提交 36f8b848 编写于 作者: D dzhwinter 提交者: GitHub

Merge branch 'develop' into go_optimizer

language: cpp
cache:
directories:
- $HOME/third_party
- $HOME/.ccache
- $HOME/.cache/pip
- $TRAVIS_BUILD_DIR/build/third_party
sudo: required
dist: trusty
os:
- linux
env:
- JOB=DOCS
- JOB=BUILD_AND_TEST
- JOB=PRE_COMMIT
- JOB=build_doc
- JOB=check_style
addons:
apt:
packages:
- gcc-4.8
- g++-4.8
- gfortran-4.8
- git
- build-essential
- python
......@@ -34,18 +32,7 @@ addons:
- libtool
- ccache
before_install:
- |
if [ ${JOB} == "BUILD_AND_TEST" ]; then
local change_list=`git diff --name-only $TRAVIS_COMMIT_RANGE`
if [ $? -eq 0 ]; then # if git diff return no zero, then rerun unit test.
if ! echo ${change_list} | grep -qvE '(\.md$)|(\.rst$)|(\.jpg$)|(\.png$)'
then
echo "Only markdown docs were updated, stopping build process."
exit
fi
fi
fi
- if [[ "$JOB" == "PRE_COMMIT" ]]; then sudo ln -s /usr/bin/clang-format-3.8 /usr/bin/clang-format; fi
- if [[ "$JOB" == "check_style" ]]; then sudo ln -s /usr/bin/clang-format-3.8 /usr/bin/clang-format; fi
# Paddle is using protobuf 3.1 currently. Protobuf 3.2 breaks the compatibility. So we specify the python
# protobuf version.
- pip install numpy wheel 'protobuf==3.1' sphinx==1.5.6 recommonmark sphinx-rtd-theme==0.1.9 virtualenv pre-commit requests==2.9.2 LinkChecker
......@@ -55,7 +42,7 @@ before_install:
function timeout() { perl -e 'alarm shift; exec @ARGV' "$@"; }
script:
- |
timeout 2580 paddle/scripts/travis/main.sh # 43min timeout
timeout 2580 paddle/scripts/travis/${JOB}.sh # 43min timeout
RESULT=$?; if [ $RESULT -eq 0 ] || [ $RESULT -eq 142 ]; then true; else false; fi;
notifications:
email:
......
......@@ -27,6 +27,7 @@ if(NOT CMAKE_CROSSCOMPILING)
endif(NOT CMAKE_CROSSCOMPILING)
find_package(Git REQUIRED)
find_package(Threads REQUIRED)
find_package(Boost QUIET)
include(simd)
......@@ -71,7 +72,7 @@ if(ANDROID)
"Disable RDMA when cross-compiling for Android" FORCE)
endif(ANDROID)
set(THIRD_PARTY_PATH "${PROJ_ROOT}/third_party" CACHE STRING
set(THIRD_PARTY_PATH "${CMAKE_BINARY_DIR}/third_party" CACHE STRING
"A path setting third party libraries download & build directories.")
if (WITH_C_API AND WITH_PYTHON)
......@@ -92,6 +93,7 @@ include(external/openblas) # download, build, install openblas
include(external/swig) # download, build, install swig
include(external/warpctc) # download, build, install warpctc
include(external/any) # download libn::any
include(external/eigen) # download eigen3
include(generic) # simplify cmake module
include(package) # set paddle packages
......@@ -109,6 +111,7 @@ include_directories("${PROJ_ROOT}")
include_directories("${PROJ_ROOT}/paddle/cuda/include")
include_directories("${CMAKE_CURRENT_BINARY_DIR}/proto")
include_directories("${CMAKE_CURRENT_BINARY_DIR}/go/pserver/cclient")
include_directories(${Boost_INCLUDE_DIRS})
set(EXTERNAL_LIBS
${GFLAGS_LIBRARIES}
......
......@@ -25,7 +25,7 @@ COPY ./paddle/scripts/docker/root/ /root/
RUN apt-get update && \
apt-get install -y \
git python-pip python-dev openssh-server bison \
wget unzip tar xz-utils bzip2 gzip coreutils \
wget unzip tar xz-utils bzip2 gzip coreutils ntp \
curl sed grep graphviz libjpeg-dev zlib1g-dev \
python-numpy python-matplotlib gcc g++ \
automake locales clang-format-3.8 swig doxygen cmake \
......
INCLUDE(ExternalProject)
SET(EIGEN_SOURCE_DIR ${THIRD_PARTY_PATH}/eigen3)
INCLUDE_DIRECTORIES(${EIGEN_SOURCE_DIR}/src/eigen3)
ExternalProject_Add(
eigen3
${EXTERNAL_PROJECT_LOG_ARGS}
# for latest version, please get from official website
# URL "https://bitbucket.org/eigen/eigen/get/3.3.4.tar.gz"
# URL_MD5 "1a47e78efe365a97de0c022d127607c3"
# for no-ssl http support, please get from bazel's mirror
# URL "http://mirror.bazel.build/bitbucket.org/eigen/eigen/get/f3a22f35b044.tar.gz"
# URL_MD5 "4645c66075982da6fa0bcf6b20f3e8f7"
# get from github mirror
GIT_REPOSITORY "https://github.com/RLovelett/eigen.git"
GIT_TAG "a46d2e7337c4656f00abe54a8115f6d76153a048"
PREFIX ${EIGEN_SOURCE_DIR}
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
LIST(APPEND external_project_dependencies eigen3)
......@@ -21,7 +21,8 @@ IF(NOT ${CBLAS_FOUND})
SET(CBLAS_INSTALL_DIR ${THIRD_PARTY_PATH}/install/openblas)
SET(CBLAS_INC_DIR "${CBLAS_INSTALL_DIR}/include" CACHE PATH "openblas include directory." FORCE)
SET(CBLAS_LIBRARIES "${CBLAS_INSTALL_DIR}/lib/${LIBRARY_PREFIX}openblas${STATIC_LIBRARY_SUFFIX}"
SET(CBLAS_LIBRARIES
"${CBLAS_INSTALL_DIR}/lib/${CMAKE_STATIC_LIBRARY_PREFIX}openblas${CMAKE_STATIC_LIBRARY_SUFFIX}"
CACHE FILEPATH "openblas library." FORCE)
SET(COMMON_ARGS CC=${CMAKE_C_COMPILER} NO_SHARED=1 NO_LAPACK=1 libs)
......
......@@ -13,12 +13,53 @@
# limitations under the License.
INCLUDE(ExternalProject)
# Always invoke `FIND_PACKAGE(Protobuf)` for importing function protobuf_generate_cpp
FIND_PACKAGE(Protobuf QUIET)
SET(PROTOBUF_FOUND "OFF")
# Print and set the protobuf library information,
# finish this cmake process and exit from this file.
macro(PROMPT_PROTOBUF_LIB)
SET(protobuf_DEPS ${ARGN})
MESSAGE(STATUS "Protobuf protoc executable: ${PROTOBUF_PROTOC_EXECUTABLE}")
MESSAGE(STATUS "Protobuf library: ${PROTOBUF_LIBRARY}")
MESSAGE(STATUS "Protobuf version: ${PROTOBUF_VERSION}")
INCLUDE_DIRECTORIES(${PROTOBUF_INCLUDE_DIR})
# Assuming that all the protobuf libraries are of the same type.
IF(${PROTOBUF_LIBRARY} MATCHES "${CMAKE_STATIC_LIBRARY_SUFFIX}$")
SET(protobuf_LIBTYPE STATIC)
ELSEIF(${PROTOBUF_LIBRARY} MATCHES "${CMAKE_SHARED_LIBRARY_SUFFIX}$")
SET(protobuf_LIBTYPE SHARED)
ELSE()
MESSAGE(FATAL_ERROR "Unknown library type: ${PROTOBUF_LIBRARY}")
ENDIF()
ADD_LIBRARY(protobuf ${protobuf_LIBTYPE} IMPORTED GLOBAL)
SET_PROPERTY(TARGET protobuf PROPERTY IMPORTED_LOCATION ${PROTOBUF_LIBRARY})
ADD_LIBRARY(protobuf_lite ${protobuf_LIBTYPE} IMPORTED GLOBAL)
SET_PROPERTY(TARGET protobuf_lite PROPERTY IMPORTED_LOCATION ${PROTOBUF_LITE_LIBRARY})
ADD_LIBRARY(libprotoc ${protobuf_LIBTYPE} IMPORTED GLOBAL)
SET_PROPERTY(TARGET libprotoc PROPERTY IMPORTED_LOCATION ${PROTOC_LIBRARY})
ADD_EXECUTABLE(protoc IMPORTED GLOBAL)
SET_PROPERTY(TARGET protoc PROPERTY IMPORTED_LOCATION ${PROTOBUF_PROTOC_EXECUTABLE})
# FIND_Protobuf.cmake uses `Protobuf_PROTOC_EXECUTABLE`.
# make `protobuf_generate_cpp` happy.
SET(Protobuf_PROTOC_EXECUTABLE ${PROTOBUF_PROTOC_EXECUTABLE})
FOREACH(dep ${protobuf_DEPS})
ADD_DEPENDENCIES(protobuf ${dep})
ADD_DEPENDENCIES(protobuf_lite ${dep})
ADD_DEPENDENCIES(libprotoc ${dep})
ADD_DEPENDENCIES(protoc ${dep})
ENDFOREACH()
LIST(APPEND external_project_dependencies protobuf)
RETURN()
endmacro()
macro(SET_PROTOBUF_VERSION)
......@@ -43,22 +84,23 @@ if (NOT "${PROTOBUF_ROOT}" STREQUAL "")
endif()
FUNCTION(build_protobuf TARGET_NAME BUILD_FOR_HOST)
SET(PROTOBUF_SOURCES_DIR ${THIRD_PARTY_PATH}/${TARGET_NAME})
SET(PROTOBUF_INSTALL_DIR ${THIRD_PARTY_PATH}/install/${TARGET_NAME})
STRING(REPLACE "extern_" "" TARGET_DIR_NAME "${TARGET_NAME}")
SET(PROTOBUF_SOURCES_DIR ${THIRD_PARTY_PATH}/${TARGET_DIR_NAME})
SET(PROTOBUF_INSTALL_DIR ${THIRD_PARTY_PATH}/install/${TARGET_DIR_NAME})
SET(${TARGET_NAME}_INCLUDE_DIR "${PROTOBUF_INSTALL_DIR}/include" PARENT_SCOPE)
SET(PROTOBUF_INCLUDE_DIR "${PROTOBUF_INSTALL_DIR}/include" PARENT_SCOPE)
SET(${TARGET_NAME}_LITE_LIBRARY
"${PROTOBUF_INSTALL_DIR}/lib/libprotobuf-lite${STATIC_LIBRARY_SUFFIX}"
"${PROTOBUF_INSTALL_DIR}/lib/libprotobuf-lite${CMAKE_STATIC_LIBRARY_SUFFIX}"
PARENT_SCOPE)
SET(${TARGET_NAME}_LIBRARY
"${PROTOBUF_INSTALL_DIR}/lib/libprotobuf${STATIC_LIBRARY_SUFFIX}"
"${PROTOBUF_INSTALL_DIR}/lib/libprotobuf${CMAKE_STATIC_LIBRARY_SUFFIX}"
PARENT_SCOPE)
SET(${TARGET_NAME}_PROTOC_LIBRARY
"${PROTOBUF_INSTALL_DIR}/lib/libprotoc${STATIC_LIBRARY_SUFFIX}"
"${PROTOBUF_INSTALL_DIR}/lib/libprotoc${CMAKE_STATIC_LIBRARY_SUFFIX}"
PARENT_SCOPE)
SET(${TARGET_NAME}_PROTOC_EXECUTABLE
"${PROTOBUF_INSTALL_DIR}/bin/protoc${EXECUTABLE_SUFFIX}"
"${PROTOBUF_INSTALL_DIR}/bin/protoc${CMAKE_EXECUTABLE_SUFFIX}"
PARENT_SCOPE)
SET(OPTIONAL_CACHE_ARGS "")
......@@ -109,6 +151,8 @@ IF(NOT CMAKE_CROSSCOMPILING)
SET_PROTOBUF_VERSION()
IF("${PROTOBUF_VERSION}" VERSION_LESS "3.1.0")
SET(PROTOBUF_FOUND OFF)
ELSE()
PROMPT_PROTOBUF_LIB()
ENDIF()
ENDIF(PROTOBUF_FOUND)
ELSE()
......@@ -120,18 +164,22 @@ ELSE()
ENDIF()
IF(NOT PROTOBUF_FOUND)
build_protobuf(protobuf FALSE)
LIST(APPEND external_project_dependencies protobuf)
build_protobuf(extern_protobuf FALSE)
SET(PROTOBUF_INCLUDE_DIR ${protobuf_INCLUDE_DIR}
SET(PROTOBUF_INCLUDE_DIR ${extern_protobuf_INCLUDE_DIR}
CACHE PATH "protobuf include directory." FORCE)
IF(NOT CMAKE_CROSSCOMPILING)
SET(PROTOBUF_PROTOC_EXECUTABLE ${protobuf_PROTOC_EXECUTABLE}
SET(PROTOBUF_LITE_LIBRARY ${extern_protobuf_LITE_LIBRARY}
CACHE FILEPATH "protobuf lite library." FORCE)
SET(PROTOBUF_LIBRARY ${extern_protobuf_LIBRARY}
CACHE FILEPATH "protobuf library." FORCE)
SET(PROTOBUF_PROTOC_LIBRARY ${extern_protobuf_PROTOC_LIBRARY}
CACHE FILEPATH "protoc library." FORCE)
IF(CMAKE_CROSSCOMPILING)
PROMPT_PROTOBUF_LIB(protobuf_host extern_protobuf)
ELSE()
SET(PROTOBUF_PROTOC_EXECUTABLE ${extern_protobuf_PROTOC_EXECUTABLE}
CACHE FILEPATH "protobuf executable." FORCE)
PROMPT_PROTOBUF_LIB(extern_protobuf)
ENDIF()
SET(PROTOBUF_LITE_LIBRARY ${protobuf_LITE_LIBRARY} CACHE FILEPATH "protobuf lite library." FORCE)
SET(PROTOBUF_LIBRARY ${protobuf_LIBRARY} CACHE FILEPATH "protobuf library." FORCE)
SET(PROTOBUF_PROTOC_LIBRARY ${protobuf_PROTOC_LIBRARY} CACHE FILEPATH "protoc library." FORCE)
ENDIF(NOT PROTOBUF_FOUND)
PROMPT_PROTOBUF_LIB()
\ No newline at end of file
......@@ -77,6 +77,18 @@
# /cmake/external/*.cmake:
#
# cc_test(example_test SRCS example_test.cc DEPS example glog gflags)
#
# To build a go static library using Golang, use the go_ prefixed version:
#
# go_library(example STATIC)
#
# To build a go shared library using Golang, use the go_ prefixed version:
#
# go_library(example SHARED)
#
# including binary directory for generated headers.
include_directories(${CMAKE_BINARY_DIR})
if(NOT APPLE)
find_package(Threads REQUIRED)
......@@ -246,42 +258,53 @@ endfunction(nv_test)
set(GOPATH "${CMAKE_CURRENT_BINARY_DIR}/go")
file(MAKE_DIRECTORY ${GOPATH})
set(PADDLE_IN_GOPATH "${GOPATH}/src/github.com/PaddlePaddle/Paddle")
# Because api.go defines a GO wrapper to ops and tensor, it depends on
# both. This implies that if any of tensor.{h,cc}, ops.{h,cu}, or
# api.go is changed, api need to be re-built.
# go_library(api
# SRCS
# api.go
# DEPS
# tensor # Because ops depend on tensor, this line is optional.
# ops)
function(go_library TARGET_NAME)
set(options OPTIONAL)
set(options STATIC static SHARED shared)
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS)
set(multiValueArgs DEPS)
cmake_parse_arguments(go_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
if (${go_library_OPTIONAL} STREQUAL "SHARED")
if (go_library_SHARED OR go_library_shared)
set(BUILD_MODE "-buildmode=c-shared")
if(APPLE)
set(LIB_NAME "lib${TARGET_NAME}.dylib")
set(LIB_NAME "${CMAKE_SHARED_LIBRARY_PREFIX}${TARGET_NAME}${CMAKE_SHARED_LIBRARY_SUFFIX}")
else()
set(LIB_NAME "lib${TARGET_NAME}.so")
set(BUILD_MODE "-buildmode=c-archive")
set(LIB_NAME "${CMAKE_STATIC_LIBRARY_PREFIX}${TARGET_NAME}${CMAKE_STATIC_LIBRARY_SUFFIX}")
endif()
# Add dummy code to support `make target_name` under Terminal Command
set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}_dummy.c)
file(WRITE ${dummyfile} "const char * dummy = \"${dummyfile}\";")
if (go_library_SHARED OR go_library_shared)
add_library(${TARGET_NAME} SHARED ${dummyfile})
else()
set(BUILD_MODE "-buildmode=c-archive")
set(LIB_NAME "lib${TARGET_NAME}.a")
add_library(${TARGET_NAME} STATIC ${dummyfile})
endif()
add_custom_command(OUTPUT ${TARGET_NAME}_timestamp
if(go_library_DEPS)
add_dependencies(${TARGET_NAME} ${go_library_DEPS})
endif(go_library_DEPS)
# we need to symlink Paddle directory into GOPATH. If we
# don't do it and we have code that depends on Paddle, go
# get ./... will download a new Paddle repo from Github,
# without the changes in our current Paddle repo that we
# want to build.
file(GLOB GO_SOURCE RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.go")
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND rm "${CMAKE_CURRENT_BINARY_DIR}/${LIB_NAME}"
# Symlink Paddle directory into GOPATH
COMMAND mkdir -p ${PADDLE_IN_GOPATH}
COMMAND rm -rf ${PADDLE_IN_GOPATH}
COMMAND ln -sf ${CMAKE_SOURCE_DIR} ${PADDLE_IN_GOPATH}
# Automatically get all dependencies specified in the source code
COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} get -d ./...
# Golang build source code
COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build ${BUILD_MODE}
-o "${CMAKE_CURRENT_BINARY_DIR}/${LIB_NAME}"
${go_library_SRCS}
${GO_SOURCE}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
add_custom_target(${TARGET_NAME}_lib ALL DEPENDS ${TARGET_NAME}_timestamp ${go_library_DEPS})
add_library(${TARGET_NAME} STATIC IMPORTED)
set_property(TARGET ${TARGET_NAME} PROPERTY
IMPORTED_LOCATION "${CMAKE_CURRENT_BINARY_DIR}/${LIB_NAME}")
add_dependencies(${TARGET_NAME} ${TARGET_NAME}_lib)
endfunction(go_library)
function(go_binary TARGET_NAME)
......@@ -312,9 +335,12 @@ function(go_test TARGET_NAME)
add_test(${TARGET_NAME} ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME})
endfunction(go_test)
# go_extern will download extern go project.
# go_extern(target_name extern_source)
# go_extern(go_redis github.com/hoisie/redis)
function(go_extern TARGET_NAME)
add_custom_target(${TARGET_NAME} env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} get ${ARGN})
endfunction(go_extern)
function(proto_library TARGET_NAME)
set(oneValueArgs "")
set(multiValueArgs SRCS)
cmake_parse_arguments(proto_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(proto_srcs)
set(proto_hdrs)
protobuf_generate_cpp(proto_srcs proto_hdrs ${proto_library_SRCS})
cc_library(${TARGET_NAME} SRCS ${proto_srcs} DEPS protobuf)
endfunction()
......@@ -33,6 +33,7 @@ ELSE(WIN32)
SET(CMAKE_OSX_DEPLOYMENT_TARGET ${MACOS_VERSION} CACHE STRING
"Minimum OS X version to target for deployment (at runtime); newer APIs weak linked. Set to empty string for default value.")
ENDIF()
set(CMAKE_EXE_LINKER_FLAGS "-framework CoreFoundation -framework Security")
ELSE(APPLE)
IF(EXISTS "/etc/issue")
......@@ -84,24 +85,6 @@ IF(DEFINED CMAKE_SYSTEM_NAME)
ENDIF()
ENDIF()
# prefix and suffix on different os
IF(WIN32)
SET(LIBRARY_PREFIX "")
SET(SHARED_LIBRARY_SUFFIX ".dll")
SET(STATIC_LIBRARY_SUFFIX ".lib")
SET(EXECUTABLE_SUFFIX ".exe")
ELSE(WIN32)
SET(LIBRARY_PREFIX "lib")
IF(APPLE)
SET(SHARED_LIBRARY_SUFFIX ".dylib")
ELSE(APPLE)
SET(SHARED_LIBRARY_SUFFIX ".so")
ENDIF(APPLE)
SET(STATIC_LIBRARY_SUFFIX ".a")
SET(EXECUTABLE_SUFFIX "")
ENDIF(WIN32)
# external dependencies log output
SET(EXTERNAL_PROJECT_LOG_ARGS
LOG_DOWNLOAD 0 # Wrap download in script to log output
......
......@@ -27,10 +27,6 @@ sphinx_add_target(paddle_docs
${CMAKE_CURRENT_SOURCE_DIR}
${SPHINX_HTML_DIR_EN})
add_dependencies(paddle_docs
gen_proto_py)
# configured documentation tools and intermediate build results
set(BINARY_BUILD_DIR_CN "${CMAKE_CURRENT_BINARY_DIR}/cn/_build")
......@@ -51,6 +47,3 @@ sphinx_add_target(paddle_docs_cn
${SPHINX_CACHE_DIR_CN}
${CMAKE_CURRENT_SOURCE_DIR}
${SPHINX_HTML_DIR_CN})
add_dependencies(paddle_docs_cn
gen_proto_py)
......@@ -99,3 +99,12 @@ value_printer
.. automodule:: paddle.v2.evaluator
:members: value_printer
:noindex:
Detection
=====
detection_map
-------------
.. automodule:: paddle.v2.evaluator
:members: detection_map
:noindex:
# Design of Scope in Paddle
## Overview
Scope is an important concept in programming languages, which defines a program region that a set of bindings between names and entities applies. In a specific scope, a valid name is uniquely associated with an entity, such as a variable. And in another scope, this name may refer to other entity or nothing at all. It clearly restricts the visibility and validity of names in a program. Hence **Scope** is introduced to PaddlePaddle to manage variables in context. But different from the original abstract concept, Scope now becomes an object with two important attributes:
- Scope is an association of a name to variable.
- Variables in a parent scope can be retrieved from local scope.
A detailed explanation of these two attributes goes as following.
## Scope is an association of a name to variable.
Scope is an association of a name to variable. All variables belong to `Scope`. You need to specify a scope to run a Net, i.e., `net.Run(&scope)`. One net can run in different scopes and update different variable in the scope.
1. Scope only contains a map of a name to variable.
All parameters, data, states in a Net should be variables and stored inside a scope. Each op should get inputs and outputs to do computation from a scope, such as data buffer, state(momentum) etc.
1. Variable can only be created by Scope and a variable can only be got from Scope. User cannot create or get a variable outside a scope. This is a constraints of our framework, and will keep our framework simple and clear.
1. Scope only contains methods that are used to Create and Get Variables. Scope do not contain Operators and have no information to run them.
`Net` is designed to drive the computation and Scope only contains a map of variables. There is no computation logic inside a `Scope`. Scope just handles the lifetime management of variables.
- `Create` is used to create a Variable by its name and add the mapping relation.
- `Get` is used to find a Variable by name.
1. Every variable only belongs to one certain Scope.
Variable can not belong to many scopes. If you want to use variables from parent scope, you can use `parent scope`.
1. Scope should destruct all Variables inside it when itself is destructed. User can never store `Variable` pointer somewhere else.
Because Variable can only be got from Scope. When destroying Scope, we also need to destroy all the Variables in it. If user store `Variable` pointer to private data member or some global variable, the pointer will be a invalid pointer when associated `Scope` is destroyed.
```cpp
class Scope {
public:
Variable* CreateVariable(const std::string& name);
const Variable* GetVariable(const std::string& name) const;
private:
std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
};
```
## Parent scope and local scope
Just like [scope](https://en.wikipedia.org/wiki/Scope_(computer_science)) in programming languages, `Scope` in the neural network can also be a local scope. There are two attributes about local scope.
1. We can create local variables in a local scope. When that local scope are destroyed, all local variables should also be destroyed.
2. Variables in a parent scope can be retrieved from local scopes of that parent scope, i.e., when user get a variable from a scope, it will try to search this variable in current scope. If there is no such variable in the local scope, `scope` will keep searching from its parent, until the variable is found or there is no parent.
```cpp
class Scope {
public:
Scope(const std::shared_ptr<Scope>& scope): parent_(scope) {}
Variable* GetVariable(const std::string& name) const {
auto it = vars_.find(name);
if (it != vars_.end()) {
return it->second.get();
} else if (parent_ != nullptr) {
return parent_->GetVariable(name);
} else {
return nullptr;
}
}
private:
std::shared_ptr<Scope> parent_ {nullptr};
};
```
In `Scope` class, there is a private data member called `parent_`. `parent_` is a smart pointer to its parent scope. When user `Get` a variable by its `name`, the `name` will be searched inside the current scope. If the variable cannot be found locally and parent scope is not a `nullptr`, the variable will be searched inside that parent scope. `parent_` pointer's default value is `nullptr`. It means that the scope is a global scope when `parent_` is nullptr.
A local scope is very useful when we implement Recurrent Neural Network. Each timestep of an RNN should be a `Net`. Each `Net` of timestep (`StepNet` for short) should use an independent local scope. Just like variables in a while loop is inside a local scope in programming languages. By using a single `StepNet` and changing local scope, we can implement an RNN easily.
# Interface Design
```cpp
class Variable {
private:
Variable() = default;
friend class Scope;
};
class Scope {
private:
Scope(const std::shared_ptr<Scope>& parent = nullptr);
public:
static std::shared_ptr<Scope> Create(const std::shared_ptr<Scope>& parent = nullptr);
// return nullptr if not found.
Variable* GetVariable(const std::string& name) const;
// return if already contains same name variable.
Variable* CreateVariable(const std::string& name);
private:
std::shared_ptr<Scope> parent_;
std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
};
```
## Only scope can create a variable
To ensure `only scope can create a variable`, we should mark `Variable`'s constructor as a private member function, and Scope is a friend class of Variable. And then only `CreateVariable` can construct `Variable`.
## When scope destroyed, all variables inside this scope should be destroyed together
The scope hold unique pointers for all variables. User can `GetVariable` from scope, but he should not hold this pointer as a member variable. Because when scope is destroyed, all variables inside this scope will be destroyed together.
## Sharing a parent scope
Local scope contains a `parent_` pointer. It is a linked-list for scopes. Using a `shared_ptr` because when a local scope is using, its parents cannot be destroyed.
Also, as the parent scope is a `shared_ptr`, we can only `Create()` a scope shared pointer. We cannot construct a scope variable, because it cannot be passed to other scope as `parent` pointer.
## Orthogonal interface
`GetVariable` will return `nullptr` when `name` is not found. It can be used as `Contains` method. `CreateVariable` will return a `Error` when there is a name conflict locally. Combine `GetVariable` and `CreateVariable`, we can implement `CreateOrGetVariable` easily.
......@@ -111,7 +111,7 @@ PaddlePaddle支持不同类型的输入数据,主要包括四种类型,和
# define training dataset reader
def train_reader():
train_x = np.array([[1, 1], [1, 2], [3, 4], [5, 2]])
train_y = np.array([-2, -3, -7, -7])
train_y = np.array([[-2], [-3], [-7], [-7]])
def reader():
for i in xrange(train_y.shape[0]):
yield train_x[i], train_y[i]
......
if(NOT CMAKE_Go_COMPILER)
if(NOT $ENV{GO_COMPILER} STREQUAL "")
get_filename_component(CMAKE_Go_COMPILER_INIT $ENV{GO_COMPILER} PROGRAM PROGRAM_ARGS CMAKE_Go_FLAGS_ENV_INIT)
if(CMAKE_Go_FLAGS_ENV_INIT)
set(CMAKE_Go_COMPILER_ARG1 "${CMAKE_Go_FLAGS_ENV_INIT}" CACHE STRING "First argument to Go compiler")
endif()
if(NOT EXISTS ${CMAKE_Go_COMPILER_INIT})
message(SEND_ERROR "Could not find compiler set in environment variable GO_COMPILER:\n$ENV{GO_COMPILER}.")
endif()
endif()
set(Go_BIN_PATH
$ENV{GOPATH}
$ENV{GOROOT}
$ENV{GOROOT}/../bin
$ENV{GO_COMPILER}
/usr/bin
/usr/local/bin
)
if(CMAKE_Go_COMPILER_INIT)
set(CMAKE_Go_COMPILER ${CMAKE_Go_COMPILER_INIT} CACHE PATH "Go Compiler")
else()
find_program(CMAKE_Go_COMPILER
NAMES go
PATHS ${Go_BIN_PATH}
)
EXEC_PROGRAM(${CMAKE_Go_COMPILER} ARGS version OUTPUT_VARIABLE GOLANG_VERSION)
STRING(REGEX MATCH "go[0-9]+.[0-9]+.[0-9]+[ /A-Za-z0-9]*" VERSION "${GOLANG_VERSION}")
message("-- The Golang compiler identification is ${VERSION}")
message("-- Check for working Golang compiler: ${CMAKE_Go_COMPILER}")
endif()
endif()
mark_as_advanced(CMAKE_Go_COMPILER)
configure_file(${CMAKE_MODULE_PATH}/CMakeGoCompiler.cmake.in
${CMAKE_PLATFORM_INFO_DIR}/CMakeGoCompiler.cmake @ONLY)
set(CMAKE_Go_COMPILER_ENV_VAR "GO_COMPILER")
set(CMAKE_Go_COMPILER "@CMAKE_Go_COMPILER@")
set(CMAKE_Go_COMPILER_LOADED 1)
set(CMAKE_Go_SOURCE_FILE_EXTENSIONS go)
set(CMAKE_Go_LINKER_PREFERENCE 40)
set(CMAKE_Go_OUTPUT_EXTENSION .o)
set(CMAKE_Go_OUTPUT_EXTENSION_REPLACE 1)
set(CMAKE_Go_COMPILER_ENV_VAR "GO_COMPILER")
if(NOT CMAKE_Go_COMPILE_OBJECT)
set(CMAKE_Go_COMPILE_OBJECT "go tool compile -l -N -o <OBJECT> <SOURCE> ")
endif()
if(NOT CMAKE_Go_LINK_EXECUTABLE)
set(CMAKE_Go_LINK_EXECUTABLE "go tool link -o <TARGET> <OBJECTS> ")
endif()
set(CMAKE_Go_COMPILER_WORKS 1 CACHE INTERNAL "")
# Setting Paddle Compile Flags
include(CheckCXXCompilerFlag)
include(CheckCCompilerFlag)
include(CheckCXXSymbolExists)
include(CheckTypeSize)
function(CheckCompilerCXX11Flag)
if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
if(${CMAKE_CXX_COMPILER_VERSION} VERSION_LESS 4.8)
message(FATAL_ERROR "Unsupported GCC version. GCC >= 4.8 required.")
endif()
elseif(CMAKE_CXX_COMPILER_ID STREQUAL "AppleClang" OR CMAKE_CXX_COMPILER_ID STREQUAL "Clang")
# cmake >= 3.0 compiler id "AppleClang" on Mac OS X, otherwise "Clang"
# Apple Clang is a different compiler than upstream Clang which havs different version numbers.
# https://gist.github.com/yamaya/2924292
if(APPLE) # cmake < 3.0 compiler id "Clang" on Mac OS X
if(${CMAKE_CXX_COMPILER_VERSION} VERSION_LESS 5.1)
message(FATAL_ERROR "Unsupported AppleClang version. AppleClang >= 5.1 required.")
endif()
else()
if (${CMAKE_CXX_COMPILER_VERSION} VERSION_LESS 3.3)
message(FATAL_ERROR "Unsupported Clang version. Clang >= 3.3 required.")
endif()
endif()
endif()
endfunction()
CheckCompilerCXX11Flag()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
# Common gpu architectures: Kepler, Maxwell
foreach(capability 30 35 50)
list(APPEND __arch_flags " -gencode arch=compute_${capability},code=sm_${capability}")
endforeach()
if (CUDA_VERSION VERSION_GREATER "7.0" OR CUDA_VERSION VERSION_EQUAL "7.0")
list(APPEND __arch_flags " -gencode arch=compute_52,code=sm_52")
endif()
# Modern gpu architectures: Pascal
if (CUDA_VERSION VERSION_GREATER "8.0" OR CUDA_VERSION VERSION_EQUAL "8.0")
list(APPEND __arch_flags " -gencode arch=compute_60,code=sm_60")
endif()
set(CUDA_NVCC_FLAGS ${__arch_flags} ${CUDA_NVCC_FLAGS})
set(GOPATH "${CMAKE_CURRENT_BINARY_DIR}/go")
file(MAKE_DIRECTORY ${GOPATH})
set(PADDLE_IN_GOPATH "${GOPATH}/src/github.com/PaddlePaddle")
file(MAKE_DIRECTORY ${PADDLE_IN_GOPATH})
function(GO_LIBRARY NAME BUILD_TYPE)
if(BUILD_TYPE STREQUAL "STATIC")
set(BUILD_MODE -buildmode=c-archive)
set(LIB_NAME "lib${NAME}.a")
else()
set(BUILD_MODE -buildmode=c-shared)
if(APPLE)
set(LIB_NAME "lib${NAME}.dylib")
else()
set(LIB_NAME "lib${NAME}.so")
endif()
endif()
file(GLOB GO_SOURCE RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.go")
file(RELATIVE_PATH rel ${CMAKE_CURRENT_BINARY_DIR} ${CMAKE_CURRENT_SOURCE_DIR})
# find Paddle directory.
get_filename_component(PARENT_DIR ${CMAKE_CURRENT_SOURCE_DIR} DIRECTORY)
get_filename_component(PARENT_DIR ${PARENT_DIR} DIRECTORY)
get_filename_component(PADDLE_DIR ${PARENT_DIR} DIRECTORY)
# automatically get all dependencies specified in the source code
# for given target.
add_custom_target(${NAME}_goGet env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} get -d ${rel}/...)
# make a symlink that references Paddle inside $GOPATH, so go get
# will use the local changes in Paddle rather than checkout Paddle
# in github.
add_custom_target(${NAME}_copyPaddle
COMMAND rm -rf ${PADDLE_IN_GOPATH}/Paddle
COMMAND ln -sf ${PADDLE_DIR} ${PADDLE_IN_GOPATH}/Paddle)
add_dependencies(${NAME}_goGet ${NAME}_copyPaddle)
add_custom_command(OUTPUT ${OUTPUT_DIR}/.timestamp
COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build ${BUILD_MODE}
-o "${CMAKE_CURRENT_BINARY_DIR}/${LIB_NAME}"
${CMAKE_GO_FLAGS} ${GO_SOURCE}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
add_custom_target(${NAME} ALL DEPENDS ${OUTPUT_DIR}/.timestamp ${ARGN})
add_dependencies(${NAME} ${NAME}_goGet)
endfunction(GO_LIBRARY)
package main
import (
"fmt"
"net"
"net/http"
"net/rpc"
"strconv"
"strings"
"time"
"github.com/namsral/flag"
log "github.com/sirupsen/logrus"
"github.com/PaddlePaddle/Paddle/go/master"
"github.com/PaddlePaddle/Paddle/go/utils/networkhelper"
)
func main() {
port := flag.Int("port", 8080, "port of the master server.")
faultTolerance := flag.Bool("fault_tolerance", false, "enable fault tolerance (requires etcd).")
ttlSec := flag.Int("ttl", 60, "etcd lease TTL in seconds.")
endpoints := flag.String("endpoints", "http://127.0.0.1:2379", "comma separated etcd endpoints. If empty, fault tolerance will not be enabled.")
taskTimeoutDur := flag.Duration("task_timout_dur", 20*time.Minute, "task timout duration.")
taskTimeoutMax := flag.Int("task_timeout_max", 3, "max timtout count for each task before it being declared failed task.")
chunkPerTask := flag.Int("chunk_per_task", 10, "chunk per task.")
flag.Parse()
if *faultTolerance {
panic("fault tolernance not implemented.")
if *endpoints == "" {
log.Warningln("-endpoints not set, fault tolerance not be enabled.")
}
var store master.Store
if *endpoints != "" {
eps := strings.Split(*endpoints, ",")
ip, err := networkhelper.GetExternalIP()
if err != nil {
log.Fatal(err)
}
addr := fmt.Sprintf("%s:%d", ip, *port)
store, err = master.NewEtcdClient(eps, addr, master.DefaultLockPath, master.DefaultAddrPath, master.DefaultStatePath, *ttlSec)
if err != nil {
log.Fatal(err)
}
} else {
store = &master.InMemStore{}
}
s, err := master.NewService(store, *chunkPerTask, *taskTimeoutDur, *taskTimeoutMax)
if err != nil {
log.Fatal(err)
}
s := master.NewService(*chunkPerTask, *taskTimeoutDur, *taskTimeoutMax)
err := rpc.Register(s)
err = rpc.Register(s)
if err != nil {
panic(err)
log.Fatal(err)
}
rpc.HandleHTTP()
l, err := net.Listen("tcp", ":"+strconv.Itoa(*port))
if err != nil {
panic(err)
log.Fatal(err)
}
err = http.Serve(l, nil)
if err != nil {
panic(err)
log.Fatal(err)
}
}
......@@ -5,18 +5,42 @@ import (
"net/http"
"net/rpc"
"strconv"
"time"
"github.com/namsral/flag"
"github.com/PaddlePaddle/Paddle/go/pserver"
log "github.com/sirupsen/logrus"
)
func main() {
port := flag.Int("port", 0, "port of the pserver")
etcdEndpoint := flag.String("etcd-endpoint", "http://127.0.0.1:2379",
"comma separated endpoint string for pserver to connect to etcd")
etcdTimeout := flag.Int("etcd-timeout", 5, "timeout for etcd calls")
numPservers := flag.Int("num-pservers", 1, "total pserver count in a training job")
logLevel := flag.String("log-level", "info",
"log level, possible values: debug, info, warning, error, fatal, panic")
flag.Parse()
s := pserver.NewService()
err := rpc.Register(s)
level, err := log.ParseLevel(*logLevel)
if err != nil {
panic(err)
}
log.SetLevel(level)
timeout := time.Second * time.Duration((*etcdTimeout))
e := pserver.NewEtcdClient(*etcdEndpoint, *numPservers, timeout)
idx, err := e.Register()
if err != nil {
panic(err)
}
s, err := pserver.NewService(idx)
if err != nil {
panic(err)
}
err = rpc.Register(s)
if err != nil {
panic(err)
}
......@@ -27,7 +51,9 @@ func main() {
panic(err)
}
log.Infof("start pserver at port %d", *port)
err = http.Serve(l, nil)
if err != nil {
panic(err)
}
......
......@@ -13,10 +13,13 @@ typedef int paddle_master_client;
import "C"
import (
"strings"
"sync"
"time"
"unsafe"
"github.com/PaddlePaddle/Paddle/go/master"
"github.com/coreos/etcd/clientv3"
log "github.com/sirupsen/logrus"
)
......@@ -48,16 +51,33 @@ func remove(client C.paddle_master_client) *master.Client {
return h
}
type addresser string
func (a addresser) Address() string {
return string(a)
//export paddle_new_etcd_master_client
func paddle_new_etcd_master_client(etcdEndpoints *C.char, timeout int, bufSize int) C.paddle_master_client {
p := C.GoString(etcdEndpoints)
cli, err := clientv3.New(clientv3.Config{
Endpoints: strings.Split(p, ","),
DialTimeout: time.Second * time.Duration(timeout),
})
if err != nil {
panic(err)
}
ch := make(chan string, 1)
a, err := master.GetKey(cli, master.DefaultAddrPath, timeout)
if err != nil {
panic(err)
}
ch <- a
go master.WatchKey(cli, master.DefaultAddrPath, ch)
c := master.NewClient(ch, bufSize)
return add(c)
}
//export paddle_new_master_client
func paddle_new_master_client(addr *C.char, bufSize int) C.paddle_master_client {
a := C.GoString(addr)
c := master.NewClient(addresser(a), bufSize)
ch := make(chan string, 1)
ch <- a
c := master.NewClient(ch, bufSize)
return add(c)
}
......
......@@ -2,18 +2,12 @@ package master
import (
"os"
"time"
"github.com/PaddlePaddle/Paddle/go/connection"
"github.com/PaddlePaddle/recordio"
log "github.com/sirupsen/logrus"
)
// Addresser provide the address of the master server.
type Addresser interface {
Address() string
}
// Client is the client of the master server.
type Client struct {
conn *connection.Conn
......@@ -24,11 +18,11 @@ type Client struct {
//
// bufSize is the record buffer size. NextRecord will read from this
// buffer.
func NewClient(addr Addresser, bufSize int) *Client {
func NewClient(addrCh <-chan string, bufSize int) *Client {
c := &Client{}
c.conn = connection.New()
c.ch = make(chan []byte, bufSize)
go c.monitorMaster(addr)
go c.monitorMaster(addrCh)
go c.getRecords()
return c
}
......@@ -72,12 +66,10 @@ func (c *Client) getRecords() {
}
}
func (c *Client) monitorMaster(addr Addresser) {
func (c *Client) monitorMaster(addrCh <-chan string) {
lastMaster := ""
monitor := func() {
// get the lastest address of the master server,
for curMaster := range addrCh {
// connect to the new address once address changed.
curMaster := addr.Address()
if curMaster != lastMaster {
if curMaster == "" {
err := c.conn.Close()
......@@ -94,18 +86,10 @@ func (c *Client) monitorMaster(addr Addresser) {
// to retry next time.
curMaster = lastMaster
}
}
}
lastMaster = curMaster
}
monitor()
ticker := time.NewTicker(10 * time.Second)
for _ = range ticker.C {
monitor()
}
}
// SetDataset set dataset for the master server to dispatch.
......
......@@ -26,12 +26,6 @@ func init() {
log.SetLevel(log.ErrorLevel)
}
type TestAddresser string
func (a TestAddresser) Address() string {
return string(a)
}
func TestGetFinishTask(t *testing.T) {
const path = "/tmp/master_client_test_0"
......@@ -45,11 +39,14 @@ func TestGetFinishTask(t *testing.T) {
if err != nil {
panic(err)
}
go func(l net.Listener) {
s := NewService(chunkPerTask, time.Second, 1)
s, err := NewService(&InMemStore{}, chunkPerTask, time.Second, 1)
if err != nil {
panic(err)
}
server := rpc.NewServer()
err := server.Register(s)
err = server.Register(s)
if err != nil {
panic(err)
}
......@@ -78,9 +75,11 @@ func TestGetFinishTask(t *testing.T) {
// Manually intialize client to avoid calling c.getRecords()
c := &Client{}
c.conn = connection.New()
go c.monitorMaster(TestAddresser(fmt.Sprintf(":%d", p)))
addr := fmt.Sprintf(":%d", p)
ch := make(chan string, 1)
ch <- addr
go c.monitorMaster(ch)
c.SetDataset([]string{path})
checkOnePass := func(i int) {
var tasks []Task
for idx := 0; idx < totalTask; idx++ {
......
......@@ -20,7 +20,6 @@ func TestNextRecord(t *testing.T) {
path = "/tmp/master_client_TestFull"
total = 50
)
l, err := net.Listen("tcp", ":0")
if err != nil {
panic(err)
......@@ -31,11 +30,14 @@ func TestNextRecord(t *testing.T) {
if err != nil {
panic(err)
}
go func(l net.Listener) {
s := master.NewService(10, time.Second, 1)
s, err := master.NewService(&master.InMemStore{}, 10, time.Second, 1)
if err != nil {
panic(err)
}
server := rpc.NewServer()
err := server.Register(s)
err = server.Register(s)
if err != nil {
panic(err)
}
......@@ -59,10 +61,10 @@ func TestNextRecord(t *testing.T) {
}
w.Close()
f.Close()
c := master.NewClient(master.TestAddresser(fmt.Sprintf(":%d", p)), 10)
curAddr := make(chan string, 1)
curAddr <- fmt.Sprintf(":%d", p)
c := master.NewClient(curAddr, 10)
c.SetDataset([]string{path})
for pass := 0; pass < 50; pass++ {
received := make(map[byte]bool)
for i := 0; i < total; i++ {
......
package master
import (
"context"
"time"
"github.com/coreos/etcd/clientv3"
"github.com/coreos/etcd/clientv3/concurrency"
log "github.com/sirupsen/logrus"
)
const (
// DefaultLockPath is the default etcd master lock path.
DefaultLockPath = "/master/lock"
// DefaultStatePath is the default etcd key for master state.
DefaultStatePath = "/master/state"
// DefaultAddrPath is the default etcd key for master address.
DefaultAddrPath = "/master/addr"
)
// EtcdClient is the etcd client that the master uses for fault
// tolerance and service registry.
type EtcdClient struct {
lockPath string
statePath string
client *clientv3.Client
lock *concurrency.Mutex
}
// NewEtcdClient creates a new EtcdClient.
func NewEtcdClient(endpoints []string, addr string, lockPath, addrPath, statePath string, ttlSec int) (*EtcdClient, error) {
log.Debugf("Connecting to etcd at %v", endpoints)
// TODO(helin): gracefully shutdown etcd store. Becuase etcd
// store holds a etcd lock, even though the lock will expire
// when the lease timeout, we need to implement graceful
// shutdown to release the lock.
cli, err := clientv3.New(clientv3.Config{
Endpoints: endpoints,
DialTimeout: dialTimeout,
})
if err != nil {
return nil, err
}
sess, err := concurrency.NewSession(cli, concurrency.WithTTL(ttlSec))
if err != nil {
return nil, err
}
lock := concurrency.NewMutex(sess, lockPath)
// It's fine for the lock to get stuck, in this case we have
// multiple master servers running (only configured to have
// one master running, but split-brain problem may cuase
// multiple master servers running), and the cluster management
// software will kill one of them.
log.Debugf("Trying to acquire lock at %s.", lockPath)
err = lock.Lock(context.TODO())
if err != nil {
return nil, err
}
log.Debugf("Successfully acquired lock at %s.", lockPath)
put := clientv3.OpPut(addrPath, string(addr))
resp, err := cli.Txn(context.Background()).If(lock.IsOwner()).Then(put).Commit()
if err != nil {
return nil, err
}
if !resp.Succeeded {
log.Fatal("No longer owns the master lock. Exiting.")
}
e := &EtcdClient{
lockPath: lockPath,
statePath: statePath,
client: cli,
lock: lock,
}
return e, nil
}
// Save saves the state into the etcd.
func (e *EtcdClient) Save(state []byte) error {
ctx := context.TODO()
put := clientv3.OpPut(e.statePath, string(state))
resp, err := e.client.Txn(ctx).If(e.lock.IsOwner()).Then(put).Commit()
if err != nil {
return err
}
if !resp.Succeeded {
log.Errorln("No longer owns the lock, trying to lock again")
ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
err := e.lock.Lock(ctx)
cancel()
if err != nil {
// We lost the master lock and can not acquire
// it back, it means some other master is
// already started. We don't want cluster
// managment system to kill the master server
// who is holding the lock and running
// correctly. So the most feasible solution is
// to kill current master server. The current
// state is not saved, but the trainer's RPC
// call will fail, so the trainer will retry.
log.Fatalf("Could not acquire the lock at %s: %v. Exiting.", e.lockPath, err)
}
log.Infof("Successfully acquired lock at %s.", e.lockPath)
return e.Save(state)
}
return nil
}
// Load loads the state from etcd.
func (e *EtcdClient) Load() ([]byte, error) {
ctx := context.TODO()
get := clientv3.OpGet(e.statePath)
resp, err := e.client.Txn(ctx).If(e.lock.IsOwner()).Then(get).Commit()
if err != nil {
return nil, err
}
if !resp.Succeeded {
log.Errorln("No longer owns the lock, trying to lock and load again.")
err = e.lock.Lock(context.Background())
if err != nil {
return nil, err
}
return e.Load()
}
kvs := resp.Responses[0].GetResponseRange().Kvs
if len(kvs) == 0 {
// No state exists
return nil, nil
}
state := kvs[0].Value
return state, nil
}
// GetKey gets the value by the specify key.
func GetKey(c *clientv3.Client, key string, timeout int) (string, error) {
ctx, cancel := context.WithTimeout(context.Background(), time.Second*time.Duration(timeout))
resp, err := c.Get(ctx, key)
cancel()
if err != nil {
return "", err
}
kvs := resp.Kvs
if len(kvs) == 0 {
return "", nil
}
v := kvs[0].Value
return string(v), nil
}
// WatchKey watches the specify key and send to valChan if there is some event.
func WatchKey(c *clientv3.Client, key string, valChan chan<- string) {
rch := c.Watch(context.Background(), key)
for wresp := range rch {
for _, ev := range wresp.Events {
// if received event is DELETE, the value will be an empty string
log.Infof("received event %s, %q : %q\n", ev.Type, ev.Kv.Key, ev.Kv.Value)
valChan <- string(ev.Kv.Value)
}
}
}
package master
import "sync"
// InMemStore is an in memory implementation of Store interface.
//
// It does not tolerate the fault that casues the program to crash.
type InMemStore struct {
mu sync.Mutex
buf []byte
}
// Save saves the state into the in-memory store.
func (m *InMemStore) Save(state []byte) error {
m.mu.Lock()
defer m.mu.Unlock()
m.buf = state
return nil
}
// Load loads the state from the in-memory store.
func (m *InMemStore) Load() ([]byte, error) {
m.mu.Lock()
defer m.mu.Unlock()
return m.buf, nil
}
package master
import (
"bytes"
"compress/gzip"
"encoding/gob"
"errors"
"os"
"path/filepath"
......@@ -12,24 +15,54 @@ import (
"github.com/PaddlePaddle/recordio"
)
const (
dialTimeout = 5 * time.Second
)
// Store is the interface for save and load the master state.
type Store interface {
Save([]byte) error
Load() ([]byte, error)
}
// Chunk is a chunk of data consisted of several data instances.
type Chunk struct {
Path string
Index recordio.Index // chunk index
}
// Task is the basic unit of data instances assigned to trainers.
type Task struct {
ID int
Chunks []Chunk
}
type taskEntry struct {
Epoch int
NumTimeout int
Task Task
}
type taskQueues struct {
Todo []taskEntry
Pending map[int]taskEntry // map from task ID to task entry
Done []taskEntry
Failed []Task
}
// Service is the master server service.
type Service struct {
chunksPerTask int
timeoutDur time.Duration
timeoutMax int
ready chan struct{}
store Store
mu sync.Mutex
initDone bool
taskQueues taskQueues
}
// Recover recovers service state from etcd.
func Recover() (*Service, error) {
// TODO(helin): recover from snapshot state from etcd.
return nil, nil
}
func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
id := 0
if chunksPerTask <= 0 {
......@@ -58,7 +91,7 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
}
// NewService creates a new service.
func NewService(chunksPerTask int, timeoutDur time.Duration, timeoutMax int) *Service {
func NewService(store Store, chunksPerTask int, timeoutDur time.Duration, timeoutMax int) (*Service, error) {
s := &Service{}
s.chunksPerTask = chunksPerTask
s.timeoutDur = timeoutDur
......@@ -66,38 +99,82 @@ func NewService(chunksPerTask int, timeoutDur time.Duration, timeoutMax int) *Se
s.taskQueues = taskQueues{}
s.taskQueues.Pending = make(map[int]taskEntry)
s.ready = make(chan struct{})
return s
}
s.store = store
recovered, err := s.recover()
if err != nil {
return nil, err
}
// Chunk is a chunk of data consisted of several data instances.
type Chunk struct {
Path string
Index recordio.Index // chunk index
}
if recovered {
// Recovered. Now the state is already initialized,
// and the master is ready.
s.initDone = true
close(s.ready)
log.Info("Master recovered from saved state.")
}
// Task is the basic unit of data instances assigned to trainers.
type Task struct {
ID int
Chunks []Chunk
return s, nil
}
type taskEntry struct {
Epoch int
NumTimeout int
Task Task
}
// recover recovers service state from etcd.
func (s *Service) recover() (bool, error) {
state, err := s.store.Load()
if err != nil {
return false, err
}
type taskQueues struct {
Todo []taskEntry
Pending map[int]taskEntry // map from task ID to task entry
Done []taskEntry
Failed []Task
if state == nil {
log.Infoln("No state exists, not recovered.")
return false, nil
}
log.Infof("Loaded snapshot of size: %d bytes.", len(state))
gr, err := gzip.NewReader(bytes.NewReader(state))
if err != nil {
return false, err
}
dec := gob.NewDecoder(gr)
var tqs taskQueues
err = dec.Decode(&tqs)
if err != nil {
return false, err
}
err = gr.Close()
if err != nil {
// Only close failed, recover actually succeed, so
// just log error.
log.Errorln(err)
}
s.taskQueues = tqs
return true, nil
}
// *must* be called with s.mu being held.
// snapshot *must* be called with s.mu being held.
func (s *Service) snapshot() error {
// TODO(helin): snapshot state on etcd.
return nil
// TOOD(helin): etcd request has a size limit, so the snapshot
// size is limited by the max request size. We should either
// divide the snapshot into smaller chunks and save under
// different keys, or configure the request size to be big
// enough:
// https://github.com/coreos/etcd/blob/2f84f3d8d8ed8f9537ab6ffa44a3a1c7eddfa9b1/embed/config.go#L44
var buf bytes.Buffer
gw := gzip.NewWriter(&buf)
enc := gob.NewEncoder(gw)
err := enc.Encode(s.taskQueues)
if err != nil {
return err
}
err = gw.Close()
if err != nil {
return err
}
state := buf.Bytes()
log.Infof("Saving snapshot of size: %d bytes.", len(state))
return s.store.Save(state)
}
func readChunks(globPaths []string) ([]Chunk, error) {
......@@ -207,12 +284,12 @@ func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() {
t.NumTimeout++
if t.NumTimeout > s.timeoutMax {
log.Warningf("Task %v timed out %d times, discard.\n", t.Task, t.NumTimeout)
log.Warningf("Task %v timed out %d times, discard.", t.Task, t.NumTimeout)
s.taskQueues.Failed = append(s.taskQueues.Failed, t.Task)
return
}
log.Warningf("Task %v timed out %d times, retry.\n", t.Task, t.NumTimeout)
log.Warningf("Task %v timed out %d times, retry.", t.Task, t.NumTimeout)
s.taskQueues.Todo = append(s.taskQueues.Todo, t)
}
}
......
cmake_minimum_required(VERSION 3.0)
get_filename_component(PARENT_DIR ${CMAKE_CURRENT_SOURCE_DIR} DIRECTORY)
get_filename_component(PARENT_DIR ${PARENT_DIR} DIRECTORY)
set(CMAKE_MODULE_PATH ${CMAKE_MODULE_PATH} "${PARENT_DIR}/cmake")
project(cxx_go C Go)
include(golang)
include(flags)
cc_library(paddle_go_optimizer DEPS paddle_optimizer paddle_proto glog gflags)
go_library(paddle_pserver_cclient STATIC)
if(WITH_TESTING)
add_subdirectory(test)
......
......@@ -133,7 +133,7 @@ func paddle_init_param(client C.paddle_pserver_client, param C.paddle_parameter,
if err != nil {
if err.Error() == pserver.AlreadyInitialized {
log.Warningf("parameter %s already initialized, treat paddle_init_param as sucessful.\n", name)
log.Warningf("parameter %s already initialized, treat paddle_init_param as sucessful.", name)
return C.PSERVER_OK
}
log.Errorln(err)
......@@ -200,7 +200,7 @@ func paddle_get_params(client C.paddle_pserver_client, dst **C.paddle_parameter,
for i, p := range ps {
pn[i] = p.Name
}
log.Errorf("pserver returned wrong number of parameters. Requested: %s, returned: %s.\n", strings.Join(pn, ", "), strings.Join(ns, ", "))
log.Errorf("pserver returned wrong number of parameters. Requested: %s, returned: %s.", strings.Join(pn, ", "), strings.Join(ns, ", "))
return C.PSERVER_ERROR
}
......@@ -210,7 +210,7 @@ func paddle_get_params(client C.paddle_pserver_client, dst **C.paddle_parameter,
for i, p := range ps {
pn[i] = p.Name
}
log.Errorf("pserver returned wrong parameters, or not in requested order. Requested: %s, returned: %s.\n", strings.Join(pn, ", "), strings.Join(ns, ", "))
log.Errorf("pserver returned wrong parameters, or not in requested order. Requested: %s, returned: %s.", strings.Join(pn, ", "), strings.Join(ns, ", "))
return C.PSERVER_ERROR
}
}
......
cmake_minimum_required(VERSION 3.0)
add_executable(test_cclient test_cclient.c)
add_dependencies(test_cclient paddle_pserver_cclient)
if(APPLE)
set(CMAKE_EXE_LINKER_FLAGS "-framework CoreFoundation -framework Security")
else()
set(CMAKE_EXE_LINKER_FLAGS "-pthread")
endif()
if(PROJ_ROOT)
include_directories(${CMAKE_CURRENT_BINARY_DIR}/..)
target_link_libraries(test_cclient ${CMAKE_CURRENT_BINARY_DIR}/../libpaddle_pserver_cclient.a pthread)
else(PROJ_ROOT)
include_directories(${CMAKE_BINARY_DIR})
target_link_libraries(test_cclient ${CMAKE_BINARY_DIR}/libpaddle_pserver_cclient.a pthread)
endif(PROJ_ROOT)
cc_test(test_cclient SRCS test_cclient.c DEPS paddle_pserver_cclient)
\ No newline at end of file
package pserver
import (
"errors"
"hash/fnv"
"sort"
"time"
......@@ -123,6 +124,9 @@ func (c *Client) FinishInitParams() error {
// SendGrads sends gradients to parameter servers for updating
// parameters.
func (c *Client) SendGrads(grads []Gradient) error {
if len(grads) == 0 {
return errors.New("no gradient received")
}
errCh := make(chan error, len(grads))
for _, g := range grads {
go func(g Gradient) {
......
......@@ -31,9 +31,12 @@ func init() {
port[i] = p
go func(l net.Listener) {
s := pserver.NewService()
s, err := pserver.NewService(0)
if err != nil {
panic(err)
}
server := rpc.NewServer()
err := server.Register(s)
err = server.Register(s)
if err != nil {
panic(err)
}
......
package pserver
import (
"context"
"errors"
"strconv"
"strings"
"time"
"github.com/PaddlePaddle/Paddle/go/utils/networkhelper"
"github.com/coreos/etcd/clientv3"
"github.com/coreos/etcd/clientv3/concurrency"
log "github.com/sirupsen/logrus"
)
// EtcdClient is the etcd client that the pserver uses for fault
// tolerance, service registry and coordination.
type EtcdClient struct {
numPservers int
etcdEndpoints string
etcdClient *clientv3.Client
// etcdTimeout is also used as retry intervals.
etcdTimeout time.Duration
// FIXME: ensure GetExternalIP gets the correct ip for trainers to connect.
externalIP string
// desired number of pservers in the job.
// assume desired will not change during one training job.
desired int
}
// NewEtcdClient creates an EtcdClient
func NewEtcdClient(endpoints string, numPservers int, timeout time.Duration) *EtcdClient {
return &EtcdClient{
etcdTimeout: timeout,
numPservers: numPservers,
etcdEndpoints: endpoints,
}
}
// Register registers the pserver on etcd
//
// Register returns the index of the current pserver.
func (e *EtcdClient) Register() (int, error) {
var err error
e.externalIP, err = networkhelper.GetExternalIP()
if err != nil {
return 0, err
}
// initialize connection to etcd.
ep := strings.Split(e.etcdEndpoints, ",")
for {
cli, err := clientv3.New(clientv3.Config{
Endpoints: ep,
DialTimeout: e.etcdTimeout,
})
if err != nil {
log.Errorf("connect to etcd error: %v", err)
time.Sleep(e.etcdTimeout)
continue
}
e.etcdClient = cli
log.Debugf("inited client to %s", e.etcdEndpoints)
break
}
// init /ps_desired using transaction, for multiple pservers may want to write
// it at the same time.
for {
ctx, cancel := context.WithTimeout(context.Background(), time.Second)
_, err := e.initDesiredPsercers(ctx, e.numPservers)
cancel()
if err != nil {
log.Warn(err)
time.Sleep(e.etcdTimeout)
continue
}
break
}
// TODO: when implementing extending or reducing pservers, /ps_desired is
// changed, then we need to watch /ps_desired node for events. For now, just
// write once when init and read from it.
// wait and set s.desired init value
for {
ctx, cancel := context.WithTimeout(context.Background(), time.Second)
resp, err := e.etcdClient.Get(ctx, PsDesired)
cancel()
if err != nil {
log.Errorf("getting %s error: %v", PsDesired, err)
time.Sleep(e.etcdTimeout)
continue
}
if len(resp.Kvs) != 0 {
e.desired, err = strconv.Atoi(string(resp.Kvs[0].Value))
if err != nil {
log.Errorf("value of %s invalid %v\n", PsDesired, err)
time.Sleep(e.etcdTimeout)
// NOTE: wait util ps_desired value change
continue
}
break
}
}
var pserverIdx int
// try register pserver node on etcd
for {
ctx, cancel := context.WithTimeout(context.Background(), time.Second)
var err error
pserverIdx, err = e.registerPserverEtcd(ctx)
cancel()
if err != nil {
log.Warn(err)
time.Sleep(e.etcdTimeout)
continue
}
break
}
return pserverIdx, nil
}
func (e *EtcdClient) initDesiredPsercers(ctx context.Context, numPservers int) (*clientv3.TxnResponse, error) {
return concurrency.NewSTM(e.etcdClient, func(c concurrency.STM) error {
dsStr := c.Get(PsDesired)
if dsStr == "" {
c.Put(PsDesired, strconv.Itoa(numPservers))
}
return nil
}, concurrency.WithAbortContext(ctx), concurrency.WithIsolation(concurrency.RepeatableReads))
}
// registerPserverEtcd registers pserver node on etcd using transaction.
func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
var idx int
_, err := concurrency.NewSTM(e.etcdClient, func(c concurrency.STM) error {
registered := false
for i := 0; i < e.desired; i++ {
psKey := "/ps/" + strconv.Itoa(i)
log.Debugf("checking %s", psKey)
ps := c.Get(psKey)
log.Debugf("got value (%s) for key: %s", ps, psKey)
if ps == "" {
resp, err := e.etcdClient.Grant(context.TODO(), 5)
if err != nil {
log.Fatal(err)
}
// find the first id and write info
c.Put(psKey, e.externalIP, clientv3.WithLease(resp.ID))
log.Debugf("set pserver node %s with value %s", psKey, e.externalIP)
ch, kaerr := e.etcdClient.KeepAlive(context.TODO(), resp.ID)
if kaerr != nil {
log.Errorf("keepalive etcd node error: %v", kaerr)
return kaerr
}
// Eat the keep alive message so etcd
// will not expire the lease.
go func(ch <-chan *clientv3.LeaseKeepAliveResponse) {
ka := <-ch
log.Debugf("keepalive: %d\n", ka.TTL)
}(ch)
log.Debug("register finished")
idx = i
registered = true
break
}
}
if registered == true {
return nil
}
return errors.New("not registerd, may due to already have enough pservers")
}, concurrency.WithAbortContext(ctx), concurrency.WithIsolation(concurrency.RepeatableReads))
if err != nil {
return 0, err
}
return idx, nil
}
......@@ -24,6 +24,9 @@ const (
Float64
)
// PsDesired is etcd path for store desired pserver count
const PsDesired = "/ps_desired"
// Parameter is a piece of data to sync with the parameter server.
type Parameter struct {
Name string
......@@ -43,17 +46,21 @@ type Gradient Parameter
// Service is the RPC service for pserver.
type Service struct {
initialized chan struct{}
idx int
mu sync.Mutex
optMap map[string]*optimizer
}
// NewService creates a new service.
func NewService() *Service {
s := &Service{}
// NewService creates a new service, will bypass etcd registration if no
// endpoints specified.
func NewService(idx int) (*Service, error) {
s := &Service{
idx: idx,
}
s.optMap = make(map[string]*optimizer)
s.initialized = make(chan struct{})
return s
return s, nil
}
// InitParam initializes a parameter.
......
......@@ -10,8 +10,12 @@ import (
"github.com/PaddlePaddle/Paddle/go/pserver"
)
func TestServiceFull(t *testing.T) {
s := pserver.NewService()
func TestFull(t *testing.T) {
s, err := pserver.NewService(0)
if err != nil {
t.Error(err)
}
var p pserver.Parameter
p.Name = "param_a"
p.Content = []byte{1, 0, 0, 0, 2, 0, 0, 0, 3, 0, 0, 0}
......@@ -79,8 +83,11 @@ func TestServiceFull(t *testing.T) {
}
func TestMultipleInit(t *testing.T) {
s := pserver.NewService()
err := s.FinishInitParams(0, nil)
s, err := pserver.NewService(0)
if err != nil {
t.Error(err)
}
err = s.FinishInitParams(0, nil)
if err != nil {
t.FailNow()
}
......@@ -92,15 +99,18 @@ func TestMultipleInit(t *testing.T) {
}
func TestUninitialized(t *testing.T) {
s := pserver.NewService()
err := s.SendGrad(pserver.Gradient{}, nil)
s, err := pserver.NewService(0)
err = s.SendGrad(pserver.Gradient{}, nil)
if err.Error() != pserver.Uninitialized {
t.FailNow()
}
}
func TestBlockUntilInitialized(t *testing.T) {
s := pserver.NewService()
s, err := pserver.NewService(0)
if err != nil {
t.Error(err)
}
ch := make(chan struct{}, 2)
errCh := make(chan error, 2)
var wg sync.WaitGroup
......@@ -145,6 +155,7 @@ func TestBlockUntilInitialized(t *testing.T) {
t.Fatalf("read optimizer proto failed")
}
err = s.InitParam(pserver.ParameterWithConfig{Param: p, Config: config}, nil)
if err != nil {
t.FailNow()
}
......
package networkhelper
import (
"errors"
"net"
)
// GetExternalIP returns the ip address of local network interface, not the
// loopback device.
func GetExternalIP() (string, error) {
ifaces, err := net.Interfaces()
if err != nil {
return "", err
}
for _, iface := range ifaces {
if iface.Flags&net.FlagUp == 0 {
continue // interface down
}
if iface.Flags&net.FlagLoopback != 0 {
continue // loopback interface
}
addrs, err := iface.Addrs()
if err != nil {
return "", err
}
for _, addr := range addrs {
var ip net.IP
switch v := addr.(type) {
case *net.IPNet:
ip = v.IP
case *net.IPAddr:
ip = v.IP
}
if ip == nil || ip.IsLoopback() {
continue
}
ip = ip.To4()
if ip == nil {
continue // not an ipv4 address
}
return ip.String(), nil
}
}
return "", errors.New("are you connected to the network?")
}
package networkhelper
import "testing"
func TestGetIP(t *testing.T) {
_, err := GetExternalIP()
if err != nil {
t.Errorf("GetExternalIP returns error : %v\n", err)
}
}
......@@ -9,17 +9,10 @@ add_subdirectory(pserver)
add_subdirectory(trainer)
add_subdirectory(scripts)
add_subdirectory(optimizer)
add_subdirectory(strings)
# Do not build go directory until go cmake is working smoothly.
# if(CMAKE_Go_COMPILER)
# add_subdirectory(go)
# endif()
find_package(Boost QUIET)
add_subdirectory(string)
if(Boost_FOUND)
include_directories(${Boost_INCLUDE_DIRS})
add_subdirectory(memory)
add_subdirectory(platform)
add_subdirectory(framework)
endif()
......
......@@ -16,7 +16,7 @@ set(API_HEADER
Internal.h)
add_library(paddle_api STATIC ${API_SOURCES})
add_dependencies(paddle_api gen_proto_cpp paddle_trainer_lib)
add_dependencies(paddle_api paddle_proto paddle_trainer_lib)
INCLUDE(${SWIG_USE_FILE})
INCLUDE_DIRECTORIES(${PROJ_ROOT}/paddle)
......
......@@ -26,7 +26,7 @@ target_include_directories(paddle_capi PUBLIC ${CMAKE_CURRENT_BINARY_DIR})
add_style_check_target(paddle_capi ${CAPI_SOURCES} ${CAPI_HEADER}
${CAPI_PRIVATE_HEADER})
add_dependencies(paddle_capi gen_proto_cpp)
add_dependencies(paddle_capi paddle_proto)
# combine all paddle static libraries together, into libpaddle_capi_whole.a
......
......@@ -83,7 +83,7 @@ else()
${CUDA_CXX_SOURCES})
endif()
add_dependencies(paddle_cuda ${external_project_dependencies})
add_dependencies(paddle_cuda paddle_proto ${external_project_dependencies})
add_style_check_target(paddle_cuda
${CUDA_SOURCES}
......
# ddim lib
cc_library(ddim SRCS ddim.cc)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
cc_test(variable_test SRCS variable_test.cc)
cc_test(scope_test SRCS scope_test.cc)
cc_test(enforce_test SRCS enforce_test.cc)
//#include <stdexcept>
//#include <unittest/unittest.h>
#include <sstream>
#include <vector>
......
/* 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/string/printf.h>
#include <exception>
#include <sstream>
namespace paddle {
namespace framework {
/**
* @brief Enforce exception. Inherits std::exception
*
* All enforce condition not met, will throw an EnforceNotMet exception.
*/
class EnforceNotMet : public std::exception {
public:
EnforceNotMet(const std::string& msg, const char* file, int fileline) {
std::ostringstream sout;
sout << msg << " at [" << file << ":" << fileline << "];";
all_msg_ = sout.str();
}
const char* what() const noexcept override { return all_msg_.c_str(); }
private:
std::string all_msg_;
};
// From https://stackoverflow.com/questions/30130930/
// __buildin_expect is in C++ 11 standard. Since the condition which enforced
// should be true in most situation, it will make the compiler generate faster
// code by adding `UNLIKELY` macro.
#define UNLIKELY(condition) __builtin_expect(static_cast<bool>(condition), 0)
/**
* @brief Throw a EnforceNotMet exception, automatically filled __FILE__ &
* __LINE__
*
* This macro take __VA_ARGS__, user can pass any type if that type can
* serialize to std::ostream
*/
#define PADDLE_THROW(...) \
do { \
throw ::paddle::framework::EnforceNotMet( \
::paddle::string::Sprintf(__VA_ARGS__), __FILE__, __LINE__); \
} while (0)
/**
* @brief Enforce a condition, otherwise throw an EnforceNotMet
*/
#define PADDLE_ENFORCE(condition, ...) \
do { \
if (UNLIKELY(!(condition))) { \
PADDLE_THROW(__VA_ARGS__); \
} \
} while (0)
} // namespace framework
} // 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 <gtest/gtest.h>
#include <paddle/framework/enforce.h>
TEST(ENFORCE, OK) {
PADDLE_ENFORCE(true, "Enforce is ok %d now %f", 123, 0.345);
size_t val = 1;
const size_t limit = 10;
PADDLE_ENFORCE(val < limit, "Enforce is OK too");
}
TEST(ENFORCE, FAILED) {
bool in_catch = false;
try {
PADDLE_ENFORCE(false, "Enforce is not ok %d at all", 123);
} catch (paddle::framework::EnforceNotMet err) {
in_catch = true;
std::string msg = "Enforce is not ok 123 at all";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
}
}
ASSERT_TRUE(in_catch);
}
\ No newline at end of file
/* 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 <string>
#include <unordered_map>
#include <vector>
#include "paddle/framework/variable.h"
namespace paddle {
namespace framework {
/**
* @brief Scope that manage all variables.
*
* Scope is an association of a name to Variable. All variables belong to
* Scope. You need to specify a scope to run a Net, i.e., `net.Run(&scope)`.
* One net can run in different scopes and update different variable in the
* scope.
*/
class Scope {
public:
/**
* @brief Initialize s Scope without parent.
*/
Scope() {}
/**
* @brief Initialize a Scope with parent.
*/
explicit Scope(const std::shared_ptr<Scope>& parent) : parent_(parent) {}
/**
* @brief Create Variable
*
* Create Variable in this Scope. Return the exist one if Variable already
* been created.
*/
Variable* CreateVariable(const std::string& name) {
auto var = GetVariable(name);
if (var) {
return var;
} else {
vars_[name] = std::unique_ptr<Variable>(new Variable());
return GetVariable(name);
}
}
/**
* @brief Get Variable.
*
* Get Variable from this Scope, this function will recursive find Variable
* from it's parent scope. Return nullptr if not found.
*/
Variable* GetVariable(const std::string& name) const {
auto it = vars_.find(name);
if (it != vars_.end()) {
return it->second.get();
} else if (parent_ != nullptr) {
return parent_->GetVariable(name);
} else {
return nullptr;
}
}
/**
* @brief If this scope has a Var named name.
*
* Find if there is a Variable in this scope and it's parent scope
*/
bool HasVariable(const std::string& name) const {
return (vars_.find(name) != vars_.end() ||
(parent_ && parent_->HasVariable(name)));
}
private:
std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
std::shared_ptr<Scope> parent_{nullptr};
};
} // namespace framework
} // 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/framework/scope.h"
#include "gtest/gtest.h"
TEST(Scope, Create) {
using paddle::framework::Scope;
using paddle::framework::Variable;
auto scope = std::make_shared<Scope>();
Variable* var0 = scope->CreateVariable("");
EXPECT_NE(var0, nullptr);
/// GetVariable will return nullptr if not exist.
Variable* var1 = scope->GetVariable("a");
EXPECT_EQ(var1, nullptr);
/// CreateVariable will return one.
Variable* var2 = scope->CreateVariable("a");
EXPECT_NE(var2, nullptr);
/// Get the created variable.
Variable* var3 = scope->GetVariable("a");
EXPECT_EQ(var2, var3);
/// CreateVariable will just return the variable if it's
/// already exist.
Variable* var4 = scope->CreateVariable("a");
EXPECT_EQ(var4, var2);
}
TEST(Scope, Parent) {
using paddle::framework::Scope;
using paddle::framework::Variable;
auto parent_scope = std::make_shared<Scope>();
auto scope = std::make_shared<Scope>(parent_scope);
Variable* var0 = parent_scope->CreateVariable("a");
EXPECT_NE(var0, nullptr);
/// GetVariable will get Variable from parent scope if exist.
Variable* var1 = scope->GetVariable("a");
EXPECT_EQ(var0, var1);
}
/*
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 <memory>
#include <typeindex>
#include <typeinfo>
#include "paddle/platform/assert.h"
namespace paddle {
namespace framework {
class Variable {
public:
template <typename T>
const T& Get() const {
PADDLE_ASSERT(IsType<T>());
return *static_cast<const T*>(holder_->Ptr());
}
template <typename T>
T* GetMutable() {
if (!IsType<T>()) {
holder_.reset(new PlaceholderImpl<T>(new T()));
}
return static_cast<T*>(holder_->Ptr());
}
template <typename T>
bool IsType() const {
return holder_ != nullptr &&
std::type_index(typeid(T)) == std::type_index(holder_->Type());
}
private:
struct Placeholder {
virtual ~Placeholder() {}
virtual const std::type_info& Type() const = 0;
virtual void* Ptr() const = 0;
};
// Placeholder hides type T, so it doesn't appear as a template
// parameter of Variable.
template <typename T>
struct PlaceholderImpl : public Placeholder {
PlaceholderImpl(T* ptr) : ptr_(ptr), type_(typeid(T)) {}
virtual const std::type_info& Type() const { return type_; }
virtual void* Ptr() const { return static_cast<void*>(ptr_.get()); }
std::unique_ptr<T> ptr_;
const std::type_info& type_;
};
std::unique_ptr<Placeholder>
holder_; // pointers to a PlaceholderImpl object indeed.
};
} // namespace framework
} // namespace paddle
# Design Doc: Variable
Variable is also known as *blob* in MxNet and Caffe2. It is the input and output type of operators, where a neural network is a graph of operators.
## Requirements: Lazy Memory Allocation
For the flexibility of a DL system, a variable should be able to contain any typed value -- a tensor in most cases, but could also be some integer IDs or a scope of other variables in the case of RNN.
To use the minimum amount of memory, we'd like that a variable to allocate memory when it has to, or, lazy memory allocation. Let's take the following example:
```cpp
Variable vr, v1, v2;
Tensor* t1 = new Tensor();
Tensor* t2 = new Tensor();
Randomize(
/* malloc */ v1.GetMutable<Tensor>().mutable_data<float16>(DDim(100,200)),
/* size */ t1.Size());
Randomize(
/* malloc */ v2.GetMutable<Tensor>().mutable_data<float16>(DDim(200,300)),
/* size */ t2.Size());
Mult(
/*result*/ vr.GetMutable<Tensor>().mutable_data<v1.Type()>(SizeOfMult(v1, v2)),
/*input1*/ v1.Get<Tensor>().data(),
/*input2*/ v2.Get<Tensor>().data());
```
We see that a variable holds nothing until `Variable::GetMutable<Tensor>()` allocates a tensor and puts it in the variable. Similarly, a tensor gets its memory until `Tensor::mutable_data()`.
This syntax for lazy memory allocation when we call `Randomize` and `Mult`, those functions that mutate the variable, so it saves us some line of C++ code.
## Implementation: Type Hiding
To make memory allocation lazy, we cannot assume that we know the type held by a variable at definition time. In other words, `class Variable` cannot be a template `template <T> class Variable`.
Because we don't know the type `T`, we cannot save a `T*` as `Variable's` data member. Instead, we save an interface object `Placeholder`, who can return the pointer to the saved object via `Placeholder::Ptr()` as `void*`.
But anyway, Variable needs to know `T` so could it `delete<T>(ptr)` and so could `Variable::Get` checks the expected type and the saved object's type.
We save `T` in `PlaceholderImpl`, the implementation of `Placeholder`. Please be aware that `PlaceholderImpl` is a class template and `T` is passed in as a template parameter.
Because `PlaceholderImpl` knows `T`, it can save and return `typeid(T)` for the type comparison in `Variable::Get` and `Variable::GetMutable`.
## Conclusion
The technique type hiding utilizes C++ class templates, interface and derivation, and C++ RTTI (typeid). This combination saves us from definition something like `caffe2::TypeMata`, which takes hundreds of lines of C++ code.
/*
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 <memory>
#include <string>
#include "gtest/gtest.h"
#include "paddle/framework/variable.h"
TEST(Variable, GetMutable) {
using paddle::framework::Variable;
struct Tensor {
int content_;
};
std::unique_ptr<Variable> v(new Variable());
Tensor* t = v->GetMutable<Tensor>();
t->content_ = 1234;
const Tensor& tt = v->Get<Tensor>();
EXPECT_EQ(1234, tt.content_);
std::string* s = v->GetMutable<std::string>();
*s = "hello";
const std::string& ss = v->Get<std::string>();
EXPECT_EQ("hello", ss);
}
......@@ -12,7 +12,7 @@ endif()
add_library(paddle_function STATIC ${cpp_files} ${cu_objs})
add_dependencies(paddle_function ${external_project_dependencies})
add_dependencies(paddle_function gen_proto_cpp)
add_dependencies(paddle_function paddle_proto)
if(WITH_TESTING)
if(WITH_GPU)
......
......@@ -58,7 +58,7 @@ endif()
add_style_check_target(paddle_gserver ${GSERVER_SOURCES})
add_style_check_target(paddle_gserver ${GSERVER_HEADER})
add_dependencies(paddle_gserver gen_proto_cpp)
add_dependencies(paddle_gserver paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
add_subdirectory(tests)
endif()
/* 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 "Evaluator.h"
#include "paddle/gserver/layers/DetectionUtil.h"
using std::map;
using std::vector;
using std::pair;
using std::make_pair;
namespace paddle {
/**
* @brief detection map Evaluator
*
* The config file api is detection_map_evaluator.
*/
class DetectionMAPEvaluator : public Evaluator {
public:
DetectionMAPEvaluator()
: evaluateDifficult_(false), cpuOutput_(nullptr), cpuLabel_(nullptr) {}
virtual void start() {
Evaluator::start();
allTruePos_.clear();
allFalsePos_.clear();
numPos_.clear();
}
virtual real evalImp(std::vector<Argument>& arguments) {
overlapThreshold_ = config_.overlap_threshold();
backgroundId_ = config_.background_id();
evaluateDifficult_ = config_.evaluate_difficult();
apType_ = config_.ap_type();
MatrixPtr detectTmpValue = arguments[0].value;
Matrix::resizeOrCreate(cpuOutput_,
detectTmpValue->getHeight(),
detectTmpValue->getWidth(),
false,
false);
MatrixPtr labelTmpValue = arguments[1].value;
Matrix::resizeOrCreate(cpuLabel_,
labelTmpValue->getHeight(),
labelTmpValue->getWidth(),
false,
false);
cpuOutput_->copyFrom(*detectTmpValue);
cpuLabel_->copyFrom(*labelTmpValue);
Argument label = arguments[1];
const int* labelIndex = label.sequenceStartPositions->getData(false);
size_t batchSize = label.getNumSequences();
vector<map<size_t, vector<NormalizedBBox>>> allGTBBoxes;
vector<map<size_t, vector<pair<real, NormalizedBBox>>>> allDetectBBoxes;
for (size_t n = 0; n < batchSize; ++n) {
map<size_t, vector<NormalizedBBox>> bboxes;
for (int i = labelIndex[n]; i < labelIndex[n + 1]; ++i) {
vector<NormalizedBBox> bbox;
getBBoxFromLabelData(cpuLabel_->getData() + i * 6, 1, bbox);
int c = cpuLabel_->getData()[i * 6];
bboxes[c].push_back(bbox[0]);
}
allGTBBoxes.push_back(bboxes);
}
size_t n = 0;
const real* cpuOutputData = cpuOutput_->getData();
for (size_t imgId = 0; imgId < batchSize; ++imgId) {
map<size_t, vector<pair<real, NormalizedBBox>>> bboxes;
size_t curImgId = static_cast<size_t>((cpuOutputData + n * 7)[0]);
while (curImgId == imgId && n < cpuOutput_->getHeight()) {
vector<real> label;
vector<real> score;
vector<NormalizedBBox> bbox;
getBBoxFromDetectData(cpuOutputData + n * 7, 1, label, score, bbox);
bboxes[label[0]].push_back(make_pair(score[0], bbox[0]));
++n;
curImgId = static_cast<size_t>((cpuOutputData + n * 7)[0]);
}
allDetectBBoxes.push_back(bboxes);
}
for (size_t n = 0; n < batchSize; ++n) {
for (map<size_t, vector<NormalizedBBox>>::iterator it =
allGTBBoxes[n].begin();
it != allGTBBoxes[n].end();
++it) {
size_t count = 0;
if (evaluateDifficult_) {
count = it->second.size();
} else {
for (size_t i = 0; i < it->second.size(); ++i)
if (!(it->second[i].isDifficult)) ++count;
}
if (numPos_.find(it->first) == numPos_.end() && count != 0) {
numPos_[it->first] = count;
} else {
numPos_[it->first] += count;
}
}
}
// calcTFPos
calcTFPos(batchSize, allGTBBoxes, allDetectBBoxes);
return 0;
}
virtual void printStats(std::ostream& os) const {
real mAP = calcMAP();
os << "Detection mAP=" << mAP;
}
virtual void distributeEval(ParameterClient2* client) {
LOG(FATAL) << "Distribute detection evaluation not implemented.";
}
protected:
void calcTFPos(const size_t batchSize,
const vector<map<size_t, vector<NormalizedBBox>>>& allGTBBoxes,
const vector<map<size_t, vector<pair<real, NormalizedBBox>>>>&
allDetectBBoxes) {
for (size_t n = 0; n < allDetectBBoxes.size(); ++n) {
if (allGTBBoxes[n].size() == 0) {
for (map<size_t, vector<pair<real, NormalizedBBox>>>::const_iterator
it = allDetectBBoxes[n].begin();
it != allDetectBBoxes[n].end();
++it) {
size_t label = it->first;
for (size_t i = 0; i < it->second.size(); ++i) {
allTruePos_[label].push_back(make_pair(it->second[i].first, 0));
allFalsePos_[label].push_back(make_pair(it->second[i].first, 1));
}
}
} else {
for (map<size_t, vector<pair<real, NormalizedBBox>>>::const_iterator
it = allDetectBBoxes[n].begin();
it != allDetectBBoxes[n].end();
++it) {
size_t label = it->first;
vector<pair<real, NormalizedBBox>> predBBoxes = it->second;
if (allGTBBoxes[n].find(label) == allGTBBoxes[n].end()) {
for (size_t i = 0; i < predBBoxes.size(); ++i) {
allTruePos_[label].push_back(make_pair(predBBoxes[i].first, 0));
allFalsePos_[label].push_back(make_pair(predBBoxes[i].first, 1));
}
} else {
vector<NormalizedBBox> gtBBoxes =
allGTBBoxes[n].find(label)->second;
vector<bool> visited(gtBBoxes.size(), false);
// Sort detections in descend order based on scores
std::sort(predBBoxes.begin(),
predBBoxes.end(),
sortScorePairDescend<NormalizedBBox>);
for (size_t i = 0; i < predBBoxes.size(); ++i) {
real maxOverlap = -1.0;
size_t maxIdx = 0;
for (size_t j = 0; j < gtBBoxes.size(); ++j) {
real overlap =
jaccardOverlap(predBBoxes[i].second, gtBBoxes[j]);
if (overlap > maxOverlap) {
maxOverlap = overlap;
maxIdx = j;
}
}
if (maxOverlap > overlapThreshold_) {
if (evaluateDifficult_ ||
(!evaluateDifficult_ && !gtBBoxes[maxIdx].isDifficult)) {
if (!visited[maxIdx]) {
allTruePos_[label].push_back(
make_pair(predBBoxes[i].first, 1));
allFalsePos_[label].push_back(
make_pair(predBBoxes[i].first, 0));
visited[maxIdx] = true;
} else {
allTruePos_[label].push_back(
make_pair(predBBoxes[i].first, 0));
allFalsePos_[label].push_back(
make_pair(predBBoxes[i].first, 1));
}
}
} else {
allTruePos_[label].push_back(make_pair(predBBoxes[i].first, 0));
allFalsePos_[label].push_back(
make_pair(predBBoxes[i].first, 1));
}
}
}
}
}
}
}
real calcMAP() const {
real mAP = 0.0;
size_t count = 0;
for (map<size_t, size_t>::const_iterator it = numPos_.begin();
it != numPos_.end();
++it) {
size_t label = it->first;
size_t labelNumPos = it->second;
if (labelNumPos == 0 || allTruePos_.find(label) == allTruePos_.end())
continue;
vector<pair<real, size_t>> labelTruePos = allTruePos_.find(label)->second;
vector<pair<real, size_t>> labelFalsePos =
allFalsePos_.find(label)->second;
// Compute average precision.
vector<size_t> tpCumSum;
getAccumulation(labelTruePos, &tpCumSum);
vector<size_t> fpCumSum;
getAccumulation(labelFalsePos, &fpCumSum);
std::vector<real> precision, recall;
size_t num = tpCumSum.size();
// Compute Precision.
for (size_t i = 0; i < num; ++i) {
CHECK_LE(tpCumSum[i], labelNumPos);
precision.push_back(static_cast<real>(tpCumSum[i]) /
static_cast<real>(tpCumSum[i] + fpCumSum[i]));
recall.push_back(static_cast<real>(tpCumSum[i]) / labelNumPos);
}
// VOC2007 style
if (apType_ == "11point") {
vector<real> maxPrecisions(11, 0.0);
int startIdx = num - 1;
for (int j = 10; j >= 0; --j)
for (int i = startIdx; i >= 0; --i) {
if (recall[i] < j / 10.) {
startIdx = i;
if (j > 0) maxPrecisions[j - 1] = maxPrecisions[j];
break;
} else {
if (maxPrecisions[j] < precision[i])
maxPrecisions[j] = precision[i];
}
}
for (int j = 10; j >= 0; --j) mAP += maxPrecisions[j] / 11;
++count;
} else if (apType_ == "Integral") {
// Nature integral
real averagePrecisions = 0.;
real prevRecall = 0.;
for (size_t i = 0; i < num; ++i) {
if (fabs(recall[i] - prevRecall) > 1e-6)
averagePrecisions += precision[i] * fabs(recall[i] - prevRecall);
prevRecall = recall[i];
}
mAP += averagePrecisions;
++count;
} else {
LOG(FATAL) << "Unkown ap version: " << apType_;
}
}
if (count != 0) mAP /= count;
return mAP * 100;
}
void getAccumulation(vector<pair<real, size_t>> inPairs,
vector<size_t>* accuVec) const {
std::stable_sort(
inPairs.begin(), inPairs.end(), sortScorePairDescend<size_t>);
accuVec->clear();
size_t sum = 0;
for (size_t i = 0; i < inPairs.size(); ++i) {
sum += inPairs[i].second;
accuVec->push_back(sum);
}
}
std::string getTypeImpl() const { return "detection_map"; }
real getValueImpl() const { return calcMAP(); }
private:
real overlapThreshold_; // overlap threshold when determining whether matched
bool evaluateDifficult_; // whether evaluate difficult ground truth
size_t backgroundId_; // class index of background
std::string apType_; // how to calculate mAP (Integral or 11point)
MatrixPtr cpuOutput_;
MatrixPtr cpuLabel_;
map<size_t, size_t> numPos_; // counts of true objects each classification
map<size_t, vector<pair<real, size_t>>>
allTruePos_; // true positive prediction
map<size_t, vector<pair<real, size_t>>>
allFalsePos_; // false positive prediction
};
REGISTER_EVALUATOR(detection_map, DetectionMAPEvaluator);
} // namespace paddle
......@@ -166,11 +166,21 @@ MultiGradientMachine::MultiGradientMachine(const ModelConfig& config,
outArgStream_ = HPPL_STREAM_1;
start();
}
void MultiGradientMachine::start() {
for (auto& thread : threads_) {
thread->start();
}
}
void MultiGradientMachine::finish() {
for (auto& thread : threads_) {
thread->stop();
}
}
std::vector<const std::vector<ParameterPtr>*>
MultiGradientMachine::getSlaveParameters() {
std::vector<const std::vector<ParameterPtr>*> vec;
......@@ -326,12 +336,6 @@ void MultiGradientMachine::onPassEnd() {
}
}
void MultiGradientMachine::finish() {
for (auto& thread : threads_) {
thread->stop();
}
}
Evaluator* MultiGradientMachine::makeEvaluator() const {
return threads_[0]->getGradientMachine()->makeEvaluator();
}
......@@ -445,7 +449,7 @@ TrainerThread::TrainerThread(const ModelConfig& config,
gradStream_ = HPPL_STREAM_2;
valueStream_ = HPPL_STREAM_3;
stopping_ = false;
stopping_ = true;
updateCounter_ = 0;
parameterUpdated_ = false;
}
......@@ -453,6 +457,10 @@ TrainerThread::TrainerThread(const ModelConfig& config,
TrainerThread::~TrainerThread() { stop(); }
void TrainerThread::start() {
if (!stopping_) return;
stopping_ = false;
gradientMachine_->start();
computeThread_.reset(new std::thread([this]() { computeThread(); }));
......@@ -593,7 +601,7 @@ void TrainerThread::backward() {
void TrainerThread::backwardCallback(Parameter* para) {
// CPU parameters are merged in the end
if (!para->useGpu()) return;
if (!para->useGpu() || para->isStatic()) return;
int paramId = para->getID();
if (multiMachine_->getNumThreads() == 1) {
......
......@@ -176,6 +176,10 @@ public:
explicit MultiGradientMachine(const ModelConfig& config, bool useGpu);
virtual void start();
virtual void finish();
virtual void prefetch(const std::vector<Argument>& inArgs);
virtual void forward(const std::vector<Argument>& inArgs,
......@@ -193,8 +197,6 @@ public:
virtual void onPassEnd();
virtual void finish();
virtual Evaluator* makeEvaluator() const;
virtual void eval(Evaluator* evaluator) const;
......
......@@ -241,11 +241,14 @@ void NeuralNetwork::forward(const std::vector<Argument>& inArgs,
dataLayers_[i]->setData(inArgs[i]);
}
gLayerStackTrace.set_stage(true);
{
for (auto& layer : layers_) {
REGISTER_TIMER_INFO("ForwardTimer", layer->getName().c_str());
gLayerStackTrace.push(layer->getName());
layer->forward(passType);
gLayerStackTrace.pop(layer->getName());
}
}
......@@ -254,9 +257,6 @@ void NeuralNetwork::forward(const std::vector<Argument>& inArgs,
for (auto& layer : outputLayers_) {
outArgs->push_back(layer->getOutput());
}
if (passType == PASS_TEST) {
gLayerStackTrace.clear();
}
}
void NeuralNetwork::resetState() {
......@@ -283,9 +283,10 @@ void NeuralNetwork::getState(MachineState& machineState) {
}
void NeuralNetwork::backward(const UpdateCallback& callback) {
gLayerStackTrace.pop(""); // tell layer trace is during backward.
gLayerStackTrace.set_stage(false);
FOR_EACH_R(layer, layers_) {
REGISTER_TIMER_INFO("BackwardTimer", (*layer)->getName().c_str());
gLayerStackTrace.push((*layer)->getName());
if ((*layer)->needGradient()) {
(*layer)->backward(callback);
}
......@@ -308,35 +309,35 @@ public:
void addEvaluator(std::unique_ptr<Evaluator>&& evaluator) {
evaluators_.emplace_back(std::move(evaluator));
}
virtual void start() {
void start() override {
for (auto& evaluator : evaluators_) {
evaluator->start();
}
}
virtual void finish() {
void finish() override {
for (auto& evaluator : evaluators_) {
evaluator->finish();
}
}
virtual void eval(const NeuralNetwork& nn) {
void eval(const NeuralNetwork& nn) override {
for (auto& evaluator : evaluators_) {
evaluator->eval(nn);
}
}
virtual real evalImp(std::vector<Argument>& arguments) {
real evalImp(std::vector<Argument>& arguments) override {
(void)arguments;
return -1;
}
virtual void printStats(std::ostream& os) const {
void printStats(std::ostream& os) const override {
for (auto& evaluator : evaluators_) {
evaluator->printStats(os);
os << ' ';
}
}
virtual void distributeEval(ParameterClient2* client) {
void distributeEval(ParameterClient2* client) override {
for (auto& evaluator : evaluators_) {
evaluator->distributeEval(client);
}
......@@ -351,7 +352,7 @@ public:
* @brief getNames will return all inside evaluators' names.
* @param names [out]: return names.
*/
void getNames(std::vector<std::string>* names) {
void getNames(std::vector<std::string>* names) override {
for (auto& eval : evaluators_) {
eval->getNames(names);
}
......@@ -360,7 +361,7 @@ public:
/**
* @brief getValue could get all inside evaluators' value.
*/
real getValue(const std::string& name, Error* err) const {
real getValue(const std::string& name, Error* err) const override {
return this->getMethodHelper<real>(
name, err, [&name, err](const std::unique_ptr<Evaluator>& eval) {
return eval->getValue(name, err);
......@@ -370,7 +371,7 @@ public:
/**
* @brief getType could get all inside evaluators' type.
*/
std::string getType(const std::string& name, Error* err) const {
std::string getType(const std::string& name, Error* err) const override {
return this->getMethodHelper<std::string>(
name, err, [&name, err](const std::unique_ptr<Evaluator>& eval) {
return eval->getType(name, err);
......@@ -395,6 +396,30 @@ private:
}
};
class SubnetEvaluator : public CombinedEvaluator {
public:
SubnetEvaluator(const std::string& layerName,
std::unique_ptr<Evaluator>&& evaluator)
: layerName_(layerName) {
addEvaluator(std::move(evaluator));
}
virtual void eval(const NeuralNetwork& nn) override {
const LayerPtr& layer = nn.getLayer(layerName_);
CHECK(layer) << "Nonexisted layer: " << layerName_ << " in submodel "
<< nn.getName();
bool accessed = false;
layer->accessSubNetwork([this, &accessed](NeuralNetwork& subnet) {
subnet.eval(evaluators_[0].get());
accessed = true;
});
CHECK(accessed) << "There is no subnetwork for layer " << layerName_
<< " in submodel " << nn.getName();
}
protected:
std::string layerName_;
};
Evaluator* NeuralNetwork::makeEvaluator() const {
CombinedEvaluator* combinedEvaluator = new CombinedEvaluator();
auto subModelConfig = std::find_if(config_.sub_models().begin(),
......@@ -421,6 +446,15 @@ Evaluator* NeuralNetwork::makeEvaluator() const {
combinedEvaluator->addEvaluator(std::move(evaluator));
}
}
for (auto& layer : layers_) {
layer->accessSubNetwork(
[layer, combinedEvaluator](NeuralNetwork& subnet) {
std::unique_ptr<Evaluator> subEvaluator(new SubnetEvaluator(
layer->getName(),
std::unique_ptr<Evaluator>(subnet.makeEvaluator())));
combinedEvaluator->addEvaluator(std::move(subEvaluator));
});
}
} else {
for (const EvaluatorConfig& evalConfig : config_.evaluators()) {
std::unique_ptr<Evaluator> evaluator(Evaluator::create(evalConfig));
......
......@@ -129,6 +129,8 @@ public:
static NeuralNetwork* newNeuralNetwork(const std::string& name = "",
NeuralNetwork* rootNetwork = nullptr);
const std::string& getName() const { return subModelName_; }
protected:
/**
* The constructor of NeuralNetwork.
......
......@@ -208,6 +208,7 @@ void RecurrentGradientMachine::init(
});
CHECK(subModelConfig != config.sub_models().end());
reversed_ = subModelConfig->reversed();
generating_ = subModelConfig->has_generator();
inFrameLines_.resize(subModelConfig->in_links_size());
for (size_t i = 0; i < inFrameLines_.size(); ++i) {
......@@ -287,10 +288,6 @@ void RecurrentGradientMachine::init(
parameterIds_.push_back(para->getID());
}
}
if (subModelConfig->evaluator_names_size() > 0) {
evaluator_.reset(frames_[0]->makeEvaluator());
}
}
void RecurrentGradientMachine::resizeOrCreateFrames(int numFrames) {
......@@ -538,7 +535,7 @@ void RecurrentGradientMachine::forward(const std::vector<Argument>& inArgs,
The outputs are outFramesLines_[i].agentLayer
*/
if (inFrameLines_.empty() && passType == PASS_TEST) {
if (generating_) {
generateSequence();
return;
} // else forward..
......@@ -561,14 +558,14 @@ void RecurrentGradientMachine::forward(const std::vector<Argument>& inArgs,
std::vector<Argument> outArgs;
frames_[i]->forward(inArgs, &outArgs, passType);
}
if (evaluator_ && passType == PASS_TEST) {
this->eval(evaluator_.get());
}
reorganizeOutput(passType);
}
void RecurrentGradientMachine::backward(const UpdateCallback& callback) {
if (generating_) {
return;
}
REGISTER_TIMER_INFO("RecurrentBwTime", "RecurrentBwTime");
AsyncGpuBlock asyncGpuBlock;
for (int i = maxSequenceLength_ - 1; i >= 0; --i) {
......@@ -577,11 +574,6 @@ void RecurrentGradientMachine::backward(const UpdateCallback& callback) {
for (auto& memoryFrameLine : memoryFrameLines_) {
memoryFrameLine.bootLayer->backward(nullptr);
}
// call printers here so the gradient can be printed
if (evaluator_) {
this->eval(evaluator_.get());
}
}
void RecurrentGradientMachine::forwardBackward(
......@@ -595,9 +587,9 @@ void RecurrentGradientMachine::forwardBackward(
void RecurrentGradientMachine::eval(Evaluator* evaluator) const {
// call printers frame by frame
for (int i = 0; i < maxSequenceLength_; ++i) {
LOG(INFO) << "Recurrent Layer Group eval frame " << i << " begin";
VLOG(2) << "Recurrent Layer Group eval frame " << i << " begin";
evaluator->eval(*(frames_[i].get()));
LOG(INFO) << "Recurrent Layer Group eval frame " << i << " end";
VLOG(2) << "Recurrent Layer Group eval frame " << i << " end";
}
}
......@@ -1093,10 +1085,6 @@ void RecurrentGradientMachine::oneWaySearch(size_t batchSize) {
copyDataOutlinkFrame(machineCur);
// call value printer
if (evaluator_) {
evaluator_->eval(*(frames_[machineCur].get()));
}
// check eos
const IVectorPtr& eosVec =
eosFrameLine_->layers[machineCur]->getOutput().ids;
......@@ -1321,11 +1309,10 @@ void RecurrentGradientMachine::fillGenOutputs() {
batchMachineIdVec_.clear();
generator_.ids.clear();
int* starts = generator_.outArg.sequenceStartPositions->getMutableData(false);
starts[0] = 0;
if (numResults > 1) {
real* probs = generator_.outArg.in->getData();
int* starts =
generator_.outArg.sequenceStartPositions->getMutableData(false);
starts[0] = 0;
for (size_t i = 0; i < finalPaths_.size(); ++i) {
for (size_t j = 0; j < finalPaths_[i].size(); ++j) {
Path& path = finalPaths_[i][j];
......@@ -1348,7 +1335,10 @@ void RecurrentGradientMachine::fillGenOutputs() {
} else {
for (size_t i = 0; i < finalPaths_.size(); ++i) {
CHECK(!finalPaths_[i].empty());
generator_.ids = finalPaths_[i][0].ids;
generator_.ids.insert(generator_.ids.begin(),
finalPaths_[i][0].ids.begin(),
finalPaths_[i][0].ids.end());
starts[i + 1] = starts[i] + finalPaths_[i][0].ids.size();
}
}
}
......
......@@ -414,6 +414,7 @@ protected:
std::vector<int> ids; // store generated sequences
Argument outArg; // final output argument
};
bool generating_;
Generator generator_;
std::vector<std::unique_ptr<NeuralNetwork>> frames_;
......@@ -428,8 +429,6 @@ protected:
std::vector<int>
parameterIds_; // parameters actually used by this Layer Group
std::unique_ptr<Evaluator> evaluator_; // frame printers in this layer group
// store final argument of outFrameLines_
std::vector<Argument> dataArgs_;
// store each frame's output argument of outFrameLines_
......
......@@ -109,6 +109,40 @@ void GatherAgentLayer::forwardValue(PassType passType) {
}
}
namespace {
// dest[index[i]] <- src[i] for each i
void copyElements(const IVector& srcVec,
const IVector& indexVec,
IVector& destVec) {
const int* src = srcVec.getData();
const int* index = indexVec.getData();
int* dest = destVec.getData();
int len = indexVec.getSize();
CHECK_EQ(srcVec.getSize(), indexVec.getSize());
for (int i = 0; i < len; ++i) {
dest[index[i]] = src[i];
}
}
}
void GatherAgentLayer::forwardIds(PassType passType) {
IVectorPtr realId = realLayers_[0]->getOutputLabel();
if (!realId) return;
IVector::resizeOrCreate(output_.ids, allIds_->getSize(), useGpu_);
IVectorPtr outId = output_.ids;
idsVec_.resize(idIndex_.size());
for (size_t i = 0; i < realLayers_.size(); ++i) {
const IVectorPtr& realId = realLayers_[i]->getOutputLabel();
idsVec_[i] = IVector::create(allIds_->getData() + idIndex_[i],
/* size */ realId->getSize(),
useGpu_);
execViaCpu(&copyElements, *realId, *idsVec_[i], *outId);
}
}
void GatherAgentLayer::backward(const UpdateCallback& callback) {
(void)callback;
const MatrixPtr& outputGrad = getOutputGrad();
......@@ -136,23 +170,22 @@ void ScatterAgentLayer::forward(PassType passType) {
CHECK_EQ(realLayer_->getDeviceId(), this->getDeviceId());
int width = this->getSize();
if (selectionMode_) {
forwardWithSelection(passType);
} else {
if (realOutArg_.hasSeq()) {
forwardSequence(passType);
} else if (realOutArg_.value || realOutArg_.ids) {
output_.subArgFrom(realOutArg_,
/* offset */ idIndex_,
idSize_,
width,
useGpu_,
/* trans */ false,
/* seqFlag */ true,
/* seqStart */ seqStartPosIndex_,
/* seqSize */ numSequences_);
} else {
output_.subArgFrom(
realOutArg_, /* offset */ idIndex_, idSize_, width, useGpu_);
} else { // used in generation
if (realLayer_->getOutput().ids) {
IVector::resizeOrCreate(output_.ids, ids_->getSize(), useGpu_);
output_.ids->selectFrom(*realLayer_->getOutput().ids, *ids_);
}
if (realLayer_->getOutput().value) {
int height = ids_->getSize();
resetOutput(height, width);
const MatrixPtr& outV = getOutputValue();
const MatrixPtr& realV = realLayer_->getOutputValue();
outV->selectRows(*realV, *ids_);
}
}
}
......@@ -160,6 +193,8 @@ void ScatterAgentLayer::forward(PassType passType) {
void ScatterAgentLayer::backward(const UpdateCallback& callback) {
(void)callback;
CHECK(!selectionMode_);
const MatrixPtr& outputGrad = realOutArg_.grad;
const MatrixPtr& realGrad = realLayer_->getOutputGrad();
if (realGrad) {
......@@ -174,42 +209,7 @@ void ScatterAgentLayer::backward(const UpdateCallback& callback) {
REGISTER_LAYER(gather_agent, GatherAgentLayer);
REGISTER_LAYER(scatter_agent, ScatterAgentLayer);
void GatherAgentLayer::forwardIds(PassType passType) {
int height = 0;
IVectorPtr idReal = realLayers_[0]->getOutputLabel();
if (!idReal) return;
if (output_.subSequenceStartPositions) {
int* starts = output_.subSequenceStartPositions->getMutableData(false);
// Gather generator.idsVec
// if is beam search generation result. Get first result.
if (idReal->getData()[idReal->getSize() - 1] == -1) {
for (size_t i = 0; i < realLayers_.size(); ++i) {
// The first element stores first result size
idReal = realLayers_[i]->getOutputLabel();
idReal->subVecFrom(*idReal, 1, idReal->getData()[0]);
}
}
for (size_t i = 0; i < realLayers_.size(); ++i) {
CHECK(realLayers_[i]->getOutputLabel());
starts[i] = height;
height += realLayers_[i]->getOutputLabel()->getSize();
}
starts[realLayers_.size()] = height;
output_.sequenceStartPositions->getMutableData(false)[1] = height;
IVector::resizeOrCreate(output_.ids, height, false);
for (size_t i = 0; i < realLayers_.size(); ++i) {
output_.ids->subVec(starts[i], starts[i + 1] - starts[i])
->copyFrom(*realLayers_[i]->getOutputLabel());
}
} else {
LOG(FATAL) << "Not implemented";
}
}
void ScatterAgentLayer::forwardSequence(PassType passType) {
void ScatterAgentLayer::forwardWithSelection(PassType passType) {
Layer::forward(passType);
CHECK_EQ(realLayer_->getDeviceId(), this->getDeviceId());
......@@ -220,17 +220,19 @@ void ScatterAgentLayer::forwardSequence(PassType passType) {
AsyncGpuBlock asyncGpuBlock;
REGISTER_TIMER_INFO("SequenceAgentLayerForward", getName().c_str());
if (realOutArg_.value || realOutArg_.ids) {
CHECK(realOutArg_.sequenceStartPositions);
output_.subArgFrom(realOutArg_,
/* offset */ idIndex_,
idSize_,
width,
useGpu_,
/* trans */ false,
/* seqFlag */ true,
/* seqStart */ seqStartPosIndex_,
/* seqSize */ numSequences_);
if (!input.hasSeq()) {
if (realLayer_->getOutput().ids) {
IVector::resizeOrCreate(output_.ids, ids_->getSize(), useGpu_);
output_.ids->selectFrom(*realLayer_->getOutput().ids, *ids_);
}
if (realLayer_->getOutput().value) {
int height = ids_->getSize();
resetOutput(height, width);
const MatrixPtr& outV = getOutputValue();
const MatrixPtr& realV = realLayer_->getOutputValue();
outV->selectRows(*realV, *ids_);
}
} else {
// Putting the generation logic here is really an ugly hack!
// used in generation
......
......@@ -110,6 +110,9 @@ protected:
// of real layer.
ICpuGpuVectorPtr inputStartPos_;
// true for setRealLayer, false for setRealLayerAndOutput
bool selectionMode_;
public:
explicit ScatterAgentLayer(const LayerConfig& config) : Layer(config) {}
......@@ -137,6 +140,7 @@ public:
} else {
cpuIds_ = ids_;
}
selectionMode_ = true;
}
// set real layer and output, [idIndex, idIndex + idSize) of *ids*
......@@ -153,6 +157,7 @@ public:
idIndex_ = idIndex;
idSize_ = idSize;
handleBackward_ = handleBackward;
selectionMode_ = false;
}
void setSequenceStartPositions(const ICpuGpuVectorPtr& sequenceStartPositions,
......@@ -166,7 +171,7 @@ public:
void forward(PassType passType) override;
void backward(const UpdateCallback& callback) override;
void forwardSequence(PassType passType);
void forwardWithSelection(PassType passType);
};
} // namespace paddle
......@@ -191,6 +191,11 @@ void Layer::addOutputArgument(int deviceId) {
void Layer::copyOutputToOtherDevice() {
for (size_t i = 0; i != outputOtherDevice_.size(); i++) {
SetDevice device(outputOtherDevice_[i].deviceId);
// If outputOtherDevice_[i].value is a CpuMatrix,
// the copyFrom is a synchronous interface.
// If outputOtherDevice_[i].value is a GpuMatrix, since subsequent
// calculations are all on HPPL_STREAM_DEFAULT,
// copyFrom can be an asynchronous interface.
outputOtherDevice_[i].value->copyFrom(*getOutputValue(),
HPPL_STREAM_DEFAULT);
outputOtherDevice_[i].sequenceStartPositions =
......
......@@ -138,6 +138,23 @@ void testEvaluatorAll(TestConfig testConf,
testEvaluator(testConf, testEvaluatorName, batchSize, false);
}
TEST(Evaluator, detection_map) {
TestConfig config;
config.evaluatorConfig.set_type("detection_map");
config.evaluatorConfig.set_overlap_threshold(0.5);
config.evaluatorConfig.set_background_id(0);
config.evaluatorConfig.set_ap_type("Integral");
config.evaluatorConfig.set_evaluate_difficult(0);
config.inputDefs.push_back({INPUT_DATA, "output", 7});
config.inputDefs.push_back({INPUT_SEQUENCE_DATA, "label", 6});
config.evaluatorConfig.set_evaluate_difficult(false);
testEvaluatorAll(config, "detection_map", 100);
config.evaluatorConfig.set_evaluate_difficult(true);
testEvaluatorAll(config, "detection_map", 100);
}
TEST(Evaluator, classification_error) {
TestConfig config;
config.evaluatorConfig.set_type("classification_error");
......
......@@ -33,7 +33,7 @@ endif()
add_style_check_target(paddle_math ${MATH_SOURCES})
add_style_check_target(paddle_math ${MATH_HEADERS})
add_dependencies(paddle_math gen_proto_cpp) # depends
add_dependencies(paddle_math paddle_proto ${external_project_dependencies}) # depends
if(WITH_TESTING)
add_subdirectory(tests)
endif()
......@@ -1565,6 +1565,8 @@ void CpuMatrix::copyFrom(const Matrix& src, hl_stream_t stream) {
const_cast<real*>(src.getData()),
sizeof(real) * elementCnt_,
stream);
// There is a need to add synchronization to ensure that the data is copied.
hl_stream_synchronize(stream);
} else if (typeid(src) == typeid(CpuMatrix)) {
memcpy(data_, src.getData(), sizeof(real) * elementCnt_);
} else {
......
......@@ -239,7 +239,8 @@ public:
LOG(FATAL) << "Not implemented";
}
// asynchronous copy
// For GpuMatrix this is an asynchronous copy interface
// For CpuMatrix this is an synchronous copy interface
virtual void copyFrom(const Matrix& src, hl_stream_t stream) {
LOG(FATAL) << "Not implemented";
}
......
......@@ -657,6 +657,8 @@ void CpuVectorT<T>::copyFrom(const VectorT<T>& src, hl_stream_t stream) {
(void*)src.getData(),
sizeof(T) * this->getSize(),
stream);
// There is a need to add synchronization to ensure that the data is copied.
hl_stream_synchronize(stream);
} else {
src.copyTo(this);
}
......
......@@ -168,11 +168,11 @@ public:
virtual void copyFrom(const VectorT<T>& src) = 0;
/**
* If use_gpu, this function will push the copy-task to the specifed-stream
* and return immediately.
* If GpuVector, this function is an asynchronous interface,
* will push the copy-task to the specifed-stream and return immediately.
*
* If not use GPU, this function is same as
* the copyFrom(const VectorT<T>& src), which use stream HPPL_STREAM_DEFAULT.
* If CpuVector, this function is an synchronous interface,
* same as the copyFrom(const VectorT<T>& src).
*/
virtual void copyFrom(const VectorT<T>& src, hl_stream_t stream) = 0;
......
......@@ -1127,4 +1127,18 @@ TEST(Matrix, MaxOutFwdBwd) {
}
}
TEST(CpuMatrix, copyFrom) {
const size_t height = 1000;
const size_t width = 1000;
CpuMatrix cpu(height, width);
GpuMatrix gpu(height, width);
CpuMatrix copy(height, width);
cpu.randomizeUniform();
gpu.copyFrom(cpu);
copy.copyFrom(gpu, HPPL_STREAM_DEFAULT);
TensorCheckEqual(cpu, copy);
}
#endif
---
Language: Cpp
BasedOnStyle: Google
Standard: Cpp11
...
add_subdirectory(detail)
## Design
### Usage
To allocate 4KB CPU memory:
```cpp
p = memory::Alloc(platform::CPUPlace(), 4*1024);
```
To allocate 4KB memory on the 3rd GPU:
```cpp
p = memory::Alloc(platform::GPUPlace(2), 4*1024);
```
To free memory and check the so-far used amount of memory on a place:
```cpp
auto pl = platform::GPUPlace(0);
p = memory::Alloc(pl, 4*1024);
cout << memory::Used(pl);
memory::Free(pl, p);
```
### API
In `paddle/memory/memory.h` we have:
```cpp
namespace memory {
template <typename Place> void* Alloc(Place, size_t);
template <typename Place> void Free(Place, void*);
template <typename Place> size_t Used(Place);
} // namespace memory
```
These function templates have specializations on either `platform::CPUPlace` or `platform::GPUPlace`:
```cpp
template<>
void* Alloc<CPUPlace>(CPUPlace p, size_t size) {
return GetCPUBuddyAllocator()->Alloc(size);
}
```
and
```cpp
template<>
void Alloc<GPUPlace>(GPUPlace p, size_t size) {
return GetGPUBuddyAllocator(p.id)->Alloc(size);
}
```
Similar specializations exist for `Free` and `Used`.
### Implementation
`GetCPUBuddyAllocator` and `GetGPUBuddyAllocator` are singletions.
```cpp
BuddyAllocator* GetCPUBuddyAllocator() {
static BuddyAllocator* a = NULL;
if (a == NULL) {
a = new BuddyAllocator(new CPUAllocator /*backup allocator*/, ...);
}
return a;
}
BuddyAllocator* GetGPUBuddyAllocator(int gpu_id) {
static BuddyAllocator* as = NULL;
if (as == NULL) {
as = new BuddyAllocator*[platform::NumGPUs()];
for (int gpu = 0; gpu < platform::NumGPUs(); gpu++) {
as[gpu] = new BuddyAllocator(new GPUAllocator(gpu) /* backup allocator */, ...);
}
}
return as[gpu_id);
```
#### `BuddyAllocator`
`BuddyAllocator` implements the buddy allocation algorithm. Its constructor takes parameters only related with the algorithm:
```cpp
BuddyAllocator::BuddyAllocator(initial_pool_size, max_pool_size) {
...
}
```
Please be aware that **`BuddyAllocator` always allocate aligned memory**, aligned on 32-bytes, which can hold a `BuddyAllocator::Block` object:
```cpp
class BuddyAllocator {
private:
struct Block {
size_t size;
Block* left, right;
size_t index; // allocator id
};
...
};
```
Because BuddyAllocator has the meta-data of each block, it can trace the used memory -- record the amount returned by `Alloc` freed in `Free`. Instead, `CPUAllocator` and `GPUAllocator` doesn't know the size of freed memory block and cannot do the trace.
#### System Allocators
The `GPUAllocator` and `CPUAllocator` are calls *system allocators*. They work as the fallback allocators of `BuddyAllocator`.
## Justification
I got inspiration from Majel and Caffe2, though above design look different from both.
### Caffe2
In Caffe2, `Tensor<Context>::mutable_data()` allocates the memroy. In particular, [`Tensor<Context>::mutable_data`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/tensor.h#L523) calls [`Tensor<Context>::raw_mutable_data`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/tensor.h#L459), which in turn calls [`Context::New`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/tensor.h#L479).
There are two implementations of `Context`:
1. [`CPUContext`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/context.h#L105), whose [`New` method](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/context.h#L131) calls [`g_cpu_allocator.get()->New(size_t)`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/context.cc#L15) to allocate the memory.
1. [`CUDAContext`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/context_gpu.h#L99), which has a data member [`int gpu_id_`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/context_gpu.h#L202). This looks very similar to class `majel::GPUPlace`, who also has an `int id_` data member. `CUDAContext::New(size_t)` calls [`g_cub_allocator->DeviceAllocate(&ptr, nbytes)`](https://github.com/caffe2/caffe2/blob/v0.7.0/caffe2/core/context_gpu.cu#L355) to allocate the memory.
### Majel
In Majel, there are basically two allocator types:
1. `cpu::SystemAllocator`, which has similar functionality to `caffe2::CPUContext::New/Delete`.
1. `gpu::SystemAllocator`, which has similar functionality to `caffe2::CUDAContext::New/Delete`.
However, memory allocation is not via these two allocators. Instead, these two allocators are defined in hidden namespaces.
In Majel there are hidden global variables like:
1. `cpu::SystemAllocator g_cpu_allocator`, and
1. `vector<gpu::SystemAllocator*> g_gpu_allocators(NUM_GPUS)`.
Programs allocate memory via a BuddyAllocator, which can take the `g_cpu_allocator` or a `g_gpu_allocators[gpu_id]` as its *fallback allocator*, so that if BuddyAllocator cannot find a block in its memory pool, it extends its memory pool by calling the fallback allocator's `New(size_t)`.
if(${WITH_GPU})
nv_library(system_allocator SRCS system_allocator.cc DEPS gflags)
nv_test(system_allocator_test SRCS system_allocator_test.cc DEPS system_allocator gflags)
else(${WITH_GPU})
cc_library(system_allocator SRCS system_allocator.cc DEPS gflags)
cc_test(system_allocator_test SRCS system_allocator_test.cc DEPS system_allocator gflags)
endif(${WITH_GPU})
/* 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/memory/detail/buddy_allocator.h"
namespace paddle {
namespace memory {
namespace detail {
BuddyAllocator::BuddyAllocator(size_t pool_size, size_t max_pools,
SystemAllocator* system_allocator)
: pool_size_(pool_size),
max_pools_(max_pools),
system_allocator_(system_allocator) {
PADDLE_ASSERT(pool_size > 0);
PADDLE_ASSERT(max_pools > 0);
PADDLE_ASSERT(system_allocator != nullptr);
}
} // namespace detail
} // namespace memory
} // 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. */
#pragma once
#include "paddle/memory/detail/system_allocator.h"
#include <mutex>
#include <vector>
namespace paddle {
namespace memory {
namespace detail {
class BuddyAllocator {
public:
BuddyAllocator(size_t pool_size, size_t max_pools,
SystemAllocator* system_allocator);
~BuddyAllocator();
void* Alloc(size_t size);
void Free(void*);
size_t Used();
private:
struct Block {
size_t size_;
Block* left_; // left buddy
Block* right_; // right buddy
};
// Initially, there is only one pool. If a Alloc founds not enough
// memory from that pool, and there has not been max_num_pools_,
// create a new pool by calling system_allocator_.Alloc(pool_size_).
std::vector<void*> pools_;
size_t pool_size_; // the size of each pool;
size_t max_num_pools_; // the size of all pools;
SystemAllocator* system_allocator_;
std::mutex mutex_;
// Disable copy and assignment.
BuddyAllocator(const BuddyAllocator&) = delete;
BuddyAllocator& operator=(const BuddyAllocator&) = delete;
};
BuddyAllocator<CPUAllocator>* GetCPUBuddyAllocator() {
static BuddyAllocator<CPUAllocator>* a = nullptr;
if (a == nullptr) {
a = new BuddyAllocator<CPUAllocator>();
}
return a;
}
#ifndef PADDLE_ONLY_CPU // The following code are for CUDA.
BuddyAllocator<GPUAllocator>* GetGPUBuddyAllocator(int gpu_id) {
static BuddyAllocator<GPUAllocator>** as = NULL;
if (as == NULL) {
int gpu_num = platform::GetDeviceCount();
as = new BuddyAllocator<GPUAllocator>*[gpu_num];
for (int gpu = 0; gpu < gpu_num; gpu++) {
as[gpu] = new BuddyAllocator<GPUAllocator>();
}
}
return as[gpu_id];
}
#endif // PADDLE_ONLY_CPU
} // namespace detail
} // namespace memory
} // 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/memory/detail/system_allocator.h"
#include <stdlib.h> // for malloc and free
#include <sys/mman.h> // for mlock and munlock
#include "gflags/gflags.h"
#include "paddle/platform/assert.h"
#include "paddle/platform/cuda.h"
// If use_pinned_memory is true, CPUAllocator calls mlock, which
// returns pinned and locked memory as staging areas for data exchange
// between host and device. Allocates too much would reduce the amount
// of memory available to the system for paging. So, by default, we
// should set false to use_pinned_memory.
DEFINE_bool(use_pinned_memory, false,
"If set, allocate cpu/gpu pinned memory.");
namespace paddle {
namespace memory {
namespace detail {
void* CPUAllocator::Alloc(size_t size) {
// According to http://www.cplusplus.com/reference/cstdlib/malloc/,
// malloc might not return nullptr if size is zero, but the returned
// pointer shall not be dereferenced -- so we make it nullptr.
if (size <= 0) return nullptr;
void* p = malloc(size);
if (p != nullptr && FLAGS_use_pinned_memory) {
mlock(p, size);
}
return p;
}
void CPUAllocator::Free(void* p, size_t size) {
if (p != nullptr && FLAGS_use_pinned_memory) {
munlock(p, size);
}
free(p);
}
#ifndef PADDLE_ONLY_CPU
void* GPUAllocator::Alloc(size_t size) {
// CUDA documentation doesn't explain if cudaMalloc returns nullptr
// if size is 0. We just make sure it does.
if (size <= 0) {
return nullptr;
}
void* p = 0;
cudaError_t result =
FLAGS_use_pinned_memory ? cudaMallocHost(&p, size) : cudaMalloc(&p, size);
if (result != cudaSuccess) {
cudaGetLastError(); // clear error if there is any.
}
return result == cudaSuccess ? p : nullptr;
}
void GPUAllocator::Free(void* p, size_t size) {
// Purposefully allow cudaErrorCudartUnloading, because
// that is returned if you ever call cudaFree after the
// driver has already shutdown. This happens only if the
// process is terminating, in which case we don't care if
// cudaFree succeeds.
cudaError_t err = FLAGS_use_pinned_memory ? cudaFreeHost(p) : cudaFree(p);
if (err != cudaErrorCudartUnloading) {
platform::throw_on_error(err, "cudaFree{Host} failed");
}
}
#endif // PADDLE_ONLY_CPU
} // namespace detail
} // namespace memory
} // 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. */
#pragma once
#include <stddef.h> // for size_t
namespace paddle {
namespace memory {
namespace detail {
// SystemAllocator is the parent class of CPUAllocator and
// GPUAllocator. A BuddyAllocator object uses a SystemAllocator*
// pointing to the underlying system allocator. An alternative to
// this class hierarchy is to pass a system allocator class to
// BuddyAllocator as a template parameter. This approach makes
// BuddyAllocator a class template, and it's very complicated
// algorithm would make the buddy_allocator.h messy.
class SystemAllocator {
public:
virtual ~SystemAllocator() {}
virtual void* Alloc(size_t size) = 0;
virtual void Free(void* p, size_t size) = 0;
};
class CPUAllocator : public SystemAllocator {
public:
virtual void* Alloc(size_t size);
virtual void Free(void* p, size_t size);
};
#ifndef PADDLE_ONLY_CPU
class GPUAllocator : public SystemAllocator {
public:
virtual void* Alloc(size_t size);
virtual void Free(void* p, size_t size);
};
#endif // PADDLE_ONLY_CPU
} // namespace detail
} // namespace memory
} // 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/memory/detail/system_allocator.h"
#include <memory>
#include <vector>
#include "gflags/gflags.h"
#include "gtest/gtest.h"
DECLARE_bool(use_pinned_memory);
void TestAllocator(paddle::memory::detail::SystemAllocator& a, size_t size) {
bool freed = false;
{
void* p = a.Alloc(size);
if (size > 0) {
EXPECT_NE(p, nullptr);
} else {
EXPECT_EQ(p, nullptr);
}
int* i = static_cast<int*>(p);
std::shared_ptr<int> ptr(i, [&](void* p) {
freed = true;
a.Free(p, size);
});
}
EXPECT_TRUE(freed);
}
TEST(CPUAllocator, NoLockMem) {
FLAGS_use_pinned_memory = false;
paddle::memory::detail::CPUAllocator a;
TestAllocator(a, 2048);
TestAllocator(a, 0);
}
TEST(CPUAllocator, LockMem) {
FLAGS_use_pinned_memory = true;
paddle::memory::detail::CPUAllocator a;
TestAllocator(a, 2048);
TestAllocator(a, 0);
}
#ifndef PADDLE_ONLY_CPU
TEST(GPUAllocator, NoStaging) {
FLAGS_use_pinned_memory = false;
paddle::memory::detail::GPUAllocator a;
TestAllocator(a, 2048);
TestAllocator(a, 0);
}
TEST(GPUAllocator, Staging) {
FLAGS_use_pinned_memory = true;
paddle::memory::detail::GPUAllocator a;
TestAllocator(a, 2048);
TestAllocator(a, 0);
}
#endif // PADDLE_ONLY_CPU
/* 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/memory/memory.h"
#include "paddle/memory/detail/buddy_allocator.h"
#include "paddle/memory/detail/system_allocator.h"
#include "paddle/platform/assert.h"
#include <boost/variant.hpp>
namespace paddle {
namespace memory {
void* Alloc(platform::Place pl, size_t size) {
#ifndef PADDLE_ONLY_CPU
if (paddle::platform::is_gpu_place(pl)) {
size_t gpu_id = boost::get<platform::GPUPlace>(pl).device;
return detail::GetGPUBuddyAllocator(gpu_id)->Alloc(size);
}
#endif // PADDLE_ONLY_CPU
PADDLE_ASSERT(paddle::platform::is_cpu_place(pl));
return detail::GetCPUBuddyAllocator()->Alloc(size);
}
void Free(paddle::platform::Place pl, void* p) {
#ifndef PADDLE_ONLY_CPU
if (paddle::platform::is_gpu_place(pl)) {
size_t gpu_id = boost::get<platform::GPUPlace>(pl).device;
detail::GetGPUBuddyAllocator(gpu_id)->Free(p);
}
#endif // PADDLE_ONLY_CPU
PADDLE_ASSERT(paddle::platform::is_cpu_place(pl));
detail::GetCPUBuddyAllocator()->Free(p);
}
size_t Used(paddle::platform::Place pl) {
#ifndef PADDLE_ONLY_CPU
if (paddle::platform::is_gpu_place(pl)) {
size_t gpu_id = boost::get<platform::GPUPlace>(pl).device;
return detail::GetGPUBuddyAllocator(gpu_id)->Used();
}
#endif // PADDLE_ONLY_CPU
PADDLE_ASSERT(paddle::platform::is_cpu_place(pl));
return detail::GetCPUBuddyAllocator()->Used();
}
} // namespace memory
} // namespace paddle
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
/* 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.
......@@ -10,24 +13,15 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
/**
* This header defines some useful attribute by each compiler. It is the
* abstract layer of compilers.
*/
#ifdef __GNUC__
#define GCC_VERSION \
(__GNUC__ * 10000 + __GNUC_MINOR__ * 100 + __GNUC_PATCHLEVEL__)
#else
#define GCC_VERSION
#endif
/**
* __must_check macro. It make the function's return value must be used,
* otherwise it will raise a compile warning. And also Paddle treat all compile
* warnings as errors.
*/
#if GCC_VERSION >= 30400
#define __must_check __attribute__((warn_unused_result))
#else
#define __must_check
#endif
#include "paddle/platform/place.h"
namespace paddle {
namespace memory {
void* Alloc(paddle::platform::Place, size_t);
void Free(paddle::platform::Place, void*);
size_t Used(paddle::platform::Place);
} // namespace memory
} // namespace paddle
......@@ -10,7 +10,7 @@ set(OPITMIZER_SRCS
)
add_library(paddle_optimizer STATIC ${OPITMIZER_SRCS})
add_dependencies(paddle_optimizer gen_proto_cpp)
add_dependencies(paddle_optimizer paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
......
......@@ -7,7 +7,7 @@ add_library(paddle_parameter STATIC
${PARAMETERS_SOURCES})
add_style_check_target(paddle_parameter ${PARAMETERS_SOURCES})
add_style_check_target(paddle_parameter ${PARAMETERS_HEADERS})
add_dependencies(paddle_parameter gen_proto_cpp)
add_dependencies(paddle_parameter paddle_proto ${external_project_dependencies})
if(WITH_TESTING)
add_subdirectory(tests)
endif()
......@@ -14,11 +14,13 @@ limitations under the License. */
#include "ParameterUpdaterHook.h"
#include <algorithm>
#include <atomic>
#include <fstream>
#include <mutex>
#include <thread>
#include <unordered_map>
#include <vector>
#include "paddle/math/Vector.h"
#include "paddle/parameter/Parameter.h"
......@@ -29,106 +31,76 @@ namespace paddle {
/**
* The static pruning hook
*
* Static means user load a mask map before training started. This map will
* define which link/weight between neural is disabled.
* Static means user specify a sparsity_ratio before training started, and the
* network will prune the parameters based on the sparsity_ratio. More details
* can be found https://arxiv.org/pdf/1506.02626.pdf.
*/
class StaticPruningHook : public IParameterUpdaterHook {
public:
/**
* The Mask Map Header.
* The map file started with this header.
*
* In Version 0, reset file will be:
* contains header.size bit, each bit means such weight is enabled or not.
* if bit is 1, then such weight is enabled.
* at end, the file will round to byte, and the low bits of end byte will be
* filled by zero.
*
*/
struct StaticMaskHeader {
uint32_t version;
size_t size;
} __attribute__((__packed__));
explicit StaticPruningHook(const std::string& mask_filename) : initCount_(0) {
bool ok = this->loadMaskFile(mask_filename);
if (!ok) {
LOG(WARNING) << "Fail to load mask file " << mask_filename
<< " in current directory, searching in init_model_path";
std::string combineMaskFilename =
path::join(FLAGS_init_model_path, mask_filename);
CHECK(this->loadMaskFile(combineMaskFilename))
<< "Cannot load " << mask_filename << " in ./" << mask_filename
<< " and " << combineMaskFilename;
explicit StaticPruningHook(const ParameterUpdaterHookConfig &hookConfig)
: initCount_(0) {
sparsityRatio_ = hookConfig.sparsity_ratio();
}
VLOG(3) << mask_filename << " mask size = " << this->mask_.size();
static bool sortPairAscend(const std::pair<real, size_t> &pair1,
const std::pair<real, size_t> &pair2) {
return pair1.first > pair2.first;
}
void update(Parameter* para) {
void update(Parameter *para) {
updateThreadChecker_.check();
auto& vec = para->getBuf(PARAMETER_GRADIENT);
auto &vec = para->getBuf(PARAMETER_GRADIENT);
if (vec) {
vec->dotMul(*maskVec_);
}
}
void init(Parameter* para) {
size_t initCount = this->initCount_.fetch_add(1);
CHECK_EQ(initCount, 0UL) << "Currently the StaticPruningHook must invoke "
"in same ParamterUpdater";
VLOG(3) << "Initialize Parameter " << para;
SetDevice device(para->getDeviceId());
void generateMask(Parameter *para) {
VectorPtr maskTemp = Vector::create(para->getSize(), false);
maskTemp->zeroMem();
real *maskTempData = maskTemp->getData();
size_t nonZeroNum = para->getSize() * (1 - sparsityRatio_);
auto maskVec = Vector::create(this->mask_.size(), false);
{ // Initialize maskVec with float mask vector
real* dataPtr = maskVec->getData();
size_t i = 0;
for (bool m : mask_) {
dataPtr[i++] = m ? 1.0 : 0.0;
}
}
VectorPtr paraVec = para->getBuf(PARAMETER_VALUE);
VectorPtr paraCpuCopy = Vector::create(para->getSize(), false);
paraCpuCopy->copyFrom(*paraVec);
std::vector<std::pair<real, size_t>> param;
for (size_t i = 0; i < para->getSize(); i++)
param.push_back(std::make_pair(fabs(paraCpuCopy->getData()[i]), i));
std::partial_sort(
param.begin(), param.begin() + nonZeroNum, param.end(), sortPairAscend);
for (size_t i = 0; i < nonZeroNum; i++) maskTempData[param[i].second] = 1.0;
// Currently just use a mask vector for hack.
// @TODO(yuyang18): Implemented the mask operation in vector.
if (para->useGpu()) {
maskVec_ = Vector::create(this->mask_.size(), para->useGpu());
maskVec_->copyFrom(*maskVec);
maskVec_ = Vector::create(para->getSize(), para->useGpu());
maskVec_->copyFrom(*maskTemp);
} else {
maskVec_ = maskVec;
maskVec_ = maskTemp;
}
auto& vec = para->getBuf(PARAMETER_VALUE);
vec->dotMul(*maskVec_);
}
private:
bool loadMaskFile(const std::string& mask_filename) {
std::ifstream fin;
fin.open(mask_filename);
if (fin.is_open()) {
StaticMaskHeader header;
fin.read(reinterpret_cast<char*>(&header), sizeof(StaticMaskHeader));
CHECK_EQ(header.version, 0UL);
mask_.resize(header.size);
uint8_t buf;
for (size_t i = 0; i < header.size; ++i, buf <<= 1) {
if (i % 8 == 0) {
fin.read(reinterpret_cast<char*>(&buf), sizeof(uint8_t));
}
mask_[i] = buf & 0x80;
}
fin.close();
return true;
} else {
return false;
}
void init(Parameter *para) {
generateMask(para);
size_t initCount = this->initCount_.fetch_add(1);
CHECK_EQ(initCount, 0UL) << "Currently the StaticPruningHook must invoke "
"in same ParamterUpdater";
VLOG(3) << "Initialize Parameter " << para;
SetDevice device(para->getDeviceId());
auto &paraVec = para->getBuf(PARAMETER_VALUE);
paraVec->dotMul(*maskVec_);
}
private:
SameThreadChecker updateThreadChecker_;
std::atomic<size_t> initCount_;
VectorPtr maskVec_;
std::vector<bool> mask_;
real sparsityRatio_;
};
IParameterUpdaterHook::IParameterUpdaterHook() {}
......@@ -145,7 +117,7 @@ IParameterUpdaterHook::~IParameterUpdaterHook() {}
*/
class StringIntPairHasher {
public:
size_t operator()(const std::pair<std::string, int>& k) const {
size_t operator()(const std::pair<std::string, int> &k) const {
return intHasher_(strHasher_(k.first) + k.second);
}
......@@ -162,19 +134,19 @@ static WeakKVCache<std::pair<std::string, int>,
/**
* ParameterUpdaterHook actually factory method.
*/
static IParameterUpdaterHook* createImpl(
const ParameterUpdaterHookConfig& config) {
auto& type = config.type();
static IParameterUpdaterHook *createImpl(
const ParameterUpdaterHookConfig &config) {
auto &type = config.type();
if (type == "pruning") {
if (config.has_purning_mask_filename()) {
return new StaticPruningHook(config.purning_mask_filename());
}
return new StaticPruningHook(config);
}
LOG(FATAL) << "Unknown Hook type: " << type;
return nullptr;
}
std::shared_ptr<IParameterUpdaterHook> IParameterUpdaterHook::create(
const ParameterConfig& paramConfig, int idx) {
const ParameterConfig &paramConfig, int idx) {
std::pair<std::string, int> key = {paramConfig.name(), idx};
return g_hookCache_.get(
key, [&] { return createImpl(paramConfig.update_hooks(idx)); });
......
/* 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
#ifndef PADDLE_ONLY_CPU
#include <thrust/system/cuda/error.h>
#include <thrust/system_error.h>
namespace paddle {
namespace platform {
inline void throw_on_error(cudaError_t e, const char* message) {
if (e) {
throw thrust::system_error(e, thrust::cuda_category(), message);
}
}
int GetDeviceCount(void) {
int count;
throw_on_error(cudaGetDeviceCount(&count), "cudaGetDeviceCount failed");
return count;
}
} // namespace platform
} // namespace paddle
#endif // PADDLE_ONLY_CPU
......@@ -8,8 +8,8 @@ namespace detail {
class PlacePrinter : public boost::static_visitor<> {
public:
PlacePrinter(std::ostream &os) : os_(os) {}
void operator()(const CpuPlace &) { os_ << "CpuPlace"; }
void operator()(const GpuPlace &p) { os_ << "GpuPlace(" << p.device << ")"; }
void operator()(const CPUPlace &) { os_ << "CPUPlace"; }
void operator()(const GPUPlace &p) { os_ << "GPUPlace(" << p.device << ")"; }
private:
std::ostream &os_;
......@@ -22,14 +22,14 @@ static Place the_default_place;
void set_place(const Place &place) { the_default_place = place; }
const Place &get_place() { return the_default_place; }
const GpuPlace default_gpu() { return GpuPlace(0); }
const CpuPlace default_cpu() { return CpuPlace(); }
const GPUPlace default_gpu() { return GPUPlace(0); }
const CPUPlace default_cpu() { return CPUPlace(); }
bool is_gpu_place(const Place &p) {
return boost::apply_visitor(IsGpuPlace(), p);
return boost::apply_visitor(IsGPUPlace(), p);
}
bool is_cpu_place(const Place &p) {
return !boost::apply_visitor(IsGpuPlace(), p);
return !boost::apply_visitor(IsGPUPlace(), p);
}
bool places_are_same_class(const Place &p1, const Place &p2) {
......
/* 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 <boost/variant.hpp>
#include <iostream>
namespace paddle {
namespace platform {
struct CpuPlace {
struct CPUPlace {
// WORKAROUND: for some reason, omitting this constructor
// causes errors with boost 1.59 and OSX
CpuPlace() {}
CPUPlace() {}
// needed for variant equality comparison
inline bool operator==(const CpuPlace &) const { return true; }
inline bool operator!=(const CpuPlace &) const { return false; }
inline bool operator==(const CPUPlace &) const { return true; }
inline bool operator!=(const CPUPlace &) const { return false; }
};
struct GpuPlace {
GpuPlace() : GpuPlace(0) {}
GpuPlace(int d) : device(d) {}
struct GPUPlace {
GPUPlace() : GPUPlace(0) {}
GPUPlace(int d) : device(d) {}
// needed for variant equality comparison
inline bool operator==(const GpuPlace &o) const { return device == o.device; }
inline bool operator!=(const GpuPlace &o) const { return !(*this == o); }
inline bool operator==(const GPUPlace &o) const { return device == o.device; }
inline bool operator!=(const GPUPlace &o) const { return !(*this == o); }
int device;
};
struct IsGpuPlace : public boost::static_visitor<bool> {
bool operator()(const CpuPlace &) const { return false; }
bool operator()(const GpuPlace &gpu) const { return true; }
struct IsGPUPlace : public boost::static_visitor<bool> {
bool operator()(const CPUPlace &) const { return false; }
bool operator()(const GPUPlace &gpu) const { return true; }
};
typedef boost::variant<GpuPlace, CpuPlace> Place;
typedef boost::variant<GPUPlace, CPUPlace> Place;
void set_place(const Place &);
const Place &get_place();
const GpuPlace default_gpu();
const CpuPlace default_cpu();
const GPUPlace default_gpu();
const CPUPlace default_cpu();
bool is_gpu_place(const Place &);
bool is_cpu_place(const Place &);
......
......@@ -3,8 +3,8 @@
#include "gtest/gtest.h"
TEST(Place, Equality) {
paddle::platform::CpuPlace cpu;
paddle::platform::GpuPlace g0(0), g1(1), gg0(0);
paddle::platform::CPUPlace cpu;
paddle::platform::GPUPlace g0(0), g1(1), gg0(0);
EXPECT_EQ(cpu, cpu);
EXPECT_EQ(g0, g0);
......@@ -22,19 +22,19 @@ TEST(Place, Default) {
EXPECT_TRUE(paddle::platform::is_gpu_place(paddle::platform::default_gpu()));
EXPECT_TRUE(paddle::platform::is_cpu_place(paddle::platform::default_cpu()));
paddle::platform::set_place(paddle::platform::CpuPlace());
paddle::platform::set_place(paddle::platform::CPUPlace());
EXPECT_TRUE(paddle::platform::is_cpu_place(paddle::platform::get_place()));
}
TEST(Place, Print) {
{
std::stringstream ss;
ss << paddle::platform::GpuPlace(1);
EXPECT_EQ("GpuPlace(1)", ss.str());
ss << paddle::platform::GPUPlace(1);
EXPECT_EQ("GPUPlace(1)", ss.str());
}
{
std::stringstream ss;
ss << paddle::platform::CpuPlace();
EXPECT_EQ("CpuPlace", ss.str());
ss << paddle::platform::CPUPlace();
EXPECT_EQ("CPUPlace", ss.str());
}
}
......@@ -17,7 +17,7 @@ add_library(paddle_network STATIC
add_style_check_target(paddle_network ${NETWORK_SOURCES})
add_style_check_target(paddle_network ${NETWORK_HEADERS})
add_dependencies(paddle_network gen_proto_cpp)
add_dependencies(paddle_network paddle_proto ${external_project_dependencies})
################### paddle_pserver ######################
set(PSERVER_SOURCES
......@@ -40,7 +40,7 @@ add_library(paddle_pserver STATIC
add_style_check_target(paddle_pserver ${PSERVER_SOURCES})
add_style_check_target(paddle_pserver ${PSERVER_HEADERS})
add_dependencies(paddle_pserver gen_proto_cpp)
add_dependencies(paddle_pserver paddle_proto ${external_project_dependencies})
set(PSERVER_MAIN_SOURCES
ParameterServer2Main.cpp)
......
......@@ -109,6 +109,10 @@ class DenseScanner(IScanner):
if len(self.__shape__) > 3:
raise ValueError(
"The dimension of input cannot be greater than 3.")
if len(self.__shape__) == 0:
raise ValueError(
"The input should be a vector, please check your input data."
)
self.__dim__ = reduce(lambda x, y: x * y, self.__shape__)
if len(self.__shape__) == 1 and self.__dim__ != self.input_type.dim:
raise ValueError(
......@@ -140,7 +144,7 @@ class DenseScanner(IScanner):
if len(self.__shape__) > 1:
# The last-two dimenstions are the frame height and width.
# For example, the layout is CHW for 3-D feature of image.
# The H and W are the fram height and width.
# The H and W are the frame height and width.
h, w = self.__shape__[-2:]
argument.setSlotFrameHeight(self.pos, h)
argument.setSlotFrameWidth(self.pos, w)
......
......@@ -31,6 +31,7 @@ Configuring cmake in /paddle/build ...
-DWITH_DOC=OFF
-DWITH_GPU=${WITH_GPU:-OFF}
-DWITH_AVX=${WITH_AVX:-OFF}
-DWITH_GOLANG=${WITH_GOLANG:-OFF}
-DWITH_SWIG_PY=ON
-DCUDNN_ROOT=/usr/
-DWITH_STYLE_CHECK=${WITH_STYLE_CHECK:-OFF}
......@@ -43,6 +44,7 @@ cmake .. \
-DWITH_DOC=OFF \
-DWITH_GPU=${WITH_GPU:-OFF} \
-DWITH_AVX=${WITH_AVX:-OFF} \
-DWITH_GOLANG=${WITH_GOLANG:-OFF} \
-DWITH_SWIG_PY=ON \
-DCUDNN_ROOT=/usr/ \
-DWITH_STYLE_CHECK=${WITH_STYLE_CHECK:-OFF} \
......
#!/bin/bash
source ./common.sh
NPROC=1
export PYTHONPATH=/opt/python/2.7.12/lib/python2.7/site-packages
export PYTHONHOME=/opt/python/2.7.12
export PATH=/opt/python/2.7.12/bin:${PATH}
cmake .. -DCMAKE_Fortran_COMPILER=/usr/bin/gfortran-4.8 -DON_TRAVIS=ON -DWITH_COVERAGE=ON -DCOVERALLS_UPLOAD=ON ${EXTRA_CMAKE_OPTS}
NRPOC=`nproc`
make -j $NPROC
make coveralls
sudo make install
#!/bin/bash
set -e
# Create the build directory for CMake.
mkdir -p $TRAVIS_BUILD_DIR/build
cd $TRAVIS_BUILD_DIR/build
# Add set -e, cd to directory.
source ./common.sh
# Compile Documentation only.
cmake .. -DCMAKE_BUILD_TYPE=Debug -DCMAKE_Fortran_COMPILER=/usr/bin/gfortran-4.8 -DWITH_GPU=OFF -DWITH_DOC=OFF -DWITH_STYLE_CHECK=OFF ${EXTRA_CMAKE_OPTS}
cmake .. -DCMAKE_BUILD_TYPE=Debug -DWITH_GPU=OFF -DWITH_DOC=OFF -DWITH_STYLE_CHECK=OFF
mkdir output
make -j `nproc`
find .. -name '*whl' | xargs pip install # install all wheels.
rm -rf *
cmake .. -DCMAKE_BUILD_TYPE=Debug -DCMAKE_Fortran_COMPILER=/usr/bin/gfortran-4.8 -DWITH_GPU=OFF -DWITH_DOC=ON ${EXTRA_CMAKE_OPTS}
make paddle_docs paddle_docs_cn
cmake .. -DCMAKE_BUILD_TYPE=Debug -DWITH_GPU=OFF -DWITH_DOC=ON
make -j `nproc` paddle_docs paddle_docs_cn
# check websites for broken links
linkchecker doc/en/html/index.html
......
#!/bin/bash
function abort(){
echo "Your commit not fit PaddlePaddle code style" 1>&2
echo "Please use pre-commit scripts to auto-format your code" 1>&2
echo "Your change doesn't follow PaddlePaddle's code style." 1>&2
echo "Please use pre-commit to reformat your code and git push again." 1>&2
exit 1
}
trap 'abort' 0
set -e
source common.sh
cd ..
cd $TRAVIS_BUILD_DIR
export PATH=/usr/bin:$PATH
pre-commit install
clang-format --version
......
#!/bin/bash
set -e
mkdir -p ../../../build
cd ../../../build
mkdir -p $HOME/third_party
EXTRA_CMAKE_OPTS="-DTHIRD_PARTY_PATH=${HOME}/third_party"
#!/bin/bash
cd `dirname $0`
if [ ${JOB} == "BUILD_AND_TEST" ]; then
./build_and_test.sh
elif [ ${JOB} == "DOCS" ]; then
./docs.sh
elif [ ${JOB} == "PRE_COMMIT" ]; then
./precommit.sh
else
echo Unknown job ${JOB}
exit 1
fi
cc_library(stringpiece SRCS piece.cc)
cc_test(stringpiece_test SRCS piece_test.cc DEPS stringpiece glog gflags)
cc_test(stringprintf_test SRCS printf_test.cc DEPS glog gflags)
......@@ -14,7 +14,7 @@
limitations under the License.
*/
#include "paddle/strings/stringpiece.h"
#include "paddle/string/piece.h"
#include <string.h>
......@@ -23,29 +23,25 @@
#include <stdexcept>
namespace paddle {
namespace string {
StringPiece::StringPiece() : data_(NULL), size_(0) {}
Piece::Piece() : data_(NULL), size_(0) {}
StringPiece::StringPiece(const char* d, size_t n) : data_(d), size_(n) {
Piece::Piece(const char* d, size_t n) : data_(d), size_(n) {
if (d == NULL && n != 0)
throw std::invalid_argument(
"StringPiece requires len to be 0 for NULL data");
throw std::invalid_argument("Piece requires len to be 0 for NULL data");
}
StringPiece::StringPiece(const char* s) : data_(s) {
size_ = (s == NULL) ? 0 : strlen(s);
}
Piece::Piece(const char* s) : data_(s) { size_ = (s == NULL) ? 0 : strlen(s); }
StringPiece::StringPiece(const std::string& s)
: data_(s.data()), size_(s.size()) {}
Piece::Piece(const std::string& s) : data_(s.data()), size_(s.size()) {}
char StringPiece::operator[](size_t n) const {
if (n >= len())
throw std::invalid_argument("index out of StringPiece length");
char Piece::operator[](size_t n) const {
if (n >= len()) throw std::invalid_argument("index out of Piece length");
return data_[n];
}
int Compare(StringPiece a, StringPiece b) {
int Compare(Piece a, Piece b) {
const size_t min_len = (a.len() < b.len()) ? a.len() : b.len();
int r = memcmp(a.data(), b.data(), min_len);
if (r == 0) {
......@@ -57,85 +53,86 @@ int Compare(StringPiece a, StringPiece b) {
return r;
}
bool operator==(StringPiece x, StringPiece y) {
bool operator==(Piece x, Piece y) {
return ((x.len() == y.len()) &&
(x.data() == y.data() || memcmp(x.data(), y.data(), x.len()) == 0));
}
bool operator!=(StringPiece x, StringPiece y) { return !(x == y); }
bool operator!=(Piece x, Piece y) { return !(x == y); }
bool operator<(StringPiece x, StringPiece y) { return Compare(x, y) < 0; }
bool operator>(StringPiece x, StringPiece y) { return Compare(x, y) > 0; }
bool operator<(Piece x, Piece y) { return Compare(x, y) < 0; }
bool operator>(Piece x, Piece y) { return Compare(x, y) > 0; }
bool operator<=(StringPiece x, StringPiece y) { return Compare(x, y) <= 0; }
bool operator>=(StringPiece x, StringPiece y) { return Compare(x, y) >= 0; }
bool operator<=(Piece x, Piece y) { return Compare(x, y) <= 0; }
bool operator>=(Piece x, Piece y) { return Compare(x, y) >= 0; }
bool HasPrefix(StringPiece s, StringPiece x) {
bool HasPrefix(Piece s, Piece x) {
return ((s.len() >= x.len()) && (memcmp(s.data(), x.data(), x.len()) == 0));
}
bool HasSuffix(StringPiece s, StringPiece x) {
bool HasSuffix(Piece s, Piece x) {
return ((s.len() >= x.len()) &&
(memcmp(s.data() + (s.len() - x.len()), x.data(), x.len()) == 0));
}
StringPiece SkipPrefix(StringPiece s, size_t n) {
Piece SkipPrefix(Piece s, size_t n) {
if (n > s.len())
throw std::invalid_argument("Skip distance larger than StringPiece length");
return StringPiece(s.data() + n, s.len() - n);
throw std::invalid_argument("Skip distance larger than Piece length");
return Piece(s.data() + n, s.len() - n);
}
StringPiece SkipSuffix(StringPiece s, size_t n) {
Piece SkipSuffix(Piece s, size_t n) {
if (n > s.len())
throw std::invalid_argument("Skip distance larger than StringPiece length");
return StringPiece(s.data(), s.len() - n);
throw std::invalid_argument("Skip distance larger than Piece length");
return Piece(s.data(), s.len() - n);
}
StringPiece TrimPrefix(StringPiece s, StringPiece x) {
Piece TrimPrefix(Piece s, Piece x) {
return HasPrefix(s, x) ? SkipPrefix(s, x.len()) : s;
}
StringPiece TrimSuffix(StringPiece s, StringPiece x) {
Piece TrimSuffix(Piece s, Piece x) {
return HasSuffix(s, x) ? SkipSuffix(s, x.len()) : s;
}
bool Contains(StringPiece s, StringPiece sub) {
bool Contains(Piece s, Piece sub) {
return std::search(s.begin(), s.end(), sub.begin(), sub.end()) != s.end();
}
size_t Index(StringPiece s, StringPiece sub) {
size_t Index(Piece s, Piece sub) {
auto e = std::search(s.begin(), s.end(), sub.begin(), sub.end());
return e != s.end() ? e - s.data() : StringPiece::npos;
return e != s.end() ? e - s.data() : Piece::npos;
}
size_t Find(StringPiece s, char c, size_t pos) {
size_t Find(Piece s, char c, size_t pos) {
if (pos >= s.len()) {
return StringPiece::npos;
return Piece::npos;
}
const char* result =
reinterpret_cast<const char*>(memchr(s.data() + pos, c, s.len() - pos));
return result != nullptr ? result - s.data() : StringPiece::npos;
return result != nullptr ? result - s.data() : Piece::npos;
}
size_t RFind(StringPiece s, char c, size_t pos) {
if (s.len() == 0) return StringPiece::npos;
size_t RFind(Piece s, char c, size_t pos) {
if (s.len() == 0) return Piece::npos;
for (const char* p = s.data() + std::min(pos, s.len() - 1); p >= s.data();
p--) {
if (*p == c) {
return p - s.data();
}
}
return StringPiece::npos;
return Piece::npos;
}
StringPiece SubStr(StringPiece s, size_t pos, size_t n) {
Piece SubStr(Piece s, size_t pos, size_t n) {
if (pos > s.len()) pos = s.len();
if (n > s.len() - pos) n = s.len() - pos;
return StringPiece(s.data() + pos, n);
return Piece(s.data() + pos, n);
}
std::ostream& operator<<(std::ostream& o, StringPiece piece) {
std::ostream& operator<<(std::ostream& o, Piece piece) {
return o << piece.ToString();
}
} // namespace string
} // namespace paddle
......@@ -20,33 +20,34 @@
#include <string>
namespace paddle {
namespace string {
// StringPiece points into a std::string object but doesn't own the
// Piece points into a std::string object but doesn't own the
// string. It is for efficient access to strings. Like Go's string
// type. Not that StringPiece doesn't mutate the underlying string,
// type. Not that Piece doesn't mutate the underlying string,
// so it is thread-safe given that the underlying string doesn't
// change. Because StringPiece contains a little data members, and
// change. Because Piece contains a little data members, and
// its syntax is simple as it doesn't own/manage the string, it is
// cheap to construct StringPieces and pass them around.
class StringPiece {
// cheap to construct Pieces and pass them around.
class Piece {
public:
static const size_t npos = static_cast<size_t>(-1);
// We provide non-explicit singleton constructors so users can
// pass in a "const char*" or a "string" wherever a "StringPiece"
// pass in a "const char*" or a "string" wherever a "Piece"
// is expected. These contructors ensure that if data_ is NULL,
// size_ is 0.
StringPiece();
StringPiece(const char* d, size_t n);
StringPiece(const char* d);
StringPiece(const std::string& s);
Piece();
Piece(const char* d, size_t n);
Piece(const char* d);
Piece(const std::string& s);
const char* data() const { return data_; }
size_t len() const { return size_; }
char operator[](size_t n) const;
// StringPiece doesn't own the string, so both iterator and const
// Piece doesn't own the string, so both iterator and const
// iterator are const char* indeed.
typedef const char* const_iterator;
typedef const char* iterator;
......@@ -63,43 +64,44 @@ private:
// Intentionally copyable
};
int Compare(StringPiece a, StringPiece b);
int Compare(Piece a, Piece b);
bool operator==(StringPiece x, StringPiece y);
bool operator!=(StringPiece x, StringPiece y);
bool operator<(StringPiece x, StringPiece y);
bool operator>(StringPiece x, StringPiece y);
bool operator<=(StringPiece x, StringPiece y);
bool operator>=(StringPiece x, StringPiece y);
bool operator==(Piece x, Piece y);
bool operator!=(Piece x, Piece y);
bool operator<(Piece x, Piece y);
bool operator>(Piece x, Piece y);
bool operator<=(Piece x, Piece y);
bool operator>=(Piece x, Piece y);
bool HasPrefix(StringPiece s, StringPiece prefix);
bool HasSuffix(StringPiece s, StringPiece suffix);
bool HasPrefix(Piece s, Piece prefix);
bool HasSuffix(Piece s, Piece suffix);
StringPiece SkipPrefix(StringPiece s, size_t n);
StringPiece SkipSuffix(StringPiece s, size_t n);
Piece SkipPrefix(Piece s, size_t n);
Piece SkipSuffix(Piece s, size_t n);
// Skip the prefix (or suffix) if it matches with the string.
StringPiece TrimPrefix(StringPiece s, StringPiece prefix);
StringPiece TrimSuffix(StringPiece s, StringPiece suffix);
Piece TrimPrefix(Piece s, Piece prefix);
Piece TrimSuffix(Piece s, Piece suffix);
// Returns if s contains sub. Any s except for empty s contains an
// empty sub.
bool Contains(StringPiece s, StringPiece sub);
bool Contains(Piece s, Piece sub);
// Return the first occurrence of sub in s, or npos. If both s and
// sub is empty, it returns npos; otherwise, if only sub is empty, it
// returns 0.
size_t Index(StringPiece s, StringPiece sub);
size_t Index(Piece s, Piece sub);
// Return the first occurrence of c in s[pos:end], or npos.
size_t Find(StringPiece s, char c, size_t pos);
size_t Find(Piece s, char c, size_t pos);
// Search range is [0..pos] inclusive. If pos == npos, search everything.
size_t RFind(StringPiece s, char c, size_t pos);
size_t RFind(Piece s, char c, size_t pos);
StringPiece SubStr(StringPiece s, size_t pos, size_t n);
Piece SubStr(Piece s, size_t pos, size_t n);
// allow StringPiece to be logged
std::ostream& operator<<(std::ostream& o, StringPiece piece);
// allow Piece to be logged
std::ostream& operator<<(std::ostream& o, Piece piece);
} // namespace string
} // namespace paddle
......@@ -14,7 +14,7 @@
limitations under the License.
*/
#include "paddle/strings/stringpiece.h"
#include "paddle/string/piece.h"
#include <sstream>
......@@ -22,42 +22,44 @@
TEST(StringPiece, Construct) {
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ(NULL, s.data());
EXPECT_EQ(0U, s.len());
}
{ EXPECT_THROW(paddle::StringPiece s(NULL, 10000U), std::invalid_argument); }
{
paddle::StringPiece s(NULL);
EXPECT_THROW(paddle::string::Piece s(NULL, 10000U), std::invalid_argument);
}
{
paddle::string::Piece s(NULL);
EXPECT_EQ(0U, s.len());
}
{
std::string a;
EXPECT_EQ(0U, a.size());
paddle::StringPiece s(a);
paddle::string::Piece s(a);
EXPECT_EQ(0U, s.len());
}
}
TEST(StringPiece, CopyAndAssign) {
paddle::StringPiece empty;
paddle::string::Piece empty;
EXPECT_EQ(0U, empty.len());
paddle::StringPiece a("hello");
paddle::StringPiece b = a;
paddle::string::Piece a("hello");
paddle::string::Piece b = a;
EXPECT_EQ(b.len(), strlen("hello"));
EXPECT_EQ(a, b);
std::string storage("hello");
paddle::StringPiece c(storage);
paddle::string::Piece c(storage);
EXPECT_EQ(a, c);
EXPECT_NE(a.data(), c.data());
}
TEST(StringPiece, Compare) {
{
paddle::StringPiece a("hello");
paddle::StringPiece b("world");
paddle::string::Piece a("hello");
paddle::string::Piece b("world");
EXPECT_TRUE(a != b);
EXPECT_FALSE(a == b);
EXPECT_TRUE(a < b);
......@@ -68,7 +70,7 @@ TEST(StringPiece, Compare) {
EXPECT_GT(Compare(b, a), 0);
}
{
paddle::StringPiece a, b;
paddle::string::Piece a, b;
EXPECT_TRUE(a == b);
EXPECT_FALSE(a != b);
EXPECT_FALSE(a < b);
......@@ -82,31 +84,31 @@ TEST(StringPiece, Compare) {
TEST(StringPiece, ToString) {
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ(std::string(""), s.ToString());
}
{
paddle::StringPiece s(NULL);
paddle::string::Piece s(NULL);
EXPECT_EQ(std::string(""), s.ToString());
}
{
paddle::StringPiece s("hello");
paddle::string::Piece s("hello");
EXPECT_EQ(std::string("hello"), s.ToString());
}
}
TEST(StringPiece, HasPrefixSuffix) {
using paddle::HasPrefix;
using paddle::HasSuffix;
using paddle::string::HasPrefix;
using paddle::string::HasSuffix;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_FALSE(HasPrefix(s, "something"));
EXPECT_TRUE(HasPrefix(s, ""));
EXPECT_FALSE(HasSuffix(s, "something"));
EXPECT_TRUE(HasSuffix(s, ""));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_TRUE(HasPrefix(s, ""));
EXPECT_TRUE(HasPrefix(s, "a"));
EXPECT_TRUE(HasPrefix(s, "ap"));
......@@ -120,10 +122,10 @@ TEST(StringPiece, HasPrefixSuffix) {
}
TEST(StringPiece, SkipPrefixSuffix) {
using paddle::SkipPrefix;
using paddle::SkipSuffix;
using paddle::string::SkipPrefix;
using paddle::string::SkipSuffix;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ("", SkipPrefix(s, 0));
EXPECT_THROW(SkipPrefix(s, 1), std::invalid_argument);
......@@ -131,7 +133,7 @@ TEST(StringPiece, SkipPrefixSuffix) {
EXPECT_THROW(SkipSuffix(s, 1), std::invalid_argument);
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_EQ("app", SkipPrefix(s, 0));
EXPECT_EQ("pp", SkipPrefix(s, 1));
EXPECT_EQ("p", SkipPrefix(s, 2));
......@@ -147,10 +149,10 @@ TEST(StringPiece, SkipPrefixSuffix) {
}
TEST(StringPiece, TrimPrefixSuffix) {
using paddle::TrimPrefix;
using paddle::TrimSuffix;
using paddle::string::TrimPrefix;
using paddle::string::TrimSuffix;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ("", TrimPrefix(s, ""));
EXPECT_EQ("", TrimPrefix(s, "something"));
......@@ -158,7 +160,7 @@ TEST(StringPiece, TrimPrefixSuffix) {
EXPECT_EQ("", TrimSuffix(s, "something"));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_EQ("app", TrimPrefix(s, ""));
EXPECT_EQ("pp", TrimPrefix(s, "a"));
EXPECT_EQ("p", TrimPrefix(s, "ap"));
......@@ -174,14 +176,14 @@ TEST(StringPiece, TrimPrefixSuffix) {
}
TEST(StringPiece, Contains) {
using paddle::Contains;
using paddle::string::Contains;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_FALSE(Contains(s, ""));
EXPECT_FALSE(Contains(s, "something"));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_TRUE(Contains(s, ""));
EXPECT_TRUE(Contains(s, "a"));
EXPECT_TRUE(Contains(s, "p"));
......@@ -193,15 +195,15 @@ TEST(StringPiece, Contains) {
}
TEST(StringPiece, Index) {
using paddle::Index;
auto npos = paddle::StringPiece::npos;
using paddle::string::Index;
auto npos = paddle::string::Piece::npos;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ(npos, Index(s, ""));
EXPECT_EQ(npos, Index(s, "something"));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_EQ(0U, Index(s, ""));
EXPECT_EQ(0U, Index(s, "a"));
EXPECT_EQ(1U, Index(s, "p"));
......@@ -213,14 +215,14 @@ TEST(StringPiece, Index) {
}
TEST(StringPiece, Find) {
using paddle::Find;
auto npos = paddle::StringPiece::npos;
using paddle::string::Find;
auto npos = paddle::string::Piece::npos;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ(npos, Find(s, 'a', 0U));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_EQ(0U, Find(s, 'a', 0U));
EXPECT_EQ(1U, Find(s, 'p', 0U));
EXPECT_EQ(1U, Find(s, 'p', 1U));
......@@ -230,14 +232,14 @@ TEST(StringPiece, Find) {
}
TEST(StringPiece, RFind) {
using paddle::RFind;
auto npos = paddle::StringPiece::npos;
using paddle::string::RFind;
auto npos = paddle::string::Piece::npos;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ(npos, RFind(s, 'a', 0U));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_EQ(2U, RFind(s, 'p', 2U));
EXPECT_EQ(0U, RFind(s, 'a', 2U));
EXPECT_EQ(1U, RFind(s, 'p', 1U));
......@@ -247,15 +249,15 @@ TEST(StringPiece, RFind) {
}
TEST(StringPiece, SubStr) {
using paddle::SubStr;
using paddle::string::SubStr;
{
paddle::StringPiece s;
paddle::string::Piece s;
EXPECT_EQ("", SubStr(s, 0, 0));
EXPECT_EQ("", SubStr(s, 0, 1));
EXPECT_EQ("", SubStr(s, 1, 0));
}
{
paddle::StringPiece s("app");
paddle::string::Piece s("app");
EXPECT_EQ("", SubStr(s, 0, 0));
EXPECT_EQ("", SubStr(s, 1, 0));
EXPECT_EQ("", SubStr(s, 2, 0));
......@@ -279,15 +281,15 @@ TEST(StringPiece, SubStr) {
}
TEST(StringPiece, StreamOutput) {
using paddle::StringPiece;
using paddle::string::Piece;
std::stringstream o;
o << StringPiece();
o << paddle::string::Piece();
EXPECT_EQ("", o.str());
o << StringPiece("hello");
o << paddle::string::Piece("hello");
EXPECT_EQ("hello", o.str());
o << StringPiece();
o << paddle::string::Piece();
EXPECT_EQ("hello", o.str());
}
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