())
return false;
// check: the higher level's last offset should equals the lower
// level's
// size-1.
// NOTE LoD store the levels from top to bottom, so the higher level
// goes
// first.
for (size_t level = 0; level < in.size() - 1; level++) {
if (in[level].back() != in[level + 1].size() - 1)
return false;
}
return true; 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;
// check: the first offset(the begin offset) of each level
// should be 0.
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;
return false;
})) {
std::cout << "ascending error";
return false;
}
}
// check: the lowest level's last offset should equals
// `tensor_height` if
// tensor_height>0.
if (tensor_height > 0 && (size_t)tensor_height != in.back().back())
return false;
// check: the higher level's last offset should equals the lower
// level's
// size-1.
// NOTE LoD store the levels from top to bottom, so the higher level
// goes
// first.
for (size_t level = 0; level < in.size() - 1; level++) {
if (in[level].back() != in[level + 1].size() - 1)
return false;
}
return true;
} }
bool CheckAbsLoD(const LoD &in, int tensor_height) { bool CheckAbsLoD(const LoD &in, int tensor_height) {
if (in.empty()) 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;
return false;
})) {
return false;
}
// check: there should be more than 2 offsets existing in each
// level.
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 (tensor_height < 0) {
tensor_height = level.back();
} else if ((size_t)tensor_height != level.back()) {
return false;
}
}
return true; 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;
return false;
})) {
return false;
}
// check: there should be more than 2 offsets existing in each
// level.
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 (tensor_height < 0) {
tensor_height = level.back();
} else if ((size_t)tensor_height != level.back()) {
return false;
}
}
return true;
} }
using LoDAndOffset = std::pair<LoD, std::pair<size_t, size_t>>; using LoDAndOffset = std::pair<LoD, std::pair<size_t, size_t>>;
LoDAndOffset GetSubLoDAndAbsoluteOffset(const LoD &lod, size_t start_idx, LoDAndOffset GetSubLoDAndAbsoluteOffset(const LoD &lod, size_t start_idx,
size_t end_idx, size_t start_level) { size_t end_idx, size_t start_level) {
LoD sub_lod; LoD sub_lod;
for (size_t level_idx = start_level; level_idx < lod.size(); ++level_idx) { for (size_t level_idx = start_level; level_idx < lod.size(); ++level_idx) {
// PADDLE_ENFORCE_LE(start_idx, end_idx); // PADDLE_ENFORCE_LE(start_idx, end_idx);
// PADDLE_ENFORCE_LT(end_idx, lod[level_idx].size()); // PADDLE_ENFORCE_LT(end_idx, lod[level_idx].size());
std::vector<size_t> level_lens; std::vector<size_t> level_lens;
for (size_t i = start_idx; i < end_idx; ++i) { for (size_t i = start_idx; i < end_idx; ++i) {
level_lens.push_back(lod[level_idx][i + 1] - lod[level_idx][i]); level_lens.push_back(lod[level_idx][i + 1] - lod[level_idx][i]);
}
sub_lod.emplace_back(level_lens);
start_idx = lod[level_idx][start_idx];
end_idx = lod[level_idx][end_idx];
} }
sub_lod.emplace_back(level_lens);
start_idx = lod[level_idx][start_idx];
end_idx = lod[level_idx][end_idx];
}
return LoDAndOffset{sub_lod, {start_idx, end_idx}}; return LoDAndOffset{sub_lod, {start_idx, end_idx}};
} }
void AppendLoD(LoD *lod, const LoD &lod_length) { void AppendLoD(LoD *lod, const LoD &lod_length) {
// PADDLE_ENFORCE( // PADDLE_ENFORCE(
// lod->empty() || lod->size() == lod_length.size(), // lod->empty() || lod->size() == lod_length.size(),
// "The lod_length should has the same size with the appended // "The lod_length should has the same size with the appended
// lod."); // lod.");
if (lod->empty()) { if (lod->empty()) {
for (size_t i = 0; i < lod_length.size(); ++i) { for (size_t i = 0; i < lod_length.size(); ++i) {
lod->emplace_back(1, 0); // size = 1, value = 0; lod->emplace_back(1, 0); // size = 1, value = 0;
}
*lod = LoD(lod_length.size(), std::vector<size_t>({0}));
} }
for (size_t i = 0; i < lod->size(); ++i) { *lod = LoD(lod_length.size(), std::vector<size_t>({0}));
auto &level = (*lod)[i]; }
for (size_t len : lod_length[i]) { for (size_t i = 0; i < lod->size(); ++i) {
level.push_back(level.back() + len); auto &level = (*lod)[i];
} for (size_t len : lod_length[i]) {
level.push_back(level.back() + len);
} }
}
} }
void SerializeToStream(std::ostream &os, const LoDTensor &tensor) { void SerializeToStream(std::ostream &os, const LoDTensor &tensor) {
{ // the 1st field, uint32_t version for LoDTensor { // the 1st field, uint32_t version for LoDTensor
constexpr uint32_t version = 0; constexpr uint32_t version = 0;
os.write(reinterpret_cast<const char *>(&version), sizeof(version)); os.write(reinterpret_cast<const char *>(&version), sizeof(version));
}
{
// the 2st field, LoD information
// uint64_t lod_level
// uint64_t lod_level_1 size in byte.
// int* lod_level_1 data
// ...
auto lod = tensor.lod();
uint64_t size = lod.size();
os.write(reinterpret_cast<const char *>(&size), sizeof(size));
for (auto &each : lod) {
size = each.size() * sizeof(framework::LoD::value_type::value_type);
os.write(reinterpret_cast<const char *>(&size), sizeof(size));
os.write(reinterpret_cast<const char *>(each.data()),
static_cast<std::streamsize>(size));
} }
{ }
// the 2st field, LoD information // the 3st field, Tensor
// uint64_t lod_level TensorToStream(os, static_cast<Tensor>(tensor));
// uint64_t lod_level_1 size in byte.
// int* lod_level_1 data
// ...
auto lod = tensor.lod();
uint64_t size = lod.size();
os.write(reinterpret_cast<const char *>(&size), sizeof(size));
for (auto &each : lod) {
size = each.size() * sizeof(framework::LoD::value_type::value_type);
os.write(reinterpret_cast<const char *>(&size), sizeof(size));
os.write(reinterpret_cast<const char *>(each.data()),
static_cast<std::streamsize>(size));
}
}
// the 3st field, Tensor
TensorToStream(os, static_cast<Tensor>(tensor));
} }
void DeserializeFromStream(std::istream &is, LoDTensor *tensor) { void DeserializeFromStream(std::istream &is, LoDTensor *tensor) {
{ {
// the 1st field, unit32_t version for LoDTensor // the 1st field, unit32_t version for LoDTensor
uint32_t version; uint32_t version;
is.read(reinterpret_cast<char *>(&version), sizeof(version)); is.read(reinterpret_cast<char *>(&version), sizeof(version));
// PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is // PADDLE_ENFORCE_EQ(version, 0U, "Only version 0 is
// supported"); // supported");
} }
{ {
// the 2st field, LoD information // the 2st field, LoD information
uint64_t lod_level; uint64_t lod_level;
is.read(reinterpret_cast<char *>(&lod_level), sizeof(lod_level)); is.read(reinterpret_cast<char *>(&lod_level), sizeof(lod_level));
auto &lod = *tensor->mutable_lod(); auto &lod = *tensor->mutable_lod();
lod.resize(lod_level); lod.resize(lod_level);
for (uint64_t i = 0; i < lod_level; ++i) { for (uint64_t i = 0; i < lod_level; ++i) {
uint64_t size; uint64_t size;
is.read(reinterpret_cast<char *>(&size), sizeof(size)); is.read(reinterpret_cast<char *>(&size), sizeof(size));
std::vector<size_t> tmp(size / sizeof(size_t)); std::vector<size_t> tmp(size / sizeof(size_t));
is.read(reinterpret_cast<char *>(tmp.data()), is.read(reinterpret_cast<char *>(tmp.data()),
static_cast<std::streamsize>(size)); static_cast<std::streamsize>(size));
lod[i] = tmp; lod[i] = tmp;
}
} }
// the 3st filed, Tensor }
TensorFromStream(is, static_cast<Tensor *>(tensor)); // the 3st filed, Tensor
TensorFromStream(is, static_cast<Tensor *>(tensor));
} }
} // namespace framework } // namespace framework
......
src/framework/lod_tensor.h
浏览文件 @ 1ad8f821
...@@ -102,45 +102,45 @@ bool CheckAbsLoD(const LoD &in, int tensor_height = -1); ...@@ -102,45 +102,45 @@ bool CheckAbsLoD(const LoD &in, int tensor_height = -1);
* see https://en.wikipedia.org/wiki/Level_of_details for reference. * see https://en.wikipedia.org/wiki/Level_of_details for reference.
*/ */
class LoDTensor : public Tensor { class LoDTensor : public Tensor {
public: public:
LoDTensor() : Tensor() {} LoDTensor() : Tensor() {}
explicit LoDTensor(const LoD &lod) : lod_(lod) {} explicit LoDTensor(const LoD &lod) : lod_(lod) {}
void set_lod(const LoD &lod) { lod_ = lod; } void set_lod(const LoD &lod) { lod_ = lod; }
const LoD &lod() const { return lod_; } const LoD &lod() const { return lod_; }
LoD *mutable_lod() { return &lod_; } LoD *mutable_lod() { return &lod_; }
/* /*
* Get the start offset and end offset of an element from 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 { std::pair<size_t, size_t> lod_element(size_t level, size_t elem) const {
// PADDLE_ENFORCE_LT(level, NumLevels()); // PADDLE_ENFORCE_LT(level, NumLevels());
// PADDLE_ENFORCE_LT(elem, NumElements(level)); // PADDLE_ENFORCE_LT(elem, NumElements(level));
return std::make_pair((lod_)[level][elem], (lod_)[level][elem + 1]); return std::make_pair((lod_)[level][elem], (lod_)[level][elem + 1]);
} }
/* /*
* Number of LoDTensor's levels, each level has units of data, for * Number of LoDTensor's levels, each level has units of data, for
* example, * example,
* in the sentence's view, article, paragraph, sentence are 3 * in the sentence's view, article, paragraph, sentence are 3
* levels. * levels.
*/ */
size_t NumLevels() const { return lod_.size(); } size_t NumLevels() const { return lod_.size(); }
/* /*
* Number of elements in a level. * Number of elements in a level.
*/ */
size_t NumElements(size_t level = 0) const { size_t NumElements(size_t level = 0) const {
// PADDLE_ENFORCE_LT(level, NumLevels()); // PADDLE_ENFORCE_LT(level, NumLevels());
// the last offset is the end of last element // the last offset is the end of last element
return (lod_)[level].size() - 1; return (lod_)[level].size() - 1;
} }
private: private:
LoD lod_; LoD lod_;
}; };
/* /*
...@@ -155,26 +155,26 @@ class LoDTensor : public Tensor { ...@@ -155,26 +155,26 @@ class LoDTensor : public Tensor {
*/ */
template <typename T> template <typename T>
LoDTensor LodExpand(const LoDTensor &source, const LoD &lod, size_t level) { LoDTensor LodExpand(const LoDTensor &source, const LoD &lod, size_t level) {
LoD abs_lod = ToAbsOffset(lod); LoD abs_lod = ToAbsOffset(lod);
const auto &lod_level = lod[level]; const auto &lod_level = lod[level];
size_t num_instances = source.dims()[0]; size_t num_instances = source.dims()[0];
// new tensor // new tensor
LoDTensor tensor; LoDTensor tensor;
tensor.set_lod(lod); tensor.set_lod(lod);
auto dims = source.dims(); auto dims = source.dims();
dims[0] = lod_level.back(); dims[0] = lod_level.back();
tensor.Resize(dims); tensor.Resize(dims);
tensor.mutable_data<T>(); tensor.mutable_data<T>();
// PADDLE_ENFORCE_EQ(num_instances, lod_level.size() - 1); // PADDLE_ENFORCE_EQ(num_instances, lod_level.size() - 1);
for (size_t ins = 0; ins < num_instances; ins++) { for (size_t ins = 0; ins < num_instances; ins++) {
for (size_t elem = lod_level[ins]; elem < lod_level[ins + 1]; elem++) { for (size_t elem = lod_level[ins]; elem < lod_level[ins + 1]; elem++) {
auto slice = tensor.Slice(elem, elem + 1); auto slice = tensor.Slice(elem, elem + 1);
TensorCopy(source.Slice(ins, ins + 1), &slice); TensorCopy(source.Slice(ins, ins + 1), &slice);
}
} }
return tensor; }
return tensor;
} }
// Get the absolute offset of a lod[start_level][start_idx:end_idx] and // Get the absolute offset of a lod[start_level][start_idx:end_idx] and
......
src/framework/op_desc.cpp
浏览文件 @ 1ad8f821
...@@ -8,51 +8,51 @@ namespace paddle_mobile { ...@@ -8,51 +8,51 @@ namespace paddle_mobile {
namespace framework { namespace framework {
OpDesc::OpDesc(const proto::OpDesc &desc) : desc_(desc) { OpDesc::OpDesc(const proto::OpDesc &desc) : desc_(desc) {
for (int i = 0; i < desc_.inputs_size(); ++i) { for (int i = 0; i < desc_.inputs_size(); ++i) {
const proto::OpDesc::Var &var = desc_.inputs(i); const proto::OpDesc::Var &var = desc_.inputs(i);
std::vector<std::string> &args = inputs_[var.parameter()]; std::vector<std::string> &args = inputs_[var.parameter()];
int arg_size = var.arguments_size(); int arg_size = var.arguments_size();
for (int j = 0; j < arg_size; ++j) { for (int j = 0; j < arg_size; ++j) {
args.push_back(var.arguments(j)); args.push_back(var.arguments(j));
}
} }
}
for (int i = 0; i < desc_.outputs_size(); ++i) {
const proto::OpDesc::Var &var = desc_.outputs(i); for (int i = 0; i < desc_.outputs_size(); ++i) {
std::vector<std::string> &args = outputs_[var.parameter()]; const proto::OpDesc::Var &var = desc_.outputs(i);
int arg_size = var.arguments_size(); std::vector<std::string> &args = outputs_[var.parameter()];
for (int j = 0; j < arg_size; ++j) { int arg_size = var.arguments_size();
args.push_back(var.arguments(j)); 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(); for (const proto::OpDesc::Attr &attr : desc_.attrs()) {
if (attr.type() != proto::AttrType::BLOCK) { std::string attr_name = attr.name();
attrs_[attr_name] = Attribute::GetAttrValue(attr); if (attr.type() != proto::AttrType::BLOCK) {
// if (attr.type() == proto::AttrType::INT){ attrs_[attr_name] = Attribute::GetAttrValue(attr);
// std::cout << " attrName " << attr_name << " " << // if (attr.type() == proto::AttrType::INT){
// attrs_[attr_name].Get<int>() << std::endl; // std::cout << " attrName " << attr_name << " " <<
// } // attrs_[attr_name].Get<int>() << std::endl;
} // }
} }
}
} }
const std::vector<std::string> &OpDesc::Input(const std::string &name) const { const std::vector<std::string> &OpDesc::Input(const std::string &name) const {
return inputs_.find(name)->second; return inputs_.find(name)->second;
} }
const std::vector<std::string> &OpDesc::Output(const std::string &name) const { const std::vector<std::string> &OpDesc::Output(const std::string &name) const {
return outputs_.find(name)->second; return outputs_.find(name)->second;
} }
Attribute OpDesc::GetAttr(const std::string &name) const { Attribute OpDesc::GetAttr(const std::string &name) const {
auto it = attrs_.find(name); auto it = attrs_.find(name);
return it->second; return it->second;
} }
const std::unordered_map<std::string, Attribute> &OpDesc::GetAttrMap() const { const std::unordered_map<std::string, Attribute> &OpDesc::GetAttrMap() const {
return attrs_; return attrs_;
} }
} // namespace framework } // namespace framework
......
src/framework/op_desc.h
浏览文件 @ 1ad8f821
...@@ -26,25 +26,25 @@ namespace paddle_mobile { ...@@ -26,25 +26,25 @@ namespace paddle_mobile {
namespace framework { namespace framework {
class OpDesc : PaddleMobileObject { class OpDesc : PaddleMobileObject {
public: public:
OpDesc(const proto::OpDesc &desc); OpDesc(const proto::OpDesc &desc);
const std::vector<std::string> &Input(const std::string &name) const; const std::vector<std::string> &Input(const std::string &name) const;
const std::vector<std::string> &Output(const std::string &name) const; const std::vector<std::string> &Output(const std::string &name) const;
Attribute GetAttr(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: private:
proto::OpDesc desc_; proto::OpDesc desc_;
VariableNameMap inputs_; VariableNameMap inputs_;
VariableNameMap outputs_; VariableNameMap outputs_;
AttributeMap attrs_; AttributeMap attrs_;
}; };
} // namespace framework } // namespace framework
......
src/framework/op_info.h
浏览文件 @ 1ad8f821
...@@ -25,13 +25,13 @@ namespace paddle_mobile { ...@@ -25,13 +25,13 @@ namespace paddle_mobile {
namespace framework { namespace framework {
template <typename Dtype> struct OpInfo { template <typename Dtype> struct OpInfo {
OpCreator<Dtype> creator_; OpCreator<Dtype> creator_;
const OpCreator<Dtype> &Creator() const { const OpCreator<Dtype> &Creator() const {
// PADDLE_ENFORCE_NOT_NULL(creator_, // PADDLE_ENFORCE_NOT_NULL(creator_,
// "Operator Creator has not been // "Operator Creator has not been
// registered"); // registered");
return creator_; return creator_;
} }
}; };
template <typename Dtype> class OpInfoMap; template <typename Dtype> class OpInfoMap;
...@@ -39,55 +39,55 @@ template <typename Dtype> class OpInfoMap; ...@@ -39,55 +39,55 @@ 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 { template <typename Dtype> class OpInfoMap {
public: public:
static OpInfoMap &Instance() { static OpInfoMap &Instance() {
if (g_op_info_map<Dtype> == nullptr) { if (g_op_info_map<Dtype> == nullptr) {
g_op_info_map<Dtype> = new OpInfoMap(); 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;
} }
return *g_op_info_map<Dtype>;
const OpInfo<Dtype> *GetNullable(const std::string &type) const { };
auto it = map_.find(type);
if (it == map_.end()) { bool Has(const std::string &op_type) const {
return nullptr; return map_.find(op_type) != map_.end();
} else { }
return &it->second;
} 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 { const std::unordered_map<std::string, OpInfo<Dtype>> &map() const {
return map_; return map_;
} }
std::unordered_map<std::string, OpInfo<Dtype>> *mutable_map() { std::unordered_map<std::string, OpInfo<Dtype>> *mutable_map() {
return &map_; return &map_;
} }
private: private:
OpInfoMap() = default; OpInfoMap() = default;
std::unordered_map<std::string, OpInfo<Dtype>> map_; std::unordered_map<std::string, OpInfo<Dtype>> map_;
// DISABLE_COPY_AND_ASSIGN(OpInfoMap); // DISABLE_COPY_AND_ASSIGN(OpInfoMap);
}; };
} // namespace framework } // namespace framework
......
src/framework/op_kernel_type.h
浏览文件 @ 1ad8f821
...@@ -24,41 +24,40 @@ SOFTWARE. ...@@ -24,41 +24,40 @@ SOFTWARE.
namespace paddle_mobile { namespace paddle_mobile {
namespace framework { namespace framework {
struct OpKernelType { struct OpKernelType {
struct Hash { struct Hash {
size_t operator()(const OpKernelType &key) const { size_t operator()(const OpKernelType &key) const {
int data_type = static_cast<int>(key.data_type_) << LEFT_SHIFT; int data_type = static_cast<int>(key.data_type_) << LEFT_SHIFT;
int data_layout = static_cast<int>(key.data_layout_) int data_layout = static_cast<int>(key.data_layout_) << (LEFT_SHIFT * 2);
<< (LEFT_SHIFT * 2);
std::hash<int> hasher; std::hash<int> hasher;
return hasher(data_type + data_layout); return hasher(data_type + data_layout);
} }
}; };
// place, data_type, library_type kinds less than 2^8 // place, data_type, library_type kinds less than 2^8
constexpr static int LEFT_SHIFT = 8; constexpr static int LEFT_SHIFT = 8;
proto::VarType::Type data_type_; proto::VarType::Type data_type_;
DataLayout data_layout_; DataLayout data_layout_;
OpKernelType(proto::VarType::Type data_type, OpKernelType(proto::VarType::Type data_type,
DataLayout data_layout = DataLayout::kAnyLayout) DataLayout data_layout = DataLayout::kAnyLayout)
: data_type_(data_type), data_layout_(data_layout) {} : data_type_(data_type), data_layout_(data_layout) {}
bool operator==(const OpKernelType &o) const { bool operator==(const OpKernelType &o) const {
return data_type_ == o.data_type_ && data_layout_ == o.data_layout_; 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) { inline bool NeedTransformLayout(const DataLayout &l, const DataLayout &r) {
return l != DataLayout::kAnyLayout && r != DataLayout::kAnyLayout && l != r; return l != DataLayout::kAnyLayout && r != DataLayout::kAnyLayout && l != r;
} }
inline bool TransFromNeeded(const OpKernelType &l, const OpKernelType &r) { inline bool TransFromNeeded(const OpKernelType &l, const OpKernelType &r) {
return (l.data_type_ != r.data_type_) || return (l.data_type_ != r.data_type_) ||
NeedTransformLayout(l.data_layout_, r.data_layout_); NeedTransformLayout(l.data_layout_, r.data_layout_);
} }
} // namespace framework } // namespace framework
......
src/framework/operator.cpp
浏览文件 @ 1ad8f821
...@@ -30,7 +30,7 @@ OperatorBase<Dtype>::OperatorBase(const std::string &type, ...@@ -30,7 +30,7 @@ OperatorBase<Dtype>::OperatorBase(const std::string &type,
std::shared_ptr<Scope> scope) std::shared_ptr<Scope> scope)
: type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs), : type_(type), inputs_(inputs), outputs_(outputs), attrs_(attrs),
scope_(scope) { scope_(scope) {
CheckAllInputOutputSet(); CheckAllInputOutputSet();
} }
template <typename Dtype> template <typename Dtype>
void OperatorBase<Dtype>::CheckAllInputOutputSet() const {} void OperatorBase<Dtype>::CheckAllInputOutputSet() const {}
......
src/framework/operator.h
浏览文件 @ 1ad8f821
...@@ -49,50 +49,50 @@ static std::unordered_map< ...@@ -49,50 +49,50 @@ static std::unordered_map<
{"fetch", {{"X"}, {"Out"}}}}; {"fetch", {{"X"}, {"Out"}}}};
template <typename Dtype> class OperatorBase : PaddleMobileObject { template <typename Dtype> class OperatorBase : PaddleMobileObject {
public: public:
OperatorBase(const std::string &type, const VariableNameMap &inputs, OperatorBase(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const AttributeMap &attrs, const VariableNameMap &outputs, const AttributeMap &attrs,
std::shared_ptr<Scope> scope); std::shared_ptr<Scope> scope);
virtual ~OperatorBase() {} virtual ~OperatorBase() {}
virtual void Run() const = 0; virtual void Run() const = 0;
const VariableNameMap &Inputs() const { return inputs_; } const VariableNameMap &Inputs() const { return inputs_; }
const VariableNameMap &Outputs() const { return outputs_; } const VariableNameMap &Outputs() const { return outputs_; }
const std::string &Type() const { return type_; } const std::string &Type() const { return type_; }
const AttributeMap &Attrs() const { return attrs_; } const AttributeMap &Attrs() const { return attrs_; }
void ClearVariables(const std::vector<std::string> &var_names) const { void ClearVariables(const std::vector<std::string> &var_names) const {
if (this->scope_) { if (this->scope_) {
this->scope_->EraseVars(var_names); this->scope_->EraseVars(var_names);
}
} }
}
protected: protected:
std::shared_ptr<Scope> scope_; std::shared_ptr<Scope> scope_;
std::string type_; std::string type_;
VariableNameMap inputs_; VariableNameMap inputs_;
VariableNameMap outputs_; VariableNameMap outputs_;
AttributeMap attrs_; AttributeMap attrs_;
private: private:
void CheckAllInputOutputSet() const; void CheckAllInputOutputSet() const;
}; };
template <typename Dtype> template <typename Dtype>
class OperatorWithKernel : public OperatorBase<Dtype> { class OperatorWithKernel : public OperatorBase<Dtype> {
public: public:
OperatorWithKernel(const std::string &type, const VariableNameMap &inputs, OperatorWithKernel(const std::string &type, const VariableNameMap &inputs,
const VariableNameMap &outputs, const VariableNameMap &outputs, const AttributeMap &attrs,
const AttributeMap &attrs, std::shared_ptr<Scope> scope) std::shared_ptr<Scope> scope)
: OperatorBase<Dtype>(type, inputs, outputs, attrs, scope) {} : OperatorBase<Dtype>(type, inputs, outputs, attrs, scope) {}
virtual void InferShape() const = 0; virtual void InferShape() const = 0;
virtual void Run() const = 0; virtual void Run() const = 0;
}; };
template <typename Dtype, typename P> class OpKernelBase : PaddleMobileObject { template <typename Dtype, typename P> class OpKernelBase : PaddleMobileObject {
public: public:
virtual void Compute(const P &para) const = 0; virtual void Compute(const P &para) const = 0;
virtual ~OpKernelBase() = default; virtual ~OpKernelBase() = default;
}; };
} // namespace framework } // namespace framework
......
src/framework/paddle_mobile_object.h
浏览文件 @ 1ad8f821
...@@ -24,13 +24,13 @@ SOFTWARE. ...@@ -24,13 +24,13 @@ SOFTWARE.
namespace paddle_mobile { namespace paddle_mobile {
class PaddleMobileObject { class PaddleMobileObject {
public: public:
virtual std::string ToString() { virtual std::string ToString() {
char address[128] = {0}; char address[128] = {0};
sprintf(address, "%p", this); sprintf(address, "%p", this);
return std::string(address); return std::string(address);
} }
private: private:
}; };
} // namespace paddle_mobile } // namespace paddle_mobile
src/framework/program-optimize/node.cpp
浏览文件 @ 1ad8f821
...@@ -25,71 +25,71 @@ namespace paddle_mobile { ...@@ -25,71 +25,71 @@ namespace paddle_mobile {
namespace framework { namespace framework {
Node &Node::operator>(std::shared_ptr<Node> node) { Node &Node::operator>(std::shared_ptr<Node> node) {
outputs_.push_back(node); outputs_.push_back(node);
std::shared_ptr<Node> this_node; std::shared_ptr<Node> this_node;
node->inputs_.push_back(this); node->inputs_.push_back(this);
return *node; return *node;
} }
bool Node::operator==(const Node &in) { bool Node::operator==(const Node &in) {
if (in.type_ == this->type_) { if (in.type_ == this->type_) {
if (this->outputs_.size() == in.outputs_.size()) { if (this->outputs_.size() == in.outputs_.size()) {
for (int i = 0; i < outputs_.size(); ++i) { for (int i = 0; i < outputs_.size(); ++i) {
if (!(*outputs_[i] == *in.outputs_[i])) { if (!(*outputs_[i] == *in.outputs_[i])) {
return false; return false;
}
}
} else {
return false;
} }
}
} else { } else {
return false; return false;
} }
return true; } else {
return false;
}
return true;
} }
std::string Node::ToString(std::string blank, const Node *node) const { std::string Node::ToString(std::string blank, const Node *node) const {
std::stringstream ss; std::stringstream ss;
ss << type_ << "-> \n"; ss << type_ << "-> \n";
if (inputs_.size() > 1 && node != inputs_.back()) { if (inputs_.size() > 1 && node != inputs_.back()) {
return ss.str();
} else if (inputs_.size() > 1 && node == inputs_.back()) {
ss << "\n" << blank << type_ << "\n";
}
for (int i = 0; i < outputs_.size(); ++i) {
ss << blank << outputs_[i]->ToString(blank + " ", this) << "";
}
return ss.str(); return ss.str();
} else if (inputs_.size() > 1 && node == inputs_.back()) {
ss << "\n" << blank << type_ << "\n";
}
for (int i = 0; i < outputs_.size(); ++i) {
ss << blank << outputs_[i]->ToString(blank + " ", this) << "";
}
return ss.str();
} }
std::string Node::ToString() const { return this->ToString(" ", this); } std::string Node::ToString() const { return this->ToString(" ", this); }
Node &Node::To(int index) { Node &Node::To(int index) {
if (index == 0) { if (index == 0) {
this->outputs_.clear(); this->outputs_.clear();
} }
for (int j = 0; j < this->outputs_.size(); ++j) { for (int j = 0; j < this->outputs_.size(); ++j) {
outputs_[j]->To(index - 1); outputs_[j]->To(index - 1);
} }
return *this; return *this;
} }
uint Node::depth(uint begin) { uint Node::depth(uint begin) {
uint depth = 0; uint depth = 0;
begin++; begin++;
for (int i = 0; i < outputs_.size(); ++i) { for (int i = 0; i < outputs_.size(); ++i) {
uint output_depth = outputs_[i]->depth(begin); uint output_depth = outputs_[i]->depth(begin);
depth = output_depth > depth ? output_depth : depth; depth = output_depth > depth ? output_depth : depth;
} }
return begin > depth ? begin : depth; return begin > depth ? begin : depth;
} }
Print &operator<<(Print &printer, const Node &node) { Print &operator<<(Print &printer, const Node &node) {
printer << node.ToString(); printer << node.ToString();
return printer; return printer;
} }
} // namespace framework } // namespace framework
......
src/framework/program-optimize/node.h
浏览文件 @ 1ad8f821
...@@ -29,22 +29,22 @@ namespace paddle_mobile { ...@@ -29,22 +29,22 @@ namespace paddle_mobile {
namespace framework { namespace framework {
class Node : PaddleMobileObject { class Node : PaddleMobileObject {
public: public:
Node(const std::string &type) : type_(type) {} Node(const std::string &type) : type_(type) {}
Node(std::shared_ptr<OpDesc> op_desc) Node(std::shared_ptr<OpDesc> op_desc)
: op_desc_(op_desc), type_(op_desc->Type()){}; : op_desc_(op_desc), type_(op_desc->Type()){};
Node &operator>(std::shared_ptr<Node> node); Node &operator>(std::shared_ptr<Node> node);
bool operator==(const Node &in); bool operator==(const Node &in);
std::string ToString() const; std::string ToString() const;
Node &To(int index); Node &To(int index);
uint depth(uint begin = 0); uint depth(uint begin = 0);
private: private:
std::shared_ptr<OpDesc> op_desc_; std::shared_ptr<OpDesc> op_desc_;
std::string ToString(std::string blank, const Node *node) const; std::string ToString(std::string blank, const Node *node) const;
std::vector<std::shared_ptr<Node>> outputs_; std::vector<std::shared_ptr<Node>> outputs_;
std::vector<Node *> inputs_; std::vector<Node *> inputs_;
std::string type_; std::string type_;
}; };
Print &operator<<(Print &printer, const Node &node); Print &operator<<(Print &printer, const Node &node);
......
src/framework/program-optimize/program_optimize.cpp
浏览文件 @ 1ad8f821
...@@ -26,49 +26,48 @@ std::shared_ptr<ProgramDesc> ProgramOptimize::Optimize() {} ...@@ -26,49 +26,48 @@ std::shared_ptr<ProgramDesc> ProgramOptimize::Optimize() {}
std::shared_ptr<ProgramDesc> std::shared_ptr<ProgramDesc>
ProgramOptimize::FushionOptimize(std::shared_ptr<ProgramDesc> ori_des) { ProgramOptimize::FushionOptimize(std::shared_ptr<ProgramDesc> ori_des) {
for (int i = 0; i < ori_des->Blocks().size(); ++i) { for (int i = 0; i < ori_des->Blocks().size(); ++i) {
std::unordered_map<std::string, std::shared_ptr<Node>> output_nodes; std::unordered_map<std::string, std::shared_ptr<Node>> output_nodes;
std::shared_ptr<Node> begin_node; std::shared_ptr<Node> begin_node;
auto block = ori_des->Block(i); auto block = ori_des->Block(i);
// DLOG << " ops size: " << block->Ops().size(); // DLOG << " ops size: " << block->Ops().size();
for (int j = 0; j < block->Ops().size(); ++j) { for (int j = 0; j < block->Ops().size(); ++j) {
auto op = block->Ops()[j]; auto op = block->Ops()[j];
auto op_type = op->Type(); auto op_type = op->Type();
// DLOG << "op type: " << op_type << " index: " << j; // DLOG << "op type: " << op_type << " index: " << j;
if (op_input_output_key.find(op->Type()) == if (op_input_output_key.find(op->Type()) == op_input_output_key.end()) {
op_input_output_key.end()) { return NULL;
return NULL; }
}
std::shared_ptr<Node> node = std::make_shared<Node>(op); std::shared_ptr<Node> node = std::make_shared<Node>(op);
if (j == 0) { if (j == 0) {
begin_node = node; begin_node = node;
} }
auto input_keys = op_input_output_key.at(op->Type()).first; auto input_keys = op_input_output_key.at(op->Type()).first;
for (auto input_key : input_keys) { for (auto input_key : input_keys) {
auto op_inputs = op->Input(input_key); auto op_inputs = op->Input(input_key);
for (int l = 0; l < op_inputs.size(); ++l) { for (int l = 0; l < op_inputs.size(); ++l) {
std::string input_key = op_inputs[l]; std::string input_key = op_inputs[l];
if (output_nodes.find(input_key) != output_nodes.end()) { if (output_nodes.find(input_key) != output_nodes.end()) {
auto input_node = output_nodes[input_key]; auto input_node = output_nodes[input_key];
*input_node > node; *input_node > node;
} }
}
}
auto output_keys = op_input_output_key.at(op_type).second;
for (auto output_key : output_keys) {
auto op_outputs = op->Output(output_key);
for (int k = 0; k < op_outputs.size(); ++k) {
output_nodes[op_outputs[k]] = node;
}
}
} }
}
DLOG << "node: \n" << *begin_node; auto output_keys = op_input_output_key.at(op_type).second;
for (auto output_key : output_keys) {
auto op_outputs = op->Output(output_key);
for (int k = 0; k < op_outputs.size(); ++k) {
output_nodes[op_outputs[k]] = node;
}
}
} }
return ori_des;
DLOG << "node: \n" << *begin_node;
}
return ori_des;
} }
} // namespace framework } // namespace framework
} // namespace paddle_mobile } // namespace paddle_mobile
src/framework/program-optimize/program_optimize.h
浏览文件 @ 1ad8f821
...@@ -26,16 +26,16 @@ namespace paddle_mobile { ...@@ -26,16 +26,16 @@ namespace paddle_mobile {
namespace framework { namespace framework {
class ProgramOptimize { class ProgramOptimize {
public: public:
ProgramOptimize() {} ProgramOptimize() {}
std::shared_ptr<ProgramDesc> Optimize(); std::shared_ptr<ProgramDesc> Optimize();
std::shared_ptr<ProgramDesc> std::shared_ptr<ProgramDesc>
FushionOptimize(std::shared_ptr<ProgramDesc> ori_des); FushionOptimize(std::shared_ptr<ProgramDesc> ori_des);
private: private:
// std::shared_ptr<ProgramDesc> ori_desc_; // std::shared_ptr<ProgramDesc> ori_desc_;
std::vector<std::unordered_map<std::string, std::shared_ptr<Node>>> std::vector<std::unordered_map<std::string, std::shared_ptr<Node>>>
outputs_nodes_; outputs_nodes_;
}; };
} // namespace framework } // namespace framework
} // namespace paddle_mobile } // namespace paddle_mobile
src/framework/program.h
浏览文件 @ 1ad8f821
...@@ -28,12 +28,12 @@ namespace framework { ...@@ -28,12 +28,12 @@ namespace framework {
template <typename Dtype, Precision P = Precision::FP32> template <typename Dtype, Precision P = Precision::FP32>
class Program : PaddleMobileObject { class Program : PaddleMobileObject {
public: public:
std::shared_ptr<ProgramDesc> originProgram; std::shared_ptr<ProgramDesc> originProgram;
std::shared_ptr<ProgramDesc> optimizeProgram; std::shared_ptr<ProgramDesc> optimizeProgram;
std::shared_ptr<Scope> scope; std::shared_ptr<Scope> scope;
private: private:
}; };
} // namespace framework } // namespace framework
......
src/framework/program_desc.cpp
浏览文件 @ 1ad8f821
...@@ -8,14 +8,14 @@ namespace paddle_mobile { ...@@ -8,14 +8,14 @@ namespace paddle_mobile {
namespace framework { namespace framework {
ProgramDesc::ProgramDesc(const proto::ProgramDesc &desc) : desc_(desc) { ProgramDesc::ProgramDesc(const proto::ProgramDesc &desc) : desc_(desc) {
for (auto &block_desc : *desc_.mutable_blocks()) { for (auto &block_desc : *desc_.mutable_blocks()) {
// new framework::BlockDesc(block_desc) // new framework::BlockDesc(block_desc)
blocks_.emplace_back(std::make_shared<BlockDesc>(block_desc)); blocks_.emplace_back(std::make_shared<BlockDesc>(block_desc));
} }
} }
std::shared_ptr<BlockDesc> ProgramDesc::Block(size_t idx) { std::shared_ptr<BlockDesc> ProgramDesc::Block(size_t idx) {
return blocks_[idx]; return blocks_[idx];
} }
} // namespace framework } // namespace framework
......
src/framework/program_desc.h
浏览文件 @ 1ad8f821
...@@ -28,14 +28,14 @@ namespace paddle_mobile { ...@@ -28,14 +28,14 @@ namespace paddle_mobile {
namespace framework { namespace framework {
class ProgramDesc : PaddleMobileObject { class ProgramDesc : PaddleMobileObject {
public: public:
ProgramDesc(const proto::ProgramDesc &desc); ProgramDesc(const proto::ProgramDesc &desc);
std::shared_ptr<BlockDesc> Block(size_t idx); std::shared_ptr<BlockDesc> Block(size_t idx);
const std::vector<std::shared_ptr<BlockDesc>> &Blocks() { return blocks_; }; const std::vector<std::shared_ptr<BlockDesc>> &Blocks() { return blocks_; };
private: private:
std::vector<std::shared_ptr<BlockDesc>> blocks_; std::vector<std::shared_ptr<BlockDesc>> blocks_;
proto::ProgramDesc desc_; proto::ProgramDesc desc_;
}; };
} // namespace framework } // namespace framework
......
src/framework/scope.cc
浏览文件 @ 1ad8f821
...@@ -7,20 +7,20 @@ namespace paddle_mobile { ...@@ -7,20 +7,20 @@ namespace paddle_mobile {
namespace framework { namespace framework {
Scope &Scope::NewScope() const { Scope &Scope::NewScope() const {
std::unique_lock<std::mutex> lock(mutex_); std::unique_lock<std::mutex> lock(mutex_);
kids_.push_back(new Scope(this)); kids_.push_back(new Scope(this));
return *kids_.back(); return *kids_.back();
} }
Variable *Scope::Var(const std::string &name) { Variable *Scope::Var(const std::string &name) {
auto *pvar = FindVarLocally(name); auto *pvar = FindVarLocally(name);
if (pvar != nullptr) { if (pvar != nullptr) {
return pvar;
};
pvar = new Variable;
vars_[name] = pvar;
pvar->name_ = &(vars_.find(name)->first);
return pvar; return pvar;
};
pvar = new Variable;
vars_[name] = pvar;
pvar->name_ = &(vars_.find(name)->first);
return pvar;
} }
// Variable* Scope::Var(std::string* name) { // Variable* Scope::Var(std::string* name) {
...@@ -33,70 +33,70 @@ Variable *Scope::Var(const std::string &name) { ...@@ -33,70 +33,70 @@ Variable *Scope::Var(const std::string &name) {
// } // }
Variable *Scope::FindVar(const std::string &name) const { Variable *Scope::FindVar(const std::string &name) const {
auto *pvar = FindVarLocally(name); auto *pvar = FindVarLocally(name);
if (pvar != nullptr) { if (pvar != nullptr) {
return pvar; return pvar;
} }
return (parent_ == nullptr) ? nullptr : parent_->FindVar(name); return (parent_ == nullptr) ? nullptr : parent_->FindVar(name);
} }
const Scope *Scope::FindScope(const Variable *var) const { const Scope *Scope::FindScope(const Variable *var) const {
for (auto &name_var : vars_) { for (auto &name_var : vars_) {
if (name_var.second == var) { if (name_var.second == var) {
return this; return this;
}
} }
return (parent_ == nullptr) ? nullptr : parent_->FindScope(var); }
return (parent_ == nullptr) ? nullptr : parent_->FindScope(var);
} }
void Scope::DropKids() { void Scope::DropKids() {
for (Scope *s : kids_) { for (Scope *s : kids_) {
delete s; delete s;
} }
kids_.clear(); kids_.clear();
} }
std::vector<std::string> Scope::LocalVarNames() const { std::vector<std::string> Scope::LocalVarNames() const {
std::vector<std::string> known_vars; std::vector<std::string> known_vars;
known_vars.reserve(vars_.size()); known_vars.reserve(vars_.size());
for (auto &name_var : vars_) { for (auto &name_var : vars_) {
known_vars.emplace_back(name_var.first); known_vars.emplace_back(name_var.first);
} }
return known_vars; return known_vars;
} }
void Scope::DeleteScope(Scope *scope) const { void Scope::DeleteScope(Scope *scope) const {
std::unique_lock<std::mutex> lock(mutex_); std::unique_lock<std::mutex> lock(mutex_);
auto it = std::find(kids_.begin(), kids_.end(), scope); auto it = std::find(kids_.begin(), kids_.end(), scope);
kids_.erase(it); kids_.erase(it);
delete scope; delete scope;
// deferent // deferent
} }
void Scope::EraseVars(const std::vector<std::string> &var_names) { void Scope::EraseVars(const std::vector<std::string> &var_names) {
std::set<std::string> var_set(var_names.begin(), var_names.end()); std::set<std::string> var_set(var_names.begin(), var_names.end());
for (auto it = vars_.begin(); it != vars_.end();) { for (auto it = vars_.begin(); it != vars_.end();) {
if (var_set.find(it->first) != var_set.end()) { if (var_set.find(it->first) != var_set.end()) {
delete it->second; delete it->second;
it = vars_.erase(it); it = vars_.erase(it);
} else { } else {
++it; ++it;
}
} }
}
} }
void Scope::Rename(const std::string &origin_name, void Scope::Rename(const std::string &origin_name,
const std::string &new_name) const { const std::string &new_name) const {
auto origin_it = vars_.find(origin_name); auto origin_it = vars_.find(origin_name);
if (origin_it == vars_.end()) { if (origin_it == vars_.end()) {
return; return;
} }
auto new_it = vars_.find(new_name); auto new_it = vars_.find(new_name);
if (new_it != vars_.end()) { if (new_it != vars_.end()) {
return; return;
} }
vars_[new_name] = origin_it->second; vars_[new_name] = origin_it->second;
vars_.erase(origin_it); vars_.erase(origin_it);
} }
// //
// std::string Scope::Rename(const std::string& origin_name) // std::string Scope::Rename(const std::string& origin_name)
...@@ -108,11 +108,11 @@ void Scope::Rename(const std::string &origin_name, ...@@ -108,11 +108,11 @@ void Scope::Rename(const std::string &origin_name,
// } // }
Variable *Scope::FindVarLocally(const std::string &name) const { Variable *Scope::FindVarLocally(const std::string &name) const {
auto it = vars_.find(name); auto it = vars_.find(name);
if (it != vars_.end()) { if (it != vars_.end()) {
return it->second; return it->second;
} }
return nullptr; return nullptr;
} }
} // namespace framework } // namespace framework
......
src/framework/scope.h
浏览文件 @ 1ad8f821
...@@ -26,56 +26,56 @@ SOFTWARE. ...@@ -26,56 +26,56 @@ SOFTWARE.
namespace paddle_mobile { namespace paddle_mobile {
namespace framework { namespace framework {
class Scope { class Scope {
public: public:
Scope() {} Scope() {}
~Scope() {} ~Scope() {}
Scope &NewScope() const; Scope &NewScope() const;
/// Create a variable with given name if it doesn't exist. /// Create a variable with given name if it doesn't exist.
Variable *Var(const std::string &name); Variable *Var(const std::string &name);
/// Create a variable with a scope-unique name. /// Create a variable with a scope-unique name.
Variable *Var(std::string *name = nullptr); 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 /// Find a variable in the scope or any of its ancestors. Returns
/// nullptr if cannot find. /// nullptr if cannot find.
Variable *FindVar(const std::string &name) const; 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 /// Find the scope or an ancestor scope that contains the given
/// variable. /// variable.
const Scope *FindScope(const Variable *var) const; 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. /// Drop all kids scopes belonged to this scope.
void DropKids(); void DropKids();
// enumerate all the variables current contains. // enumerate all the variables current contains.
std::vector<std::string> LocalVarNames() const; std::vector<std::string> LocalVarNames() const;
// Rename variable to a new name // Rename variable to a new name
void Rename(const std::string &origin_name, void Rename(const std::string &origin_name,
const std::string &new_name) const; const std::string &new_name) const;
// Rename variable to a new name and return the new name // Rename variable to a new name and return the new name
std::string Rename(const std::string &origin_name) const; std::string Rename(const std::string &origin_name) const;
Variable *FindVarLocally(const std::string &name) const; Variable *FindVarLocally(const std::string &name) const;
private: private:
// Call Scope::NewScope for a sub-scope. // Call Scope::NewScope for a sub-scope.
explicit Scope(Scope const *parent) : parent_(parent) {} explicit Scope(Scope const *parent) : parent_(parent) {}
mutable std::unordered_map<std::string, Variable *> vars_; mutable std::unordered_map<std::string, Variable *> vars_;
mutable std::list<Scope *> kids_; mutable std::list<Scope *> kids_;
Scope const *parent_{nullptr}; Scope const *parent_{nullptr};
mutable std::mutex mutex_; mutable std::mutex mutex_;
}; };
} // namespace framework } // namespace framework
} // namespace paddle_mobile } // namespace paddle_mobile
src/framework/selected_rows.h
浏览文件 @ 1ad8f821
...@@ -27,54 +27,54 @@ namespace paddle_mobile { ...@@ -27,54 +27,54 @@ namespace paddle_mobile {
namespace framework { namespace framework {
class SelectedRows { class SelectedRows {
public: public:
SelectedRows(const std::vector<int64_t> &rows, const int64_t &height) SelectedRows(const std::vector<int64_t> &rows, const int64_t &height)
: rows_(rows), height_(height) { : rows_(rows), height_(height) {
value_.reset(new Tensor()); value_.reset(new Tensor());
} }
SelectedRows() { SelectedRows() {
height_ = 0; height_ = 0;
value_.reset(new Tensor()); 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 * get the index of id in rows
*/ */
int64_t index(int64_t id) const { int64_t index(int64_t id) const {
auto it = std::find(rows_.begin(), rows_.end(), id); auto it = std::find(rows_.begin(), rows_.end(), id);
// PADDLE_ENFORCE(it != rows_.end(), "id should be in rows"); // PADDLE_ENFORCE(it != rows_.end(), "id should be in rows");
return static_cast<int64_t>(std::distance(rows_.begin(), it)); return static_cast<int64_t>(std::distance(rows_.begin(), it));
} }
DDim GetCompleteDims() const { DDim GetCompleteDims() const {
std::vector<int64_t> dims = vectorize(value_->dims()); std::vector<int64_t> dims = vectorize(value_->dims());
dims[0] = height_; dims[0] = height_;
return make_ddim(dims); return make_ddim(dims);
} }
private: private:
// Notice: rows can be duplicate. We can have {0, 4, 7, 0, 5, 7, 9} // Notice: rows can be duplicate. We can have {0, 4, 7, 0, 5, 7, 9}
// here. // here.
// SelectedRows are simply concated when adding together. Until a // SelectedRows are simply concated when adding together. Until a
// SelectedRows add a Tensor, will the duplicate rows be handled. // SelectedRows add a Tensor, will the duplicate rows be handled.
std::vector<int64_t> rows_; std::vector<int64_t> rows_;
std::unique_ptr<Tensor> value_{nullptr}; std::unique_ptr<Tensor> value_{nullptr};
int64_t height_; int64_t height_;
}; };
} // namespace framework } // namespace framework
......
src/framework/tensor.h
浏览文件 @ 1ad8f821
...@@ -29,305 +29,304 @@ namespace framework { ...@@ -29,305 +29,304 @@ 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 { size_t operator()(std::type_index type) const {
if (typeid(T).hash_code() == type.hash_code()) { if (typeid(T).hash_code() == type.hash_code()) {
return sizeof(T); return sizeof(T);
} else { } else {
return 0UL; return 0UL;
}
} }
}
}; };
template <> struct SizeOfTypeFunctor<> { template <> struct SizeOfTypeFunctor<> {
size_t operator()(std::type_index type) const { return 0UL; } size_t operator()(std::type_index type) const { return 0UL; }
}; };
template <typename HEAD, typename... TAIL> template <typename HEAD, typename... TAIL>
struct SizeOfTypeFunctor<HEAD, TAIL...> { struct SizeOfTypeFunctor<HEAD, TAIL...> {
size_t operator()(std::type_index type) const { size_t operator()(std::type_index type) const {
SizeOfTypeFunctor<HEAD> head; SizeOfTypeFunctor<HEAD> head;
size_t head_size = head(type); size_t head_size = head(type);
if (head_size != 0) { if (head_size != 0) {
return head_size; return head_size;
}
SizeOfTypeFunctor<TAIL...> tail;
return tail(type);
} }
SizeOfTypeFunctor<TAIL...> tail;
return tail(type);
}
}; };
static inline size_t SizeOfType(std::type_index type) { static inline size_t SizeOfType(std::type_index type) {
SizeOfTypeFunctor<int, float, double, int16_t, int64_t, bool, size_t> SizeOfTypeFunctor<int, float, double, int16_t, int64_t, bool, size_t> functor;
functor; size_t size = functor(type);
size_t size = functor(type); // PADDLE_ENFORCE(size != 0UL, "Cannot get size of type %s",
// PADDLE_ENFORCE(size != 0UL, "Cannot get size of type %s", // type.name());
// type.name()); return size;
return size;
} }
class LoDTensor; class LoDTensor;
class Tensor { class Tensor {
public: public:
Tensor() : offset_(0) {} Tensor() : offset_(0) {}
/*! Return a pointer to mutable memory block. */ /*! Return a pointer to mutable memory block. */
template <typename T> inline T *data() { template <typename T> inline T *data() {
check_memory_size(); check_memory_size();
// PADDLE_ENFORCE(std::is_same<T, void>::value || // PADDLE_ENFORCE(std::is_same<T, void>::value ||
// holder_->type().hash_code() == // holder_->type().hash_code() ==
// typeid(T).hash_code(), // typeid(T).hash_code(),
// "Tensor holds the wrong type, it holds %s", // "Tensor holds the wrong type, it holds %s",
// this->holder_->type().name()); // this->holder_->type().name());
return reinterpret_cast<T *>( return reinterpret_cast<T *>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_); offset_);
}
/*! Return a pointer to constant memory block. */
template <typename T> inline const T *data() const {
check_memory_size();
// PADDLE_ENFORCE(std::is_same<T, void>::value ||
// holder_->type().hash_code() ==
// typeid(T).hash_code(),
// "Tensor holds the wrong type, it holds %s",
// this->holder_->type().name());
return reinterpret_cast<const T *>(
reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);
}
inline bool IsInitialized() const { return holder_ != nullptr; }
/**
* @brief Return a pointer to mutable memory block.
* @note If not exist, then allocation.
*/
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)));
}
inline void *mutable_data(std::type_index type) {
if (holder_ != nullptr) {
holder_->set_type(type);
} }
// PADDLE_ENFORCE_GE(numel(), 0,
/*! Return a pointer to constant memory block. */ // "When calling this method, the Tensor's
template <typename T> inline const T *data() const { // numel must be
check_memory_size(); // " "equal or larger than zero. " "Please
// PADDLE_ENFORCE(std::is_same<T, void>::value || // check
// holder_->type().hash_code() == // Tensor::Resize has been called first.");
// typeid(T).hash_code(), int64_t size = numel() * SizeOfType(type);
// "Tensor holds the wrong type, it holds %s", /* some versions of boost::variant don't have operator!= */
// this->holder_->type().name()); if (holder_ == nullptr || holder_->size() < size + offset_) {
holder_.reset(new PlaceholderImpl(size, type));
return reinterpret_cast<const T *>(
reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_); offset_ = 0;
} }
return reinterpret_cast<void *>(
inline bool IsInitialized() const { return holder_ != nullptr; } reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);
}
/**
* @brief Return a pointer to mutable memory block. inline void *mutable_data() {
* @note If not exist, then allocation. // PADDLE_ENFORCE(this->holder_ != nullptr,
*/ // "Cannot invoke mutable data if current hold
template <typename T> inline T *mutable_data() { // nothing.");
static_assert(std::is_pod<T>::value, "T must be POD"); return mutable_data(holder_->type());
return reinterpret_cast<T *>(mutable_data(typeid(T))); }
/**
* @brief Return a pointer to mutable memory block.
*
* @param[in] dims The dimensions of the memory block.
* @param[in] place The place of the memory block.
*
* @note If not exist, then allocation.
*/
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>();
}
/*! Return the dimensions of the memory block. */
inline const DDim &dims() const { return dims_; }
/*! Return the numel of the memory block. */
inline int64_t numel() const { return product(dims_); }
/*! Resize the dimensions of the memory block. */
inline Tensor &Resize(const DDim &dims) {
dims_ = dims;
return *this;
}
/*! The internal of two tensors share the same memory block. */
inline Tensor &ShareDataWith(const Tensor &src) {
src.check_memory_size();
*this = src;
return *this;
}
/**
* @brief Return a sub-tensor of the given tensor.
*
* @param[in] begin_idx The index of the start row(inclusive) to
* slice.
* The index number begins from 0.
* @param[in] end_idx The index of the end row(exclusive) to
* slice.
* The index number begins from 0.
*/
inline Tensor Slice(int begin_idx, int end_idx) const {
check_memory_size();
// PADDLE_ENFORCE_GE(begin_idx, 0,
// "The start row index must be greater than
// 0.");
// PADDLE_ENFORCE_LE(end_idx, dims_[0], "The end row index is
// out of
// bound."); PADDLE_ENFORCE_LT(
// begin_idx, end_idx,
// "The start row index must be lesser than the end row
// index.");
if (dims_[0] == 1) {
return *this;
} else {
size_t base = numel() / dims_[0];
Tensor dst;
dst.holder_ = holder_;
dst.set_layout(layout_);
DDim dst_dims = dims_;
dst_dims[0] = end_idx - begin_idx;
dst.Resize(dst_dims);
dst.offset_ = offset_ + begin_idx * base * SizeOfType(type());
return dst;
} }
}
inline void *mutable_data(std::type_index type) {
if (holder_ != nullptr) { std::type_index type() const {
holder_->set_type(type); // PADDLE_ENFORCE_NOT_NULL(
} // holder_, "Tensor not initialized yet
// PADDLE_ENFORCE_GE(numel(), 0, // when
// "When calling this method, the Tensor's // Tensor::type() is called.");
// numel must be return holder_->type();
// " "equal or larger than zero. " "Please }
// check
// Tensor::Resize has been called first."); // memory size returns the holding memory size in byte.
int64_t size = numel() * SizeOfType(type); size_t memory_size() const {
/* some versions of boost::variant don't have operator!= */ return holder_ == nullptr ? 0UL : holder_->size() - offset_;
if (holder_ == nullptr || holder_->size() < size + offset_) { }
holder_.reset(new PlaceholderImpl(size, type));
inline void check_memory_size() const {
offset_ = 0; // PADDLE_ENFORCE_NOT_NULL(
} // holder_, "Tensor holds no memory. Call
return reinterpret_cast<void *>( // Tensor::mutable_data
reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_); // first.");
// PADDLE_ENFORCE_LE(
// numel() * SizeOfType(type()), memory_size(),
// "Tensor's dims_ is out of bound. Call
// Tensor::mutable_data "
// "first to re-allocate memory.\n"
// "or maybe the required data-type mismatches the data
// already
// stored.");
}
inline DataLayout layout() const { return layout_; }
inline void set_layout(const DataLayout layout) { layout_ = layout; }
private:
/**
* @note Placeholder hides type T, so it doesn't appear as a
* template
* parameter of Variable.
*/
struct Placeholder {
virtual ~Placeholder() = default;
virtual void *ptr() const = 0;
virtual size_t size() const = 0;
virtual std::type_index type() const = 0;
virtual void set_type(std::type_index type) = 0;
};
struct PlaceholderImpl : public Placeholder {
PlaceholderImpl(size_t size, std::type_index type)
: ptr_(static_cast<uint8_t *>(memory::Alloc(size)),
memory::PODDeleter<uint8_t>()),
size_(size), type_(type) {
// PADDLE_ENFORCE_NOT_NULL(ptr_,
// "Insufficient %s
// memory to allocation.",
// (is_cpu_place(place_)
// ?
// "CPU" :
// "GPU"));
} }
inline void *mutable_data() { virtual size_t size() const { return size_; }
// PADDLE_ENFORCE(this->holder_ != nullptr,
// "Cannot invoke mutable data if current hold
// nothing.");
return mutable_data(holder_->type());
}
/** virtual void *ptr() const { return static_cast<void *>(ptr_.get()); }
* @brief Return a pointer to mutable memory block.
*
* @param[in] dims The dimensions of the memory block.
* @param[in] place The place of the memory block.
*
* @note If not exist, then allocation.
*/
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>();
}
/*! Return the dimensions of the memory block. */ virtual std::type_index type() const { return type_; }
inline const DDim &dims() const { return dims_; }
/*! Return the numel of the memory block. */ virtual void set_type(std::type_index type) { type_ = type; }
inline int64_t numel() const { return product(dims_); }
/*! Resize the dimensions of the memory block. */ /*! the pointer of memory block. */
inline Tensor &Resize(const DDim &dims) { std::unique_ptr<uint8_t, memory::PODDeleter<uint8_t>> ptr_;
dims_ = dims;
return *this;
}
/*! The internal of two tensors share the same memory block. */ /*! the size of memory block. */
inline Tensor &ShareDataWith(const Tensor &src) { size_t size_;
src.check_memory_size();
*this = src;
return *this;
}
/** /* the current type of memory */
* @brief Return a sub-tensor of the given tensor. std::type_index type_;
* };
* @param[in] begin_idx The index of the start row(inclusive) to
* slice.
* The index number begins from 0.
* @param[in] end_idx The index of the end row(exclusive) to
* slice.
* The index number begins from 0.
*/
inline Tensor Slice(int begin_idx, int end_idx) const {
check_memory_size();
// PADDLE_ENFORCE_GE(begin_idx, 0,
// "The start row index must be greater than
// 0.");
// PADDLE_ENFORCE_LE(end_idx, dims_[0], "The end row index is
// out of
// bound."); PADDLE_ENFORCE_LT(
// begin_idx, end_idx,
// "The start row index must be lesser than the end row
// index.");
if (dims_[0] == 1) {
return *this;
} else {
size_t base = numel() / dims_[0];
Tensor dst;
dst.holder_ = holder_;
dst.set_layout(layout_);
DDim dst_dims = dims_;
dst_dims[0] = end_idx - begin_idx;
dst.Resize(dst_dims);
dst.offset_ = offset_ + begin_idx * base * SizeOfType(type());
return dst;
}
}
std::type_index type() const { /*! holds the memory block if allocated. */
// PADDLE_ENFORCE_NOT_NULL( std::shared_ptr<Placeholder> holder_;
// holder_, "Tensor not initialized yet
// when
// Tensor::type() is called.");
return holder_->type();
}
// memory size returns the holding memory size in byte. /**
size_t memory_size() const { * @brief points to elements dimensions.
return holder_ == nullptr ? 0UL : holder_->size() - offset_; *
} * @note dims_ do not indicate the memory block size.
*/
inline void check_memory_size() const { DDim dims_;
// PADDLE_ENFORCE_NOT_NULL(
// holder_, "Tensor holds no memory. Call /**
// Tensor::mutable_data * @brief the layout of memory block, default is NHWC.
// first."); *
// PADDLE_ENFORCE_LE( * @note the memory allocation order, describe how weight/data is
// numel() * SizeOfType(type()), memory_size(), * stored
// "Tensor's dims_ is out of bound. Call * For example, in 4-D Tensor(rank=4), there are three
// Tensor::mutable_data " * commonly
// "first to re-allocate memory.\n" * used layout. They are
// "or maybe the required data-type mismatches the data * NCHW, NHWC, CHWN.
// already * N,C,H,W for respectively the batch size, the number of
// stored."); * feature maps, the height, the width.
} */
DataLayout layout_ = DataLayout::kNHWC;
inline DataLayout layout() const { return layout_; } /**
* @brief A PlaceHolder may be shared by more than one tensor.
inline void set_layout(const DataLayout layout) { layout_ = layout; } *
* @note Some of them may be slices of the others. So the offset_
private: * is introduced here to indicate the byte offset between
/** * PlaceHolder::ptr_ and where the tensor data really
* @note Placeholder hides type T, so it doesn't appear as a * begins.
* template */
* parameter of Variable. size_t offset_;
*/
struct Placeholder {
virtual ~Placeholder() = default;
virtual void *ptr() const = 0;
virtual size_t size() const = 0;
virtual std::type_index type() const = 0;
virtual void set_type(std::type_index type) = 0;
};
struct PlaceholderImpl : public Placeholder {
PlaceholderImpl(size_t size, std::type_index type)
: ptr_(static_cast<uint8_t *>(memory::Alloc(size)),
memory::PODDeleter<uint8_t>()),
size_(size), type_(type) {
// PADDLE_ENFORCE_NOT_NULL(ptr_,
// "Insufficient %s
// memory to allocation.",
// (is_cpu_place(place_)
// ?
// "CPU" :
// "GPU"));
}
virtual size_t size() const { return size_; }
virtual void *ptr() const { return static_cast<void *>(ptr_.get()); }
virtual std::type_index type() const { return type_; }
virtual void set_type(std::type_index type) { type_ = type; }
/*! the pointer of memory block. */
std::unique_ptr<uint8_t, memory::PODDeleter<uint8_t>> ptr_;
/*! the size of memory block. */
size_t size_;
/* the current type of memory */
std::type_index type_;
};
/*! holds the memory block if allocated. */
std::shared_ptr<Placeholder> holder_;
/**
* @brief points to elements dimensions.
*
* @note dims_ do not indicate the memory block size.
*/
DDim dims_;
/**
* @brief the layout of memory block, default is NHWC.
*
* @note the memory allocation order, describe how weight/data is
* stored
* For example, in 4-D Tensor(rank=4), there are three
* commonly
* used layout. They are
* NCHW, NHWC, CHWN.
* N,C,H,W for respectively the batch size, the number of
* feature maps, the height, the width.
*/
DataLayout layout_ = DataLayout::kNHWC;
/**
* @brief A PlaceHolder may be shared by more than one tensor.
*
* @note Some of them may be slices of the others. So the offset_
* is introduced here to indicate the byte offset between
* PlaceHolder::ptr_ and where the tensor data really
* begins.
*/
size_t offset_;
}; };
inline Tensor ReshapeToMatrix(const Tensor &src, int num_col_dims) { inline Tensor ReshapeToMatrix(const Tensor &src, int num_col_dims) {
Tensor res; Tensor res;
res.ShareDataWith(src); res.ShareDataWith(src);
res.Resize(flatten_to_2d(src.dims(), num_col_dims)); res.Resize(flatten_to_2d(src.dims(), num_col_dims));
return res; return res;
} }
} // namespace framework } // namespace framework
......
src/framework/tensor_util.cc
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src/framework/tensor_util.h
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...@@ -43,23 +43,23 @@ void TensorFromStream(std::istream &is, Tensor *tensor); ...@@ -43,23 +43,23 @@ void TensorFromStream(std::istream &is, Tensor *tensor);
template <typename T> template <typename T>
void TensorFromVector(const std::vector<T> &src, Tensor *dst) { void TensorFromVector(const std::vector<T> &src, Tensor *dst) {
auto src_ptr = static_cast<const void *>(src.data()); auto src_ptr = static_cast<const void *>(src.data());
dst->Resize({static_cast<int64_t>(src.size())}); dst->Resize({static_cast<int64_t>(src.size())});
auto dst_ptr = static_cast<void *>(dst->mutable_data<T>()); auto dst_ptr = static_cast<void *>(dst->mutable_data<T>());
auto size = src.size() * sizeof(T); auto size = src.size() * sizeof(T);
memory::Copy(dst_ptr, src_ptr, size); memory::Copy(dst_ptr, src_ptr, size);
} }
template <typename T> template <typename T>
void TensorToVector(const Tensor &src, std::vector<T> *dst) { void TensorToVector(const Tensor &src, std::vector<T> *dst) {
auto src_ptr = static_cast<const void *>(src.data<T>()); auto src_ptr = static_cast<const void *>(src.data<T>());
auto size = src.numel() * sizeof(T); auto size = src.numel() * sizeof(T);
dst->resize(src.numel()); dst->resize(src.numel());
auto dst_ptr = static_cast<void *>(dst->data()); 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
......
src/framework/var_desc.h
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namespace framework { namespace framework {
class VarDesc { class VarDesc {
public: public:
VarDesc(const proto::VarDesc &desc); VarDesc(const proto::VarDesc &desc);
std::string Name() const { return desc_.name(); } std::string Name() const { return desc_.name(); }
proto::VarType::Type GetType() const { return desc_.type().type(); } proto::VarType::Type GetType() const { return desc_.type().type(); }
bool Persistable() const { return desc_.persistable(); } bool Persistable() const { return desc_.persistable(); }
const proto::VarType::ChannelDesc &channel_desc() const { const proto::VarType::ChannelDesc &channel_desc() const {
switch (desc_.type().type()) { switch (desc_.type().type()) {
case proto::VarType::CHANNEL: case proto::VarType::CHANNEL:
return desc_.type().channel(); return desc_.type().channel();
default: default:
break; break;
}
} }
}
const proto::VarType::TensorDesc &tensor_desc() const { const proto::VarType::TensorDesc &tensor_desc() const {
switch (desc_.type().type()) { switch (desc_.type().type()) {
case proto::VarType::SELECTED_ROWS: case proto::VarType::SELECTED_ROWS:
return desc_.type().selected_rows(); return desc_.type().selected_rows();
case proto::VarType::LOD_TENSOR: case proto::VarType::LOD_TENSOR:
return desc_.type().lod_tensor().tensor(); return desc_.type().lod_tensor().tensor();
case proto::VarType::LOD_TENSOR_ARRAY: case proto::VarType::LOD_TENSOR_ARRAY:
return desc_.type().tensor_array().tensor(); return desc_.type().tensor_array().tensor();
default: default:
break; break;
}
} }
}
proto::VarType::Type GetDataType() const { proto::VarType::Type GetDataType() const {
switch (desc_.type().type()) { switch (desc_.type().type()) {
case proto::VarType::CHANNEL: case proto::VarType::CHANNEL:
return channel_desc().data_type(); return channel_desc().data_type();
break; break;
default: default:
return tensor_desc().data_type(); return tensor_desc().data_type();
}
} }
}
template <typename T> template <typename T>
std::vector<T> RepeatedToVector( std::vector<T> RepeatedToVector(
const google::protobuf::RepeatedField<T> &repeated_field) const { const google::protobuf::RepeatedField<T> &repeated_field) const {
std::vector<T> ret; std::vector<T> ret;
ret.reserve(repeated_field.size()); ret.reserve(repeated_field.size());
std::copy(repeated_field.begin(), repeated_field.end(), std::copy(repeated_field.begin(), repeated_field.end(),
std::back_inserter(ret)); std::back_inserter(ret));
return ret; return ret;
} }
std::vector<int64_t> GetShape() const { std::vector<int64_t> GetShape() const {
return this->RepeatedToVector(tensor_desc().dims()); return this->RepeatedToVector(tensor_desc().dims());
} }
private: private:
proto::VarDesc desc_; proto::VarDesc desc_;
}; };
} // namespace framework } // namespace framework
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src/framework/var_type.h
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namespace paddle_mobile { namespace paddle_mobile {
namespace framework { namespace framework {
inline proto::VarType::Type ToVarType(std::type_index type) { inline proto::VarType::Type ToVarType(std::type_index type) {
if (type.hash_code() == typeid(LoDTensor).hash_code()) { if (type.hash_code() == typeid(LoDTensor).hash_code()) {
return proto::VarType_Type_LOD_TENSOR; return proto::VarType_Type_LOD_TENSOR;
} else if (type.hash_code() == typeid(SelectedRows).hash_code()) { } else if (type.hash_code() == typeid(SelectedRows).hash_code()) {
return proto::VarType_Type_SELECTED_ROWS; return proto::VarType_Type_SELECTED_ROWS;
} else { } else {
// PADDLE_THROW("ToVarType:Unsupported type %s", // PADDLE_THROW("ToVarType:Unsupported type %s",
// type.name()); // type.name());
} }
} }
} // namespace framework } // namespace framework
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src/framework/variable.h
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src/io.cpp
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src/io.h
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...@@ -29,11 +29,11 @@ namespace paddle_mobile { ...@@ -29,11 +29,11 @@ namespace paddle_mobile {
template <typename Dtype, Precision P = Precision::FP32> template <typename Dtype, Precision P = Precision::FP32>
class Loader : PaddleMobileObject { class Loader : PaddleMobileObject {
public: public:
const framework::Program<Dtype, P> Load(const std::string &dirname); const framework::Program<Dtype, P> Load(const std::string &dirname);
private: private:
void LoadVar(framework::LoDTensor *tensor, const std::string &file_path); void LoadVar(framework::LoDTensor *tensor, const std::string &file_path);
}; };
} // namespace paddle_mobile } // namespace paddle_mobile
src/memory/t_malloc.cc
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const int MALLOC_ALIGN = 16; const int MALLOC_ALIGN = 16;
void Copy(void *dst, const void *src, size_t num) { void Copy(void *dst, const void *src, size_t num) {
std::memcpy(dst, src, num); std::memcpy(dst, src, num);
}; };
void *Alloc(size_t size) { void *Alloc(size_t size) {
size_t offset = sizeof(void *) + MALLOC_ALIGN - 1; size_t offset = sizeof(void *) + MALLOC_ALIGN - 1;
char *p = static_cast<char *>(malloc(offset + size)); char *p = static_cast<char *>(malloc(offset + size));
if (!p) { if (!p) {
return nullptr; return nullptr;
} }
void *r = reinterpret_cast<void *>(reinterpret_cast<size_t>(p + offset) & void *r = reinterpret_cast<void *>(reinterpret_cast<size_t>(p + offset) &
(~(MALLOC_ALIGN - 1))); (~(MALLOC_ALIGN - 1)));
static_cast<void **>(r)[-1] = p; static_cast<void **>(r)[-1] = p;
return r; return r;
} }
void Free(void *ptr) { void Free(void *ptr) {
if (ptr) { if (ptr) {
free(static_cast<void **>(ptr)[-1]); free(static_cast<void **>(ptr)[-1]);
} }
} }
} // namespace memory } // namespace memory
......
src/memory/t_malloc.h
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src/operators/batchnorm_op.cpp
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src/operators/batchnorm_op.h
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src/operators/concat_op.cpp
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src/operators/concat_op.h
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src/operators/conv_op.cpp
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src/operators/conv_op.h
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src/operators/elementwise_add_op.h
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src/operators/kernel/conv_kernel.h
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src/operators/kernel/lrn_kernel.h
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src/operators/kernel/mul_kernel.h
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src/operators/kernel/pool_kernel.h
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src/operators/lrn_op.cpp
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src/operators/lrn_op.h
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src/operators/math/im2col.cc
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src/operators/math/im2col.h
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src/operators/math/math_function.cc
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src/operators/math/pool3x3.h
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src/operators/math/pool_2x2.h
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src/operators/math/pooling.cpp
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src/operators/math/pooling.h
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src/operators/math/transform.h
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src/operators/math/vol2col.cc
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src/operators/math/vol2col.h
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src/operators/mul_op.cpp
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src/operators/mul_op.h
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src/operators/op_param.cpp
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src/operators/op_param.h
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src/operators/pool_op.cpp
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src/operators/pool_op.h
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src/platform/data_type.h
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src/platform/macros.h
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test/common/test_log.cpp
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test/framework/executor_for_test.h
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test/framework/test_load.cpp
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test/framework/test_optimize.cpp
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test/operators/test_concat_op.cpp
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test/operators/test_cov_op.cpp
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test/operators/test_lrn_op.cpp
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test/operators/test_mul_op.cpp
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test/operators/test_pool_op.cpp
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test/test_helper.h
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