提交 052d1d16 编写于 作者: D dongzhihong

Merge remote-tracking branch 'origin/develop' into net_ycw

......@@ -21,3 +21,10 @@
sha: 28c0ea8a67a3e2dbbf4822ef44e85b63a0080a29
hooks:
- id: clang-formater
- repo: https://github.com/dnephin/pre-commit-golang
sha: e4693a4c282b4fc878eda172a929f7a6508e7d16
hooks:
- id: go-fmt
files: (.*\.go)
- id: go-lint
files: (.*\.go)
......@@ -37,12 +37,13 @@ before_install:
# protobuf version.
- pip install numpy wheel 'protobuf==3.1' sphinx==1.5.6 recommonmark sphinx-rtd-theme==0.1.9 virtualenv pre-commit requests==2.9.2 LinkChecker
- pip install rarfile
- curl https://glide.sh/get | bash
- eval "$(GIMME_GO_VERSION=1.8.3 gimme)"
- |
function timeout() { perl -e 'alarm shift; exec @ARGV' "$@"; }
script:
- |
export WITH_GOLANG=ON && timeout 2580 paddle/scripts/travis/${JOB}.sh # 43min timeout
timeout 2580 paddle/scripts/travis/${JOB}.sh # 43min timeout
RESULT=$?; if [ $RESULT -eq 0 ] || [ $RESULT -eq 142 ]; then true; else false; fi;
notifications:
email:
......
......@@ -16,6 +16,7 @@ cmake_minimum_required(VERSION 3.0)
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${CMAKE_CURRENT_SOURCE_DIR}/cmake")
set(PROJ_ROOT ${CMAKE_CURRENT_SOURCE_DIR})
set(PROJ_BINARY_ROOT ${CMAKE_CURRENT_BINARY_DIR})
include(system)
......
......@@ -38,12 +38,14 @@ ExternalProject_Add(
CMAKE_ARGS -DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}
CMAKE_ARGS -DCMAKE_C_FLAGS=${CMAKE_C_FLAGS}
CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${GLOG_INSTALL_DIR}
CMAKE_ARGS -DCMAKE_INSTALL_LIBDIR=${GLOG_INSTALL_DIR}/lib
CMAKE_ARGS -DCMAKE_POSITION_INDEPENDENT_CODE=ON
CMAKE_ARGS -DWITH_GFLAGS=ON
CMAKE_ARGS -Dgflags_DIR=${GFLAGS_INSTALL_DIR}/lib/cmake/gflags
CMAKE_ARGS -DBUILD_TESTING=OFF
CMAKE_ARGS -DCMAKE_BUILD_TYPE=Release
CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${GLOG_INSTALL_DIR}
-DCMAKE_INSTALL_LIBDIR:PATH=${GLOG_INSTALL_DIR}/lib
-DCMAKE_POSITION_INDEPENDENT_CODE:BOOL=ON
-DCMAKE_BUILD_TYPE:STRING=Release
)
......
......@@ -17,6 +17,65 @@ INCLUDE(ExternalProject)
FIND_PACKAGE(Protobuf QUIET)
SET(PROTOBUF_FOUND "OFF")
if(NOT COMMAND protobuf_generate_python) # before cmake 3.4, protobuf_genrerate_python is not defined.
function(protobuf_generate_python SRCS)
# shameless copy from https://github.com/Kitware/CMake/blob/master/Modules/FindProtobuf.cmake
if(NOT ARGN)
message(SEND_ERROR "Error: PROTOBUF_GENERATE_PYTHON() called without any proto files")
return()
endif()
if(PROTOBUF_GENERATE_CPP_APPEND_PATH)
# Create an include path for each file specified
foreach(FIL ${ARGN})
get_filename_component(ABS_FIL ${FIL} ABSOLUTE)
get_filename_component(ABS_PATH ${ABS_FIL} PATH)
list(FIND _protobuf_include_path ${ABS_PATH} _contains_already)
if(${_contains_already} EQUAL -1)
list(APPEND _protobuf_include_path -I ${ABS_PATH})
endif()
endforeach()
else()
set(_protobuf_include_path -I ${CMAKE_CURRENT_SOURCE_DIR})
endif()
if(DEFINED PROTOBUF_IMPORT_DIRS AND NOT DEFINED Protobuf_IMPORT_DIRS)
set(Protobuf_IMPORT_DIRS "${PROTOBUF_IMPORT_DIRS}")
endif()
if(DEFINED Protobuf_IMPORT_DIRS)
foreach(DIR ${Protobuf_IMPORT_DIRS})
get_filename_component(ABS_PATH ${DIR} ABSOLUTE)
list(FIND _protobuf_include_path ${ABS_PATH} _contains_already)
if(${_contains_already} EQUAL -1)
list(APPEND _protobuf_include_path -I ${ABS_PATH})
endif()
endforeach()
endif()
set(${SRCS})
foreach(FIL ${ARGN})
get_filename_component(ABS_FIL ${FIL} ABSOLUTE)
get_filename_component(FIL_WE ${FIL} NAME_WE)
if(NOT PROTOBUF_GENERATE_CPP_APPEND_PATH)
get_filename_component(FIL_DIR ${FIL} DIRECTORY)
if(FIL_DIR)
set(FIL_WE "${FIL_DIR}/${FIL_WE}")
endif()
endif()
list(APPEND ${SRCS} "${CMAKE_CURRENT_BINARY_DIR}/${FIL_WE}_pb2.py")
add_custom_command(
OUTPUT "${CMAKE_CURRENT_BINARY_DIR}/${FIL_WE}_pb2.py"
COMMAND ${Protobuf_PROTOC_EXECUTABLE} --python_out ${CMAKE_CURRENT_BINARY_DIR} ${_protobuf_include_path} ${ABS_FIL}
DEPENDS ${ABS_FIL} ${Protobuf_PROTOC_EXECUTABLE}
COMMENT "Running Python protocol buffer compiler on ${FIL}"
VERBATIM )
endforeach()
set(${SRCS} ${${SRCS}} PARENT_SCOPE)
endfunction()
endif()
# Print and set the protobuf library information,
# finish this cmake process and exit from this file.
......
......@@ -88,7 +88,7 @@
#
# including binary directory for generated headers.
include_directories(${CMAKE_BINARY_DIR})
include_directories(${CMAKE_CURRENT_BINARY_DIR})
if(NOT APPLE)
find_package(Threads REQUIRED)
......@@ -99,15 +99,33 @@ function(merge_static_libs TARGET_NAME)
set(libs ${ARGN})
list(REMOVE_DUPLICATES libs)
# First get the file names of the libraries to be merged
# Get all propagation dependencies from the merged libraries
foreach(lib ${libs})
set(libfiles ${libfiles} $<TARGET_FILE:${lib}>)
list(APPEND libs_deps ${${lib}_LIB_DEPENDS})
endforeach()
if(APPLE) # Use OSX's libtool to merge archives
# To produce a library we need at least one source file.
# It is created by add_custom_command below and will helps
# also help to track dependencies.
set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}_dummy.c)
# Make the generated dummy source file depended on all static input
# libs. If input lib changes,the source file is touched
# which causes the desired effect (relink).
add_custom_command(OUTPUT ${dummyfile}
COMMAND ${CMAKE_COMMAND} -E touch ${dummyfile}
DEPENDS ${libs})
# Generate dummy staic lib
file(WRITE ${dummyfile} "const char * dummy = \"${dummyfile}\";")
add_library(${TARGET_NAME} STATIC ${dummyfile})
target_link_libraries(${TARGET_NAME} ${libs_deps})
foreach(lib ${libs})
# Get the file names of the libraries to be merged
set(libfiles ${libfiles} $<TARGET_FILE:${lib}>)
endforeach()
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND rm "${CMAKE_CURRENT_BINARY_DIR}/lib${TARGET_NAME}.a"
COMMAND /usr/bin/libtool -static -o "${CMAKE_CURRENT_BINARY_DIR}/lib${TARGET_NAME}.a" ${libfiles})
......@@ -117,7 +135,8 @@ function(merge_static_libs TARGET_NAME)
set(objdir ${lib}.objdir)
add_custom_command(OUTPUT ${objdir}
COMMAND ${CMAKE_COMMAND} -E make_directory ${objdir})
COMMAND ${CMAKE_COMMAND} -E make_directory ${objdir}
DEPENDS ${lib})
add_custom_command(OUTPUT ${objlistfile}
COMMAND ${CMAKE_AR} -x "$<TARGET_FILE:${lib}>"
......@@ -134,18 +153,18 @@ function(merge_static_libs TARGET_NAME)
list(APPEND mergebases "${mergebase}")
endforeach()
# We need a target for the output merged library
add_library(${TARGET_NAME} STATIC ${mergebases})
target_link_libraries(${TARGET_NAME} ${libs_deps})
# Get the file name of the generated library
set(outlibfile "$<TARGET_FILE:${TARGET_NAME}>")
foreach(lib ${libs})
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND ${CMAKE_AR} ru ${outlibfile} @"../${lib}.objlist"
COMMAND ${CMAKE_AR} cr ${outlibfile} *.o
COMMAND ${CMAKE_RANLIB} ${outlibfile}
WORKING_DIRECTORY ${lib}.objdir)
endforeach()
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND ${CMAKE_RANLIB} ${outlibfile})
endif()
endfunction(merge_static_libs)
......@@ -192,7 +211,7 @@ function(cc_test TARGET_NAME)
set(multiValueArgs SRCS DEPS)
cmake_parse_arguments(cc_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
add_executable(${TARGET_NAME} ${cc_test_SRCS})
target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} gtest gtest_main -lstdc++ -lm)
target_link_libraries(${TARGET_NAME} ${cc_test_DEPS} gtest gtest_main)
add_dependencies(${TARGET_NAME} ${cc_test_DEPS} gtest gtest_main)
add_test(NAME ${TARGET_NAME} COMMAND ${TARGET_NAME} WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
endif()
......@@ -285,7 +304,7 @@ function(go_library TARGET_NAME)
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND rm "${${TARGET_NAME}_LIB_PATH}"
# Golang build source code
COMMAND env LIBRARY_PATH=${CMAKE_BINARY_DIR}/go/pserver/client/c/:$ENV{LIBRARY_PATH} GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build ${BUILD_MODE}
COMMAND GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build ${BUILD_MODE}
-o "${${TARGET_NAME}_LIB_PATH}"
"./${CMAKE_CURRENT_SOURCE_REL_DIR}/${GO_SOURCE}"
# must run under GOPATH
......@@ -335,3 +354,12 @@ function(proto_library TARGET_NAME)
protobuf_generate_cpp(proto_srcs proto_hdrs ${proto_library_SRCS})
cc_library(${TARGET_NAME} SRCS ${proto_srcs} DEPS ${proto_library_DEPS} protobuf)
endfunction()
function(py_proto_compile TARGET_NAME)
set(oneValueArgs "")
set(multiValueArgs SRCS)
cmake_parse_arguments(py_proto_compile "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(py_srcs)
protobuf_generate_python(py_srcs ${py_proto_compile_SRCS})
add_custom_target(${TARGET_NAME} ALL DEPENDS ${py_srcs})
endfunction()
......@@ -101,7 +101,7 @@
</div>
<div class="site-nav-links">
<div class="site-menu">
<a class="fork-on-github" href="https://github.com/PaddlePaddle/Paddle" target="_blank"><i class="fa fa-github"></i>Folk me on Github</a>
<a class="fork-on-github" href="https://github.com/PaddlePaddle/Paddle" target="_blank"><i class="fa fa-github"></i>Fork me on Github</a>
<div class="language-switcher dropdown">
<a type="button" data-toggle="dropdown">
<span>English</span>
......
......@@ -104,11 +104,22 @@ func paddle_set_dataset(client C.paddle_master_client, path **C.char, size C.int
return C.PADDLE_MASTER_OK
}
// return value:
// 0:ok
// -1:error
//export paddle_next_record
func paddle_next_record(client C.paddle_master_client, record **C.uchar) C.int {
c := get(client)
r := c.NextRecord()
r, err := c.NextRecord()
if err != nil {
// Error
// TODO: return the type of error?
*record = (*C.uchar)(nullPtr)
return -1
}
if len(r) == 0 {
// Empty record
*record = (*C.uchar)(nullPtr)
return 0
}
......
......@@ -11,7 +11,12 @@ import (
// Client is the client of the master server.
type Client struct {
conn *connection.Conn
ch chan []byte
ch chan record
}
type record struct {
r []byte
err error
}
// NewClient creates a new Client.
......@@ -21,7 +26,7 @@ type Client struct {
func NewClient(addrCh <-chan string, bufSize int) *Client {
c := &Client{}
c.conn = connection.New()
c.ch = make(chan []byte, bufSize)
c.ch = make(chan record, bufSize)
go c.monitorMaster(addrCh)
go c.getRecords()
return c
......@@ -46,10 +51,11 @@ func (c *Client) getRecords() {
s := recordio.NewRangeScanner(f, &chunk.Index, -1, -1)
for s.Scan() {
c.ch <- s.Record()
c.ch <- record{s.Record(), nil}
}
if s.Err() != nil {
c.ch <- record{nil, s.Err()}
log.Errorln(err, chunk.Path)
}
......@@ -116,6 +122,7 @@ func (c *Client) taskFinished(taskID int) error {
//
// NextRecord will block until the next record is available. It is
// thread-safe.
func (c *Client) NextRecord() []byte {
return <-c.ch
func (c *Client) NextRecord() ([]byte, error) {
r := <-c.ch
return r.r, r.err
}
......@@ -68,12 +68,17 @@ func TestNextRecord(t *testing.T) {
for pass := 0; pass < 50; pass++ {
received := make(map[byte]bool)
for i := 0; i < total; i++ {
r := c.NextRecord()
r, err := c.NextRecord()
if err != nil {
t.Fatal(pass, i, "Read error:", err)
}
if len(r) != 1 {
t.Fatal("Length should be 1.", r)
t.Fatal(pass, i, "Length should be 1.", r)
}
if received[r[0]] {
t.Fatal("Received duplicate.", received, r)
t.Fatal(pass, i, "Received duplicate.", received, r)
}
received[r[0]] = true
}
......
cc_library(paddle_go_optimizer DEPS paddle_optimizer paddle_proto glog gflags protobuf)
target_link_libraries(paddle_go_optimizer stdc++ m)
go_library(paddle_pserver_cclient STATIC DEPS paddle_go_optimizer)
if(WITH_TESTING)
# TODO: add unit test
#add_subdirectory(test)
# FIXME: this test requires pserver which is not managed by the test
# we need some kind of e2e testing machanism.
# add_subdirectory(test)
endif()
package pserver
// #cgo CFLAGS: -I ../../
// #cgo LDFLAGS: -lpaddle_go_optimizer -lstdc++ -lm
// //FIXME: ldflags contain "build" path
// #cgo LDFLAGS: ${SRCDIR}/../../build/go/pserver/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
// #include "paddle/optimizer/optimizer.h"
// #include <stdlib.h>
// #include <string.h>
......@@ -55,8 +56,8 @@ func newOptimizer(paramWithConfigs ParameterWithConfig) *optimizer {
func (o *optimizer) GetWeights() []byte {
var buffer unsafe.Pointer
buffer_len := C.paddle_optimizer_get_weights(o.opt, &buffer)
return cArrayToSlice(buffer, int(buffer_len)*C.sizeof_float)
bufferLen := C.paddle_optimizer_get_weights(o.opt, &buffer)
return cArrayToSlice(buffer, int(bufferLen)*C.sizeof_float)
}
func (o *optimizer) UpdateParameter(g Gradient) error {
......
......@@ -10,7 +10,9 @@ import (
type ElementType int
const (
// AlreadyInitialized is true if pserver is initialized
AlreadyInitialized = "pserver already initialized"
// Uninitialized is true if pserver not fully initialized
Uninitialized = "pserver not fully initialized"
)
......
......@@ -9,8 +9,13 @@ cc_test(enforce_test SRCS enforce_test.cc)
proto_library(attr_type SRCS attr_type.proto)
proto_library(op_proto SRCS op_proto.proto DEPS attr_type)
cc_test(op_proto_test SRCS op_proto_test.cc DEPS op_proto protobuf)
proto_library(net_proto SRCS net_proto.proto DEPS op_proto)
#cc_library(net SRCS net.cc DEPS net_proto attr_type op_proto)
proto_library(op_desc SRCS op_desc.proto DEPS attr_type)
cc_test(op_desc_test SRCS op_desc_test.cc DEPS op_desc protobuf)
cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_proto op_desc)
py_proto_compile(framework_py_proto SRCS attr_type.proto op_proto.proto op_desc.proto)
# Generate an empty __init__.py to make framework_py_proto as a valid python module.
add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
add_dependencies(framework_py_proto framework_py_proto_init)
proto_library(net_proto SRCS net_proto.proto DEPS op_proto)
#cc_library(net SRCS net.cc DEPS net_proto attr_type op_proto)
#pragma once
#include <boost/variant.hpp>
#include <functional>
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/framework/enforce.h"
namespace paddle {
namespace framework {
typedef boost::variant<boost::blank, int, float, std::string, std::vector<int>,
std::vector<float>, std::vector<std::string>>
Attribute;
typedef std::unordered_map<std::string, Attribute> AttributeMap;
// check whether a value(attribute) fit a certain limit
template <typename T>
class LargerThanChecker {
public:
LargerThanChecker(T lower_bound) : lower_bound_(lower_bound) {}
void operator()(T& value) const {
PADDLE_ENFORCE(value > lower_bound_, "larger_than check fail");
}
private:
T lower_bound_;
};
// we can provide users more common Checker, like 'LessThanChecker',
// 'BetweenChecker'...
template <typename T>
class DefaultValueSetter {
public:
DefaultValueSetter(T default_value) : default_value_(default_value) {}
void operator()(T& value) const { value = default_value_; }
private:
T default_value_;
};
// check whether a certain attribute fit its limits
// an attribute can have more than one limits
template <typename T>
class TypedAttrChecker {
typedef std::function<void(T&)> ValueChecker;
public:
TypedAttrChecker(const std::string& attr_name) : attr_name_(attr_name) {}
TypedAttrChecker& LargerThan(const T& lower_bound) {
value_checkers_.push_back(LargerThanChecker<T>(lower_bound));
return *this;
}
// we can add more common limits, like LessThan(), Between()...
TypedAttrChecker& SetDefault(const T& default_value) {
PADDLE_ENFORCE(default_value_setter_.empty(),
"%s can't have more than one default value!", attr_name_);
default_value_setter_.push_back(DefaultValueSetter<T>(default_value));
return *this;
}
// allow users provide their own checker
TypedAttrChecker& AddCustomChecker(const ValueChecker& checker) {
value_checkers_.push_back(checker);
return *this;
}
void operator()(AttributeMap& attr_map) const {
if (!attr_map.count(attr_name_)) {
// user do not set this attr
PADDLE_ENFORCE(!default_value_setter_.empty(),
"Attribute '%s' is required!", attr_name_);
// default_value_setter_ has no more than one element
T val;
(default_value_setter_[0])(val);
attr_map[attr_name_] = val;
}
Attribute& attr = attr_map.at(attr_name_);
T& attr_value = boost::get<T>(attr);
for (const auto& checker : value_checkers_) {
checker(attr_value);
}
}
private:
std::string attr_name_;
std::vector<ValueChecker> value_checkers_;
std::vector<ValueChecker> default_value_setter_;
};
// check whether op's all attributes fit their own limits
class OpAttrChecker {
typedef std::function<void(AttributeMap&)> AttrChecker;
public:
template <typename T>
TypedAttrChecker<T>& AddAttrChecker(const std::string& attr_name) {
attr_checkers_.push_back(TypedAttrChecker<T>(attr_name));
AttrChecker& checker = attr_checkers_.back();
return *(checker.target<TypedAttrChecker<T>>());
}
void Check(AttributeMap& attr_map) const {
for (const auto& checker : attr_checkers_) {
checker(attr_map);
}
}
private:
std::vector<AttrChecker> attr_checkers_;
};
} // namespace framework
} // namespace paddle
#pragma once
#include "paddle/framework/attr_checker.h"
//#include "paddle/framework/op_base.h"
#include "paddle/framework/op_desc.pb.h"
#include "paddle/framework/op_proto.pb.h"
namespace paddle {
namespace framework {
//==================For test================//
class OpBase {
public:
std::vector<std::string> inputs_;
std::vector<std::string> outputs_;
AttributeMap attr_map_;
virtual std::string Run() const = 0;
virtual ~OpBase() {}
};
//=========================================//
// helper class to set attribute type
struct AttrTypeHelper {
template <typename T>
static void SetAttrType(AttrProto* attr);
static Attribute GetAttrValue(const AttrDesc& attr_desc) {
switch (attr_desc.type()) {
case paddle::framework::AttrType::INT: {
return attr_desc.i();
}
case paddle::framework::AttrType::FLOAT: {
return attr_desc.f();
}
case paddle::framework::AttrType::STRING: {
return attr_desc.s();
}
case paddle::framework::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);
}
return val;
}
case paddle::framework::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);
}
return val;
}
case paddle::framework::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);
}
return val;
}
}
PADDLE_ENFORCE(false, "Unknown OpDesc::AttrDesc::type !");
return boost::blank();
}
};
template <>
void AttrTypeHelper::SetAttrType<int>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::INT);
}
template <>
void AttrTypeHelper::SetAttrType<float>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::FLOAT);
}
template <>
void AttrTypeHelper::SetAttrType<std::string>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::STRING);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<int>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::INTS);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<float>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::FLOATS);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<std::string>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::STRINGS);
}
// this class not only make proto but also init attribute checkers.
class OpProtoAndCheckerMaker {
public:
OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: proto_(proto), op_checker_(op_checker) {}
protected:
void AddInput(const std::string& name, const std::string& comment) {
auto input = proto_->mutable_inputs()->Add();
*(input->mutable_name()) = name;
*(input->mutable_comment()) = comment;
}
void AddOutput(const std::string& name, const std::string& comment) {
auto output = proto_->mutable_outputs()->Add();
*(output->mutable_name()) = name;
*(output->mutable_comment()) = comment;
}
template <typename T>
TypedAttrChecker<T>& AddAttr(const std::string& name,
const std::string& comment) {
auto attr = proto_->mutable_attrs()->Add();
*(attr->mutable_name()) = name;
*(attr->mutable_comment()) = comment;
AttrTypeHelper::SetAttrType<T>(attr);
return op_checker_->AddAttrChecker<T>(name);
}
void AddType(const std::string& op_type) { proto_->set_type(op_type); }
void AddComment(const std::string& comment) {
*(proto_->mutable_comment()) = comment;
}
OpProto* proto_;
OpAttrChecker* op_checker_;
};
class OpRegistry {
typedef std::function<OpBase*()> OpCreator;
public:
template <typename OpType, typename ProtoMakerType>
static void RegisterOp(const std::string& op_type) {
creators_[op_type] = []() { return new OpType; };
OpProto& op_proto = protos_[op_type];
OpAttrChecker& op_checker = op_checkers_[op_type];
ProtoMakerType(&op_proto, &op_checker);
PADDLE_ENFORCE(op_proto.IsInitialized() == true,
"Fail to initialize %s's OpProto !", op_type);
}
static OpBase* CreateOp(const OpDesc& op_desc) {
std::string op_type = op_desc.type();
OpBase* op = (creators_.at(op_type))();
(op->inputs_).resize(op_desc.inputs_size());
for (int i = 0; i < op_desc.inputs_size(); ++i) {
(op->inputs_)[i] = op_desc.inputs(i);
}
(op->outputs_).resize(op_desc.outputs_size());
for (int i = 0; i < op_desc.outputs_size(); ++i) {
(op->outputs_)[i] = op_desc.outputs(i);
}
for (int i = 0; i < op_desc.attrs_size(); ++i) {
const AttrDesc& ith_attr = op_desc.attrs(i);
std::string name = ith_attr.name();
(op->attr_map_)[name] = AttrTypeHelper::GetAttrValue(ith_attr);
}
const OpAttrChecker& op_checker = op_checkers_.at(op_type);
op_checker.Check(op->attr_map_);
return op;
}
private:
static std::unordered_map<std::string, OpCreator> creators_;
static std::unordered_map<std::string, OpProto> protos_;
static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
};
std::unordered_map<std::string, std::function<OpBase*()>> OpRegistry::creators_;
std::unordered_map<std::string, OpProto> OpRegistry::protos_;
std::unordered_map<std::string, OpAttrChecker> OpRegistry::op_checkers_;
template <typename OpType, typename ProtoMakerType>
class OpRegisterHelper {
public:
OpRegisterHelper(std::string op_type) {
OpRegistry::RegisterOp<OpType, ProtoMakerType>(op_type);
}
};
#define REGISTER_OP(__op_class, __op_maker_class, __op_type) \
class __op_class##Register { \
private: \
const static OpRegisterHelper<__op_class, __op_maker_class> reg; \
}; \
const OpRegisterHelper<__op_class, __op_maker_class> \
__op_class##Register::reg(#__op_type);
// Demos
class CosineOp : public OpBase {
public:
virtual std::string Run() const {
std::string msg = "CosineOp runs! scale = " +
std::to_string(boost::get<float>(attr_map_.at("scale")));
return msg;
}
};
class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
AddAttr<float>("scale", "scale of cosine op")
.SetDefault(1.0)
.LargerThan(0.0);
AddType("cos");
AddComment("This is cos op");
}
};
REGISTER_OP(CosineOp, CosineOpProtoAndCheckerMaker, cos_sim)
class MyTestOp : public OpBase {
public:
virtual std::string Run() const {
std::string msg =
"MyTestOp runs! test_attr = " +
std::to_string(boost::get<int>(attr_map_.at("test_attr")));
return msg;
}
};
class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
auto my_checker = [](int i) {
PADDLE_ENFORCE(i % 2 == 0, "'test_attr' must be even!");
};
AddAttr<int>("test_attr", "a simple test attribute")
.AddCustomChecker(my_checker);
AddType("my_test_op");
AddComment("This is my_test op");
}
};
REGISTER_OP(MyTestOp, MyTestOpProtoAndCheckerMaker, my_test_op)
} // namespace framework
} // namespace paddle
#include "paddle/framework/op_registry.h"
#include <gtest/gtest.h>
TEST(OpRegistry, CreateOp) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("cos_sim");
op_desc.add_inputs("aa");
op_desc.add_outputs("bb");
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("scale");
attr->set_type(paddle::framework::AttrType::FLOAT);
attr->set_f(3.3);
paddle::framework::OpBase* op =
paddle::framework::OpRegistry::CreateOp(op_desc);
std::string debug_str = op->Run();
std::string str = "CosineOp runs! scale = " + std::to_string(3.3);
ASSERT_EQ(str.size(), debug_str.size());
for (size_t i = 0; i < debug_str.length(); ++i) {
ASSERT_EQ(debug_str[i], str[i]);
}
}
TEST(OpRegistry, IllegalAttr) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("cos_sim");
op_desc.add_inputs("aa");
op_desc.add_outputs("bb");
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("scale");
attr->set_type(paddle::framework::AttrType::FLOAT);
attr->set_f(-2.0);
bool caught = false;
try {
paddle::framework::OpBase* op __attribute__((unused)) =
paddle::framework::OpRegistry::CreateOp(op_desc);
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
std::string msg = "larger_than check fail";
const char* err_msg = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(err_msg[i], msg[i]);
}
}
ASSERT_TRUE(caught);
}
TEST(OpRegistry, DefaultValue) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("cos_sim");
op_desc.add_inputs("aa");
op_desc.add_outputs("bb");
paddle::framework::OpBase* op =
paddle::framework::OpRegistry::CreateOp(op_desc);
std::string debug_str = op->Run();
float default_value = 1.0;
std::string str = "CosineOp runs! scale = " + std::to_string(default_value);
ASSERT_EQ(str.size(), debug_str.size());
for (size_t i = 0; i < debug_str.length(); ++i) {
ASSERT_EQ(debug_str[i], str[i]);
}
}
TEST(OpRegistry, CustomChecker) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("my_test_op");
op_desc.add_inputs("ii");
op_desc.add_outputs("oo");
// attr 'test_attr' is not set
bool caught = false;
try {
paddle::framework::OpBase* op __attribute__((unused)) =
paddle::framework::OpRegistry::CreateOp(op_desc);
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
std::string msg = "Attribute 'test_attr' is required!";
const char* err_msg = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(err_msg[i], msg[i]);
}
}
ASSERT_TRUE(caught);
// set 'test_attr' set to an illegal value
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("test_attr");
attr->set_type(paddle::framework::AttrType::INT);
attr->set_i(3);
caught = false;
try {
paddle::framework::OpBase* op __attribute__((unused)) =
paddle::framework::OpRegistry::CreateOp(op_desc);
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
std::string msg = "'test_attr' must be even!";
const char* err_msg = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(err_msg[i], msg[i]);
}
}
ASSERT_TRUE(caught);
// set 'test_attr' set to a legal value
op_desc.mutable_attrs()->Clear();
attr = op_desc.mutable_attrs()->Add();
attr->set_name("test_attr");
attr->set_type(paddle::framework::AttrType::INT);
attr->set_i(4);
paddle::framework::OpBase* op =
paddle::framework::OpRegistry::CreateOp(op_desc);
std::string debug_str = op->Run();
std::string str = "MyTestOp runs! test_attr = " + std::to_string(4);
ASSERT_EQ(str.size(), debug_str.size());
for (size_t i = 0; i < debug_str.length(); ++i) {
ASSERT_EQ(debug_str[i], str[i]);
}
}
\ No newline at end of file
......@@ -241,7 +241,7 @@ void testBatchState(LayerPtr testLayer,
std::vector<Argument> args;
args.push_back(out);
EXPECT_EQ(0, Argument::sum(args)) << "testBatchState failed";
ASSERT_NEAR(0, Argument::sum(args), 1e-5) << "testBatchState failed";
for (size_t seqId = 0; seqId < numSequences; ++seqId) {
start[seqId] += seqLens[seqId];
}
......
......@@ -27,22 +27,24 @@ void AdadeltaOptimizer::Update(const Tensor* gradient) {
const char* AdadeltaOptimizer::SerializeState(int* state_len) {
AdadeltaOptimizerState state;
// TODO(zhihong) : add lr_policy serialization
state.set_num_sample_passed(num_sample_passed_);
std::string lr_str = this->lr_policy_->SerializeState(state_len);
state.mutable_lr_state()->ParseFromString(lr_str);
TensorToProto(*parameter_, state.mutable_parameter());
TensorToProto(*accum_gradient_, state.mutable_accum_gradient());
TensorToProto(*accum_delta_, state.mutable_accum_delta());
TensorToProto(*update_delta_, state.mutable_update_delta());
auto str = state.SerializeAsString();
*state_len = str.size();
*state_len += str.size();
return str.c_str();
}
void AdadeltaOptimizer::DeserializeState(const std::string& str) {
AdadeltaOptimizerState state;
state.ParseFromString(str);
// TODO(zhihong) : add lr_policy DeserializeState
auto lr_state = state.lr_state();
this->lr_policy_->DeserializeState(lr_state.SerializeAsString());
num_sample_passed_ = state.num_sample_passed();
ProtoToTensor(state.parameter(), parameter_);
......
......@@ -19,20 +19,23 @@ void AdagradOptimizer::Update(const Tensor* gradient) {
}
const char* AdagradOptimizer::SerializeState(int* state_len) {
AdagradOptimizerState state;
// TODO(zhihong) : add lr_policy serialization
state.set_num_sample_passed(num_sample_passed_);
std::string lr_str = this->lr_policy_->SerializeState(state_len);
state.mutable_lr_state()->ParseFromString(lr_str);
TensorToProto(*parameter_, state.mutable_parameter());
TensorToProto(*accum_gradient_, state.mutable_accum_gradient());
auto str = state.SerializeAsString();
*state_len = str.size();
*state_len += str.size();
return str.c_str();
}
void AdagradOptimizer::DeserializeState(const std::string& str) {
AdagradOptimizerState state;
state.ParseFromString(str);
// TODO(zhihong) : add lr_policy DeserializeState
auto lr_state = state.lr_state();
this->lr_policy_->DeserializeState(lr_state.SerializeAsString());
num_sample_passed_ = state.num_sample_passed();
ProtoToTensor(state.parameter(), parameter_);
ProtoToTensor(state.accum_gradient(), accum_gradient_);
......
......@@ -24,20 +24,23 @@ void AdamOptimizer::Update(const Tensor *gradient) {
const char *AdamOptimizer::SerializeState(int *state_len) {
AdamOptimizerState state;
// TODO(zhihong) : add lr_policy serialization
std::string lr_str = this->lr_policy_->SerializeState(state_len);
state.mutable_lr_state()->ParseFromString(lr_str);
state.set_num_sample_passed(num_sample_passed_);
TensorToProto(*parameter_, state.mutable_parameter());
TensorToProto(*momentums_, state.mutable_momentums());
TensorToProto(*velocitys_, state.mutable_velocitys());
auto str = state.SerializeAsString();
*state_len = str.size();
*state_len += str.size();
return str.c_str();
}
void AdamOptimizer::DeserializeState(const std::string &str) {
AdamOptimizerState state;
state.ParseFromString(str);
// TODO(zhihong) : add lr_policy DeserializeState
auto lr_state = state.lr_state();
this->lr_policy_->DeserializeState(lr_state.SerializeAsString());
num_sample_passed_ = state.num_sample_passed();
ProtoToTensor(state.parameter(), parameter_);
......
......@@ -17,36 +17,56 @@ public:
// constant learning rate policy
class ConstLr final : public LrPolicy {
public:
ConstLr(double lr) : learning_rate(lr){};
ConstLr(double lr) : learning_rate_(lr){};
double LearningRate(const uint64_t num_sample_passed) {
return learning_rate;
return learning_rate_;
}
const char *SerializeState(int *state_len) {
LrPolicyState state;
state.set_learning_rate(learning_rate_);
auto str = state.SerializeAsString();
*state_len = str.size();
return str.c_str();
}
void DeserializeState(const std::string &str) {
LrPolicyState state;
state.ParseFromString(str);
learning_rate_ = state.learning_rate();
}
const char *SerializeState(int *state_len) { return nullptr; }
void DeserializeState(const std::string &state) {}
private:
double learning_rate;
double learning_rate_;
};
class LinearLr final : public LrPolicy {
public:
LinearLr(double lr, double lr_decay_a, double lr_decay_b)
: learning_rate(lr), lr_decay_a(lr_decay_a), lr_decay_b(lr_decay_b) {}
: learning_rate_(lr), lr_decay_a_(lr_decay_a), lr_decay_b_(lr_decay_b) {}
double LearningRate(const uint64_t num_sample_passed) {
return std::max(learning_rate - lr_decay_a * num_sample_passed, lr_decay_b);
return std::max(learning_rate_ - lr_decay_a_ * num_sample_passed,
lr_decay_b_);
}
const char *SerializeState(int *state_len) {
// TODO(zhihong) : add lr_policy serialization
return nullptr;
LrPolicyState state;
state.set_learning_rate(learning_rate_);
state.set_lr_decay_a(lr_decay_a_);
state.set_lr_decay_b(lr_decay_b_);
auto str = state.SerializeAsString();
*state_len = str.size();
return str.c_str();
}
void DeserializeState(const std::string &state) {
// TODO(zhihong) : add lr_policy serialization
void DeserializeState(const std::string &str) {
LrPolicyState state;
state.ParseFromString(str);
learning_rate_ = state.learning_rate();
lr_decay_a_ = state.lr_decay_a();
lr_decay_b_ = state.lr_decay_b();
}
private:
double learning_rate;
double lr_decay_a;
double lr_decay_b;
double learning_rate_;
double lr_decay_a_;
double lr_decay_b_;
};
} // namespace optimizer
......
......@@ -30,16 +30,20 @@ void SGDOptimizer::Update(const Tensor *gradient) {
const char *SGDOptimizer::SerializeState(int *state_len) {
SGDOptimizerState state;
state.set_num_sample_passed(num_sample_passed_);
std::string lr_str = this->lr_policy_->SerializeState(state_len);
state.mutable_lr_state()->ParseFromString(lr_str);
TensorToProto(*parameter_, state.mutable_parameter());
if (momentum_ != 0.0) TensorToProto(*momentums_, state.mutable_momentums());
auto str = state.SerializeAsString();
*state_len = str.size();
*state_len += str.size();
return str.c_str();
}
void SGDOptimizer::DeserializeState(const std::string &str) {
SGDOptimizerState state;
state.ParseFromString(str);
auto lr_state = state.lr_state();
this->lr_policy_->DeserializeState(lr_state.SerializeAsString());
num_sample_passed_ = state.num_sample_passed();
ProtoToTensor(state.parameter(), parameter_);
if (momentum_ != 0.0) ProtoToTensor(state.parameter(), momentums_);
......
......@@ -4,3 +4,5 @@ nv_test(cuda_test SRCS cuda_test.cu)
cc_library(place SRCS place.cc)
cc_test(place_test SRCS place_test.cc DEPS place glog gflags)
nv_test(device_context_test SRCS device_context_test.cc DEPS dynamic_loader place eigen3 glog gflags)
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "paddle/framework/enforce.h"
#ifndef PADDLE_ONLY_CPU
#include "paddle/platform/cuda.h"
#include "paddle/platform/dynload/cublas.h"
#include "paddle/platform/dynload/cudnn.h"
#include "paddle/platform/dynload/curand.h"
#define EIGEN_USE_GPU
#endif
#include "paddle/platform/place.h"
#include "unsupported/Eigen/CXX11/Tensor"
namespace paddle {
namespace platform {
class DeviceContext {
public:
virtual ~DeviceContext() {}
};
class CPUDeviceContext : public DeviceContext {};
#ifndef PADDLE_ONLY_CPU
class GPUPlaceGuard {
public:
explicit GPUPlaceGuard(GPUPlace new_place) : previous_(GetCurrentDeviceId()) {
if (previous_ != new_place) {
paddle::platform::SetDeviceId(new_place.device);
}
}
~GPUPlaceGuard() { paddle::platform::SetDeviceId(previous_.device); }
private:
GPUPlace previous_;
};
class CUDADeviceContext : public DeviceContext {
public:
explicit CUDADeviceContext(const GPUPlace gpu_place) : gpu_place_(gpu_place) {
GPUPlaceGuard guard(gpu_place_);
paddle::platform::throw_on_error(cudaStreamCreate(&stream_),
"cudaStreamCreate failed");
eigen_stream_ = new Eigen::CudaStreamDevice(&stream_);
eigen_device_ = new Eigen::GpuDevice(eigen_stream_);
}
void Wait() {
paddle::platform::throw_on_error(cudaStreamSynchronize(stream_),
"cudaStreamSynchronize failed");
}
cudaStream_t stream() { return stream_; }
Eigen::GpuDevice eigen_device() { return *eigen_device_; }
cublasHandle_t cublas_handle() {
if (!blas_handle_) {
GPUPlaceGuard guard(gpu_place_);
PADDLE_ENFORCE(paddle::platform::dynload::cublasCreate(&blas_handle_) ==
CUBLAS_STATUS_SUCCESS,
"cublasCreate failed");
PADDLE_ENFORCE(paddle::platform::dynload::cublasSetStream(
blas_handle_, stream_) == CUBLAS_STATUS_SUCCESS,
"cublasSetStream failed");
}
return blas_handle_;
}
cudnnHandle_t cudnn_handle() {
if (!dnn_handle_) {
GPUPlaceGuard guard(gpu_place_);
PADDLE_ENFORCE(paddle::platform::dynload::cudnnCreate(&dnn_handle_) ==
CUDNN_STATUS_SUCCESS,
"cudnnCreate failed");
PADDLE_ENFORCE(paddle::platform::dynload::cudnnSetStream(
dnn_handle_, stream_) == CUDNN_STATUS_SUCCESS,
"cudnnSetStream failed");
}
return dnn_handle_;
}
curandGenerator_t curand_generator() {
if (!rand_generator_) {
GPUPlaceGuard guard(gpu_place_);
PADDLE_ENFORCE(paddle::platform::dynload::curandCreateGenerator(
&rand_generator_, CURAND_RNG_PSEUDO_DEFAULT) ==
CURAND_STATUS_SUCCESS,
"curandCreateGenerator failed");
PADDLE_ENFORCE(
paddle::platform::dynload::curandSetPseudoRandomGeneratorSeed(
rand_generator_, random_seed_) == CURAND_STATUS_SUCCESS,
"curandSetPseudoRandomGeneratorSeed failed");
PADDLE_ENFORCE(paddle::platform::dynload::curandSetStream(
rand_generator_, stream_) == CURAND_STATUS_SUCCESS,
"curandSetStream failed");
}
return rand_generator_;
}
~CUDADeviceContext() {
Wait();
if (blas_handle_) {
PADDLE_ENFORCE(paddle::platform::dynload::cublasDestroy(blas_handle_) ==
CUBLAS_STATUS_SUCCESS,
"cublasDestroy failed");
}
if (dnn_handle_) {
PADDLE_ENFORCE(paddle::platform::dynload::cudnnDestroy(dnn_handle_) ==
CUDNN_STATUS_SUCCESS,
"cudnnDestroy failed");
}
if (rand_generator_) {
PADDLE_ENFORCE(paddle::platform::dynload::curandDestroyGenerator(
rand_generator_) == CURAND_STATUS_SUCCESS,
"curandDestroyGenerator failed");
}
delete eigen_stream_;
delete eigen_device_;
paddle::platform::throw_on_error(cudaStreamDestroy(stream_),
"cudaStreamDestroy failed");
}
private:
GPUPlace gpu_place_;
cudaStream_t stream_;
Eigen::CudaStreamDevice* eigen_stream_;
Eigen::GpuDevice* eigen_device_;
cublasHandle_t blas_handle_{nullptr};
cudnnHandle_t dnn_handle_{nullptr};
int random_seed_;
curandGenerator_t rand_generator_{nullptr};
};
#endif
} // namespace platform
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/platform/device_context.h"
#include "gtest/gtest.h"
TEST(CUDADeviceContext, Init) {
int count = paddle::platform::GetDeviceCount();
for (int i = 0; i < count; i++) {
paddle::platform::CUDADeviceContext* device_context =
new paddle::platform::CUDADeviceContext(i);
Eigen::GpuDevice gpu_device = device_context->eigen_device();
ASSERT_NE(nullptr, gpu_device.stream());
cudnnHandle_t cudnn_handle = device_context->cudnn_handle();
ASSERT_NE(nullptr, cudnn_handle);
cublasHandle_t cublas_handle = device_context->cublas_handle();
ASSERT_NE(nullptr, cublas_handle);
curandGenerator_t curand_handle = device_context->curand_generator();
ASSERT_NE(nullptr, curand_handle);
delete device_context;
}
}
......@@ -5,13 +5,14 @@ set -e
mkdir -p $TRAVIS_BUILD_DIR/build
cd $TRAVIS_BUILD_DIR/build
# Compile Documentation only.
cmake .. -DCMAKE_BUILD_TYPE=Debug -DWITH_GPU=OFF -DWITH_DOC=OFF -DWITH_STYLE_CHECK=OFF
# Compile paddle binaries first
cmake .. -DCMAKE_BUILD_TYPE=Debug -DWITH_GPU=OFF -DWITH_DOC=OFF -DWITH_GOLANG=ON -DWITH_STYLE_CHECK=OFF
mkdir output
make -j `nproc`
find .. -name '*whl' | xargs pip install # install all wheels.
rm -rf *
# Compile Documentation only.
cmake .. -DCMAKE_BUILD_TYPE=Debug -DWITH_GPU=OFF -DWITH_DOC=ON
make -j `nproc` paddle_docs paddle_docs_cn
......
......@@ -78,11 +78,15 @@ enum DataType {
repeated bytes content = 2;
}
message LrPolicyState {
// learninRate Policy
optional double learning_rate = 1 [default = 1.0];
optional double lr_decay_a = 2;
optional double lr_decay_b = 3;
}
message SGDOptimizerState {
// learning rate policy
optional double learning_rate = 101;
optional double lr_decay_a = 102;
optional double lr_decay_b = 103;
optional LrPolicyState lr_state = 101;
optional double num_sample_passed = 104;
// state
optional TensorProto parameter = 1;
......@@ -91,9 +95,7 @@ message SGDOptimizerState {
message AdadeltaOptimizerState {
// learning rate policy
optional double learning_rate = 101;
optional double lr_decay_a = 102;
optional double lr_decay_b = 103;
optional LrPolicyState lr_state = 101;
optional double num_sample_passed = 104;
// state
optional TensorProto parameter = 1;
......@@ -102,11 +104,9 @@ message AdadeltaOptimizerState {
optional TensorProto update_delta = 4;
}
message AdagradOptimizerState {
// learning rate policy
optional double learning_rate = 101;
optional double lr_decay_a = 102;
optional double lr_decay_b = 103;
optional LrPolicyState lr_state = 101;
optional double num_sample_passed = 104;
// state
optional TensorProto parameter = 1;
......@@ -114,10 +114,7 @@ message AdagradOptimizerState {
}
message AdamOptimizerState {
// learning rate policy
optional double learning_rate = 101;
optional double lr_decay_a = 102;
optional double lr_decay_b = 103;
optional LrPolicyState lr_state = 101;
optional double num_sample_passed = 104;
// state
optional TensorProto parameter = 1;
......
......@@ -29,7 +29,7 @@ configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.in
add_custom_command(OUTPUT ${OUTPUT_DIR}/.timestamp
COMMAND env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
COMMAND ${CMAKE_COMMAND} -E touch ${OUTPUT_DIR}/.timestamp
DEPENDS gen_proto_py ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
DEPENDS gen_proto_py framework_py_proto ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
add_custom_target(paddle_python ALL DEPENDS
${OUTPUT_DIR}/.timestamp)
......@@ -43,6 +43,7 @@ if (WITH_TESTING)
add_subdirectory(paddle/v2/tests)
add_subdirectory(paddle/v2/reader/tests)
add_subdirectory(paddle/v2/plot/tests)
add_subdirectory(paddle/v2/framework/tests)
endif()
endif()
install(DIRECTORY ${PADDLE_PYTHON_PACKAGE_DIR}
......
......@@ -1353,7 +1353,8 @@ class LayerBase(object):
device=None,
active_type="",
drop_rate=0.,
coeff=None):
coeff=None,
error_clipping_threshold=None):
config_assert('@' not in name,
"layer name: %s contain special character @" % name)
global g_current_submodel
......@@ -1387,6 +1388,9 @@ class LayerBase(object):
elif g_default_device is not None:
self.config.device = g_default_device
if error_clipping_threshold is not None:
self.config.error_clipping_threshold = error_clipping_threshold
for input_index in xrange(len(self.inputs)):
input = self.inputs[input_index]
input_config = None
......@@ -2782,13 +2786,7 @@ class TensorLayer(LayerBase):
@config_layer('mixed')
class MixedLayer(LayerBase):
def __init__(self,
name,
inputs,
size=0,
bias=True,
error_clipping_threshold=None,
**xargs):
def __init__(self, name, inputs, size=0, bias=True, **xargs):
config_assert(inputs, 'inputs cannot be empty')
super(MixedLayer, self).__init__(
name, 'mixed', size, inputs=inputs, **xargs)
......@@ -2870,9 +2868,6 @@ class MixedLayer(LayerBase):
self.config.bias_size = psize
self.create_bias_parameter(bias, psize)
if error_clipping_threshold is not None:
self.config.error_clipping_threshold = error_clipping_threshold
# like MixedLayer, but no bias parameter
@config_func
......
......@@ -4805,6 +4805,14 @@ def maxout_layer(input, groups, num_channels=None, name=None, layer_attr=None):
So groups should be larger than 1, and the num of channels should be able
to devided by groups.
.. math::
y_{si+j} = \max_k x_{gsi + sk + j}
g = groups
s = input.size / num_channels
0 \le i < num_channels / groups
0 \le j < s
0 \le k < groups
Please refer to Paper:
- Maxout Networks: http://www.jmlr.org/proceedings/papers/v28/goodfellow13.pdf
- Multi-digit Number Recognition from Street View \
......
add_python_test(test_framework test_protobuf.py)
import paddle.v2.framework.proto.op_proto_pb2
import paddle.v2.framework.proto.attr_type_pb2
import unittest
class TestFrameworkProto(unittest.TestCase):
def test_all(self):
op_proto_lib = paddle.v2.framework.proto.op_proto_pb2
attr_type_lib = paddle.v2.framework.proto.attr_type_pb2
op_proto = op_proto_lib.OpProto()
ipt0 = op_proto.inputs.add()
ipt0.name = "a"
ipt0.comment = "the input of cosine op"
ipt1 = op_proto.inputs.add()
ipt1.name = "b"
ipt1.comment = "the other input of cosine op"
opt = op_proto.outputs.add()
opt.name = "output"
opt.comment = "the output of cosine op"
op_proto.comment = "cosine op, output = scale*cos(a, b)"
attr = op_proto.attrs.add()
attr.name = "scale"
attr.comment = "scale of cosine op"
attr.type = attr_type_lib.FLOAT
op_proto.type = "cos"
self.assertTrue(op_proto.IsInitialized())
......@@ -26,14 +26,22 @@ class client(object):
holder[idx] = c_ptr
lib.paddle_set_dataset(self.c, holder, len(paths))
# return format: (record, errno)
# errno = 0: ok
# < 0: error
def next_record(self):
p = ctypes.c_char_p()
ret = ctypes.pointer(p)
size = lib.paddle_next_record(self.c, ret)
if size < 0:
# Error
return None, size
if size == 0:
# Empty record
return ""
return "", 0
record = ret.contents.value[:size]
# Memory created from C should be freed.
lib.mem_free(ret.contents)
return record
return record, 0
......@@ -57,17 +57,20 @@ def text_file(path):
return reader
def recordio(path):
def recordio_local(paths, buf_size=100):
"""
Creates a data reader that outputs record one one by one from given recordio file
:path: path of recordio file
:returns: data reader of recordio file
Creates a data reader from given RecordIO file paths separated by ",",
glob pattern is supported.
:path: path of recordio files.
:returns: data reader of recordio files.
"""
import recordio as rec
import paddle.v2.reader.decorator as dec
def reader():
f = rec.reader(path)
a = ','.join(paths)
f = rec.reader(a)
while True:
r = f.read()
if r is None:
......@@ -75,4 +78,38 @@ def recordio(path):
yield r
f.close()
return dec.buffered(reader, buf_size)
def recordio(paths, buf_size=100):
"""
Creates a data reader that outputs record one one by one
from given local or cloud recordio path.
:path: path of recordio files.
:returns: data reader of recordio files.
"""
import os
import paddle.v2.master.client as cloud
if "KUBERNETES_SERVICE_HOST" not in os.environ.keys():
return recordio_local(paths)
host_name = "MASTER_SERVICE_HOST"
if host_name not in os.environ.keys():
raise Exception('not find ' + host_name + ' in environ.')
addr = os.environ(host)
def reader():
c = cloud(addr, buf_size)
c.set_dataset(paths)
while True:
r, err = client.next_record()
if err < 0:
break
yield r
c.close()
return reader
......@@ -38,7 +38,7 @@ class TestRecordIO(unittest.TestCase):
def test_recordio(self):
path = os.path.join(
os.path.dirname(__file__), "test_recordio_creator.dat")
reader = paddle.v2.reader.creator.recordio(path)
reader = paddle.v2.reader.creator.recordio([path])
for idx, r in enumerate(reader()):
self.assertSequenceEqual(r, str(idx))
......
......@@ -9,7 +9,9 @@ packages=['paddle',
'paddle.v2.dataset',
'paddle.v2.reader',
'paddle.v2.master',
'paddle.v2.plot']
'paddle.v2.plot',
'paddle.v2.framework',
'paddle.v2.framework.proto']
setup_requires=["requests",
"numpy",
......@@ -27,8 +29,11 @@ setup(name='paddle',
description='Parallel Distributed Deep Learning',
install_requires=setup_requires,
packages=packages,
package_data={'paddle.v2.master': ['${paddle_master_LIB_NAME}'], },
package_data={'paddle.v2.master': ['libpaddle_master.so'], },
package_dir={
'': '${CMAKE_CURRENT_SOURCE_DIR}'
'': '${CMAKE_CURRENT_SOURCE_DIR}',
# The paddle.v2.framework.proto will be generated while compiling.
# So that package points to other directory.
'paddle.v2.framework.proto': '${PROJ_BINARY_ROOT}/paddle/framework'
},
)
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