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PaddleDetection
提交 60a78893 编写于 作者: W wanghaoshuang
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Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into crop_layer

上级 3e7819c2 b90780c3
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内联 并排
Showing with 7166 addition and 1266 deletion
.gitignore
浏览文件 @ 60a78893
......@@ -19,3 +19,9 @@ third_party/
# clion workspace.
cmake-build-*
# generated while compiling
python/paddle/v2/framework/core.so
CMakeFiles
cmake_install.cmake
.pre-commit-config.yaml
浏览文件 @ 60a78893
......@@ -21,10 +21,10 @@
sha: 28c0ea8a67a3e2dbbf4822ef44e85b63a0080a29
hooks:
- id: clang-formater
- repo: https://github.com/dnephin/pre-commit-golang
sha: e4693a4c282b4fc878eda172a929f7a6508e7d16
- repo: https://github.com/PaddlePaddle/pre-commit-golang
sha: 16398aeccf263adaf53b2495eed0406347d76281
hooks:
- id: go-fmt
files: (.*\.go)
- id: go-lint
files: (.*\.go)
types: [go]
- id: gometalinter
types: [go]
.travis.yml
浏览文件 @ 60a78893
......@@ -4,6 +4,7 @@ cache:
- $HOME/.ccache
- $HOME/.cache/pip
- $TRAVIS_BUILD_DIR/build/third_party
- $TRAVIS_BUILD_DIR/build_android/third_party
sudo: required
dist: trusty
os:
......@@ -11,6 +12,7 @@ os:
env:
- JOB=build_doc
- JOB=check_style
- JOB=build_android
addons:
apt:
packages:
......@@ -39,6 +41,8 @@ before_install:
- pip install rarfile
- curl https://glide.sh/get | bash
- eval "$(GIMME_GO_VERSION=1.8.3 gimme)"
- go get -u github.com/alecthomas/gometalinter
- gometalinter --install
- |
function timeout() { perl -e 'alarm shift; exec @ARGV' "$@"; }
script:
......
CMakeLists.txt
浏览文件 @ 60a78893
......@@ -28,7 +28,9 @@ if(NOT CMAKE_CROSSCOMPILING)
endif(NOT CMAKE_CROSSCOMPILING)
find_package(Git REQUIRED)
find_package(Threads REQUIRED)
find_package(Boost QUIET)
if(NOT ANDROID)
find_package(Boost QUIET)
endif()
include(simd)
......@@ -97,6 +99,7 @@ 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(external/pybind11) # download pybind11
include(cudnn) # set cudnn libraries, must before configure
include(configure) # add paddle env configuration
......@@ -134,11 +137,16 @@ if(WITH_GPU)
endif(WITH_GPU)
if(USE_NNPACK)
list(APPEND EXTERNAL_LIBS ${NNPACK_LIB} ${PTHREADPOOL_LIB} "rt")
include(external/nnpack)
list(APPEND EXTERNAL_LIBS ${NNPACK_LIBS})
endif(USE_NNPACK)
add_subdirectory(proto)
# "add_subdirectory(go)" should be placed after the following loine,
# because it depends on paddle/optimizer.
add_subdirectory(paddle/optimizer)
# "add_subdirectory(paddle)" and "add_subdirectory(python)" should be
# placed after this block, because they depends on it.
if(WITH_GOLANG)
......@@ -146,7 +154,9 @@ if(WITH_GOLANG)
endif(WITH_GOLANG)
add_subdirectory(paddle)
add_subdirectory(python)
if(WITH_PYTHON)
add_subdirectory(python)
endif()
if(WITH_DOC)
add_subdirectory(doc)
endif()
Dockerfile
浏览文件 @ 60a78893
......@@ -25,7 +25,7 @@ COPY ./paddle/scripts/docker/root/ /root/
RUN apt-get update && \
apt-get install -y \
git python-pip python-dev openssh-server bison \
wget unzip tar xz-utils bzip2 gzip coreutils ntp \
wget unzip unrar tar xz-utils bzip2 gzip coreutils ntp \
curl sed grep graphviz libjpeg-dev zlib1g-dev \
python-numpy python-matplotlib gcc g++ \
automake locales clang-format-3.8 swig doxygen cmake \
......
Dockerfile.android
浏览文件 @ 60a78893
......@@ -14,6 +14,17 @@ RUN apt-get update && \
wget curl tar unzip gcc g++ locales clang-format-3.8 swig cmake && \
apt-get clean -y
# Install Go and glide
RUN wget -O go.tgz https://storage.googleapis.com/golang/go1.8.1.linux-amd64.tar.gz && \
tar -C /usr/local -xzf go.tgz && \
mkdir /root/gopath && \
mkdir /root/gopath/bin && \
mkdir /root/gopath/src && \
rm go.tgz
ENV GOROOT=/usr/local/go GOPATH=/root/gopath
# should not be in the same line with GOROOT definition, otherwise docker build could not find GOROOT.
ENV PATH=${PATH}:${GOROOT}/bin:${GOPATH}/bin
# git credential to skip password typing
RUN git config --global credential.helper store
......
README.md
浏览文件 @ 60a78893
......@@ -2,8 +2,8 @@
[![Build Status](https://travis-ci.org/PaddlePaddle/Paddle.svg?branch=develop)](https://travis-ci.org/PaddlePaddle/Paddle)
[![Documentation Status](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](http://www.paddlepaddle.org/develop/doc/)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](http://www.paddlepaddle.org/doc_cn/)
[![Documentation Status](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](http://doc.paddlepaddle.org/develop/doc/)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](http://doc.paddlepaddle.org/develop/doc_cn/)
[![Coverage Status](https://coveralls.io/repos/github/PaddlePaddle/Paddle/badge.svg?branch=develop)](https://coveralls.io/github/PaddlePaddle/Paddle?branch=develop)
[![Release](https://img.shields.io/github/release/PaddlePaddle/Paddle.svg)](https://github.com/PaddlePaddle/Paddle/releases)
[![License](https://img.shields.io/badge/license-Apache%202-blue.svg)](LICENSE)
......@@ -61,35 +61,36 @@ Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddl
## Installation
It is recommended to check out the
[Docker installation guide](http://www.paddlepaddle.org/develop/doc/getstarted/build_and_install/docker_install_en.html)
[Docker installation guide](http://doc.paddlepaddle.org/develop/doc/getstarted/build_and_install/docker_install_en.html)
before looking into the
[build from source guide](http://www.paddlepaddle.org/develop/doc/getstarted/build_and_install/build_from_source_en.html)
[build from source guide](http://doc.paddlepaddle.org/develop/doc/getstarted/build_and_install/build_from_source_en.html)
## Documentation
We provide [English](http://www.paddlepaddle.org/develop/doc/) and
[Chinese](http://www.paddlepaddle.org/doc_cn/) documentation.
We provide [English](http://doc.paddlepaddle.org/develop/doc/) and
[Chinese](http://doc.paddlepaddle.org/doc_cn/) documentation.
- [Deep Learning 101](http://book.paddlepaddle.org/index.html)
You might want to start from the this online interactive book that can run in Jupyter Notebook.
- [Distributed Training](http://www.paddlepaddle.org/develop/doc/howto/usage/cluster/cluster_train_en.html)
- [Distributed Training](http://doc.paddlepaddle.org/develop/doc/howto/usage/cluster/cluster_train_en.html)
You can run distributed training jobs on MPI clusters.
- [Distributed Training on Kubernetes](http://www.paddlepaddle.org/develop/doc/howto/usage/k8s/k8s_en.html)
- [Distributed Training on Kubernetes](http://doc.paddlepaddle.org/develop/doc/howto/usage/k8s/k8s_en.html)
You can also run distributed training jobs on Kubernetes clusters.
- [Python API](http://www.paddlepaddle.org/develop/doc/api/index_en.html)
- [Python API](http://doc.paddlepaddle.org/develop/doc/api/index_en.html)
Our new API enables much shorter programs.
- [How to Contribute](http://www.paddlepaddle.org/develop/doc/howto/dev/contribute_to_paddle_en.html)
- [How to Contribute](http://doc.paddlepaddle.org/develop/doc/howto/dev/contribute_to_paddle_en.html)
We appreciate your contributions!
## Ask Questions
You are welcome to submit questions and bug reports as [Github Issues](https://github.com/PaddlePaddle/Paddle/issues).
......
cmake/configure.cmake
浏览文件 @ 60a78893
......@@ -102,12 +102,19 @@ if(WITH_GOLANG)
message(FATAL_ERROR "no glide executeble found: $ENV{GOPATH}/bin/glide")
endif()
add_custom_target(go_vendor)
add_custom_command(TARGET go_vendor
# this command will only run when the file it depends is missing
# or has changed, or the output is missing.
add_custom_command(OUTPUT ${CMAKE_BINARY_DIR}/glide
COMMAND env GOPATH=${GOPATH} ${GLIDE} install
COMMAND touch ${CMAKE_BINARY_DIR}/glide
DEPENDS ${PROJ_ROOT}/go/glide.lock
WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go"
)
add_dependencies(go_vendor go_path)
)
# depends on the custom command which outputs
# ${CMAKE_BINARY_DIR}/glide, the custom command does not need to
# run every time this target is built.
add_custom_target(go_vendor DEPENDS ${CMAKE_BINARY_DIR}/glide go_path)
endif()
endif(WITH_GOLANG)
cmake/cpplint.cmake
浏览文件 @ 60a78893
......@@ -27,7 +27,8 @@ set(IGNORE_PATTERN
.*cblas\\.h.*
.*\\.pb\\.txt
.*LtrDataProvider.*
.*MultiDataProvider.*)
.*MultiDataProvider.*
.*pb.*)
# add_style_check_target
#
......@@ -52,14 +53,13 @@ macro(add_style_check_target TARGET_NAME)
endif()
endforeach()
if(LINT MATCHES ON)
# cpplint code style
get_filename_component(base_filename ${filename} NAME)
set(CUR_GEN ${CMAKE_CURRENT_BINARY_DIR}/${base_filename}.cpplint)
add_custom_command(OUTPUT ${CUR_GEN}
PRE_BUILD
COMMAND env ${py_env} "${PYTHON_EXECUTABLE}" "${PROJ_ROOT}/paddle/scripts/cpplint.py"
"--filter=${STYLE_FILTER}"
"--write-success=${CUR_GEN}" ${filename}
DEPENDS ${filename}
add_custom_command(TARGET ${TARGET_NAME} PRE_BUILD
COMMAND "${PYTHON_EXECUTABLE}" "${PROJ_ROOT}/paddle/scripts/cpplint.py"
"--filter=${STYLE_FILTER}"
"--write-success=${CUR_GEN}" ${filename}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
endif()
endforeach()
......
cmake/cross_compiling/android.cmake
浏览文件 @ 60a78893
......@@ -106,6 +106,10 @@ IF("${CMAKE_VERSION}" VERSION_LESS "3.7.0")
SET(CMAKE_SYSTEM_PROCESSOR armv7-a)
ENDIF()
ENDIF()
IF(ANDROID_ABI STREQUAL "arm64-v8a")
SET(ANDROID_TOOLCHAIN_NAME aarch64-linux-android)
SET(CMAKE_SYSTEM_PROCESSOR aarch64)
ENDIF()
SET(ANDROID_TOOLCHAIN_PREFIX "${ANDROID_TOOLCHAIN_ROOT}/bin/${ANDROID_TOOLCHAIN_NAME}-")
ENDIF()
......@@ -162,6 +166,10 @@ IF("${CMAKE_VERSION}" VERSION_LESS "3.7.0")
ENDIF()
ENDIF()
IF(ANDROID_ABI STREQUAL "arm64-v8a")
LIST(APPEND ANDROID_COMPILER_FLAGS -march=armv8-a)
ENDIF()
STRING(REPLACE ";" " " ANDROID_COMPILER_FLAGS "${ANDROID_COMPILER_FLAGS}")
STRING(REPLACE ";" " " ANDROID_LINKER_FLAGS "${ANDROID_LINKER_FLAGS}")
......@@ -186,6 +194,10 @@ ELSE()
SET(CMAKE_ANDROID_STANDALONE_TOOLCHAIN ${ANDROID_STANDALONE_TOOLCHAIN})
ENDIF()
SET(CMAKE_ANDROID_ARCH_ABI ${ANDROID_ABI})
SET(CMAKE_ANDROID_ARM_MODE ${ANDROID_ARM_MODE})
SET(CMAKE_ANDROID_ARM_NEON ${ANDROID_ARM_NEON})
IF(ANDROID_ABI MATCHES "^armeabi(-v7a)?$")
SET(CMAKE_ANDROID_ARM_MODE ${ANDROID_ARM_MODE})
IF(ANDROID_ABI STREQUAL "armeabi-v7a")
SET(CMAKE_ANDROID_ARM_NEON ${ANDROID_ARM_NEON})
ENDIF()
ENDIF()
ENDIF()
cmake/external/glog.cmake
浏览文件 @ 60a78893
......@@ -52,6 +52,7 @@ ExternalProject_Add(
ADD_LIBRARY(glog STATIC IMPORTED GLOBAL)
SET_PROPERTY(TARGET glog PROPERTY IMPORTED_LOCATION ${GLOG_LIBRARIES})
ADD_DEPENDENCIES(glog extern_glog)
ADD_DEPENDENCIES(glog extern_glog gflags)
LINK_LIBRARIES(glog gflags)
LIST(APPEND external_project_dependencies glog)
paddle/function/nnpack/nnpack.cmake → cmake/external/nnpack.cmake
浏览文件 @ 60a78893
......@@ -7,10 +7,24 @@ set(NNPACK_ROOT $ENV{NNPACK_ROOT} CACHE PATH "Folder contains NNPACK")
find_path(NNPACK_INC_DIR nnpack.h PATHS ${NNPACK_ROOT}/include)
find_library(NNPACK_LIB NAMES nnpack PATHS ${NNPACK_ROOT}/lib)
find_library(PTHREADPOOL_LIB NAMES pthreadpool PATHS ${NNPACK_ROOT}/lib)
find_library(NNPACK_UKERNELS_LIB NAMES nnpack_ukernels PATHS ${NNPACK_ROOT}/lib)
find_library(NNPACK_CPUFEATURES_LIB NAMES cpufeatures PATHS ${NNPACK_ROOT}/lib)
if(NNPACK_INC_DIR AND NNPACK_LIB AND PTHREADPOOL_LIB)
set(NNPACK_FOUND ON)
INCLUDE_DIRECTORIES(${NNPACK_INC_DIR})
set(NNPACK_LIBS)
list(APPEND NNPACK_LIBS ${NNPACK_LIB} ${PTHREADPOOL_LIB})
if (NNPACK_UKERNELS_LIB)
list(APPEND NNPACK_LIBS ${NNPACK_UKERNELS_LIB})
endif()
if (NNPACK_CPUFEATURES_LIB)
list(APPEND NNPACK_LIBS ${NNPACK_CPUFEATURES_LIB})
endif()
if(NOT ANDROID)
list(APPEND NNPACK_LIBS "rt")
endif()
else()
message(FATAL_ERROR "Cannot find NNPACK in (${NNPACK_ROOT})")
endif()
cmake/external/openblas.cmake
浏览文件 @ 60a78893
......@@ -32,7 +32,12 @@ IF(NOT ${CBLAS_FOUND})
# arm_soft_fp_abi branch of OpenBLAS to support softfp
# https://github.com/xianyi/OpenBLAS/tree/arm_soft_fp_abi
SET(OPENBLAS_COMMIT "b5c96fcfcdc82945502a2303116a64d89985daf5")
SET(OPTIONAL_ARGS HOSTCC=${HOST_C_COMPILER} TARGET=ARMV7 ARM_SOFTFP_ABI=1 USE_THREAD=0)
IF(ANDROID_ABI MATCHES "^armeabi(-v7a)?$")
SET(TARGET "ARMV7")
ELSEIF(ANDROID_ABI STREQUAL "arm64-v8a")
SET(TARGET "ARMV8")
ENDIF()
SET(OPTIONAL_ARGS HOSTCC=${HOST_C_COMPILER} TARGET=${TARGET} ARM_SOFTFP_ABI=1 USE_THREAD=0)
ELSEIF(RPI)
# use hardfp
SET(OPENBLAS_COMMIT "v0.2.19")
......
cmake/external/pybind11.cmake 0 → 100644
浏览文件 @ 60a78893
INCLUDE(ExternalProject)
SET(PYBIND_SOURCE_DIR ${THIRD_PARTY_PATH}/pybind)
INCLUDE_DIRECTORIES(${PYBIND_SOURCE_DIR}/src/extern_pybind/include)
ExternalProject_Add(
extern_pybind
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/pybind/pybind11.git"
GIT_TAG "v2.1.1"
PREFIX ${PYBIND_SOURCE_DIR}
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
if (${CMAKE_VERSION} VERSION_LESS "3.3.0")
set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/pybind_dummy.c)
file(WRITE ${dummyfile} "const char * dummy_any = \"${dummyfile}\";")
add_library(pybind STATIC ${dummyfile})
else()
add_library(pybind INTERFACE)
endif()
add_dependencies(pybind extern_pybind)
LIST(APPEND external_project_dependencies pybind)
cmake/external/python.cmake
浏览文件 @ 60a78893
......@@ -18,6 +18,9 @@ INCLUDE(python_module)
FIND_PACKAGE(PythonInterp 2.7)
IF(WITH_PYTHON)
FIND_PACKAGE(PythonLibs 2.7)
# Fixme: Maybe find a static library. Get SHARED/STATIC by FIND_PACKAGE.
ADD_LIBRARY(python SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET python PROPERTY IMPORTED_LOCATION ${PYTHON_LIBRARIES})
ENDIF(WITH_PYTHON)
SET(py_env "")
......
cmake/flags.cmake
浏览文件 @ 60a78893
......@@ -109,7 +109,9 @@ set(COMMON_FLAGS
-Wno-unused-function
-Wno-error=literal-suffix
-Wno-error=sign-compare
-Wno-error=unused-local-typedefs)
-Wno-error=unused-local-typedefs
-Wno-error=parentheses-equality # Warnings in Pybind11
)
set(GPU_COMMON_FLAGS
-fPIC
......
cmake/generic.cmake
浏览文件 @ 60a78893
......@@ -90,10 +90,11 @@
# including binary directory for generated headers.
include_directories(${CMAKE_CURRENT_BINARY_DIR})
if(NOT APPLE)
if(NOT APPLE AND NOT ANDROID)
find_package(Threads REQUIRED)
link_libraries(${CMAKE_THREAD_LIBS_INIT})
endif(NOT APPLE)
set(CMAKE_CXX_LINK_EXECUTABLE "${CMAKE_CXX_LINK_EXECUTABLE} -ldl -lrt")
endif(NOT APPLE AND NOT ANDROID)
function(merge_static_libs TARGET_NAME)
set(libs ${ARGN})
......@@ -103,6 +104,7 @@ function(merge_static_libs TARGET_NAME)
foreach(lib ${libs})
list(APPEND libs_deps ${${lib}_LIB_DEPENDS})
endforeach()
list(REMOVE_DUPLICATES libs_deps)
if(APPLE) # Use OSX's libtool to merge archives
# To produce a library we need at least one source file.
......@@ -126,7 +128,7 @@ function(merge_static_libs TARGET_NAME)
# Get the file names of the libraries to be merged
set(libfiles ${libfiles} $<TARGET_FILE:${lib}>)
endforeach()
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND rm "${CMAKE_CURRENT_BINARY_DIR}/lib${TARGET_NAME}.a"
COMMAND /usr/bin/libtool -static -o "${CMAKE_CURRENT_BINARY_DIR}/lib${TARGET_NAME}.a" ${libfiles})
else() # general UNIX: use "ar" to extract objects and re-add to a common lib
......@@ -144,11 +146,11 @@ function(merge_static_libs TARGET_NAME)
DEPENDS ${lib} ${objdir}
WORKING_DIRECTORY ${objdir})
# Empty dummy source file that goes into merged library
set(mergebase ${lib}.mergebase.c)
add_custom_command(OUTPUT ${mergebase}
COMMAND ${CMAKE_COMMAND} -E touch ${mergebase}
DEPENDS ${objlistfile})
# Empty dummy source file that goes into merged library
set(mergebase ${lib}.mergebase.c)
add_custom_command(OUTPUT ${mergebase}
COMMAND ${CMAKE_COMMAND} -E touch ${mergebase}
DEPENDS ${objlistfile})
list(APPEND mergebases "${mergebase}")
endforeach()
......@@ -183,6 +185,10 @@ function(cc_library TARGET_NAME)
add_dependencies(${TARGET_NAME} ${cc_library_DEPS})
target_link_libraries(${TARGET_NAME} ${cc_library_DEPS})
endif()
# cpplint code style
add_style_check_target(${TARGET_NAME} ${cc_library_SRCS})
else(cc_library_SRCS)
if (cc_library_DEPS)
merge_static_libs(${TARGET_NAME} ${cc_library_DEPS})
......@@ -300,7 +306,7 @@ function(go_library TARGET_NAME)
file(GLOB GO_SOURCE RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.go")
string(REPLACE "${PADDLE_GO_PATH}/" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
# FIXME: link path
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND rm "${${TARGET_NAME}_LIB_PATH}"
# Golang build source code
......@@ -308,7 +314,7 @@ function(go_library TARGET_NAME)
-o "${${TARGET_NAME}_LIB_PATH}"
"./${CMAKE_CURRENT_SOURCE_REL_DIR}/${GO_SOURCE}"
# must run under GOPATH
WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
add_dependencies(${TARGET_NAME} go_vendor)
endfunction(go_library)
......@@ -319,14 +325,11 @@ function(go_binary TARGET_NAME)
cmake_parse_arguments(go_binary "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
string(REPLACE "${PADDLE_GO_PATH}/" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
# FIXME: link path
add_custom_command(OUTPUT ${TARGET_NAME}_timestamp
COMMAND env LIBRARY_PATH=${CMAKE_BINARY_DIR}/go/pserver/client/c/:$ENV{LIBRARY_PATH}
GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build
COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} build
-o "${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}"
"./${CMAKE_CURRENT_SOURCE_REL_DIR}/${go_binary_SRCS}"
WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
# TODO: don't know what ${TARGET_NAME}_link does
add_custom_target(${TARGET_NAME} ALL DEPENDS go_vendor ${TARGET_NAME}_timestamp ${go_binary_DEPS})
install(PROGRAMS ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME} DESTINATION bin)
endfunction(go_binary)
......@@ -334,15 +337,18 @@ endfunction(go_binary)
function(go_test TARGET_NAME)
set(options OPTIONAL)
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS)
set(multiValueArgs DEPS)
cmake_parse_arguments(go_test "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
add_custom_command(OUTPUT ${TARGET_NAME}_timestamp
COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} test
string(REPLACE "${PADDLE_GO_PATH}" "" CMAKE_CURRENT_SOURCE_REL_DIR ${CMAKE_CURRENT_SOURCE_DIR})
add_custom_target(${TARGET_NAME} ALL DEPENDS go_vendor ${go_test_DEPS})
add_custom_command(TARGET ${TARGET_NAME} POST_BUILD
COMMAND env GOPATH=${GOPATH} ${CMAKE_Go_COMPILER} test -race
-c -o "${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}"
${go_test_SRCS}
".${CMAKE_CURRENT_SOURCE_REL_DIR}"
WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go")
add_test(NAME ${TARGET_NAME}
COMMAND ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME}
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR})
add_custom_target(${TARGET_NAME} ALL DEPENDS ${TARGET_NAME}_timestamp ${go_test_DEPS})
add_test(${TARGET_NAME} ${CMAKE_CURRENT_BINARY_DIR}/${TARGET_NAME})
endfunction(go_test)
function(proto_library TARGET_NAME)
......
doc/api/v2/config/layer.rst
浏览文件 @ 60a78893
......@@ -474,6 +474,11 @@ prelu
.. autoclass:: paddle.v2.layer.prelu
:noindex:
gated_unit
-----------
.. autoclass:: paddle.v2.layer.gated_unit
:noindex:
Detection output Layer
======================
......
doc/howto/dev/new_layer_cn.rst
浏览文件 @ 60a78893
......@@ -37,7 +37,7 @@
\frac{\partial c(y)}{\partial x} = \frac{\partial c(y)}{\partial y} \frac{\partial y}{\partial x}
假设 :math:`z = f(W^T x + b)` ，那么
假设 :math:`z = W^T x + b` ，那么
.. math::
......
doc/howto/dev/new_layer_en.rst
浏览文件 @ 60a78893
......@@ -29,7 +29,7 @@ Fully connected layer takes a dense input vector with dimension :math:`D_i`. It
where :math:`f(.)` is an nonlinear *activation* function, such as sigmoid, tanh, and Relu.
The transformation matrix :math:`W` and bias vector :math:`b` are the *parameters* of the layer. The *parameters* of a layer are learned during training in the *backward pass*. The backward pass computes the gradients of the output function with respect to all parameters and inputs. The optimizer can use chain rule to compute the gradients of the loss function with respect to each parameter.
The transformation matrix :math:`W` and bias vector :math:`b` are the *parameters* of the layer. The *parameters* of a layer are learned during training in the *backward pass*. The backward pass computes the gradients of the output function with respect to all parameters and inputs. The optimizer can use chain rule to compute the gradients of the loss function with respect to each parameter.
Suppose our loss function is :math:`c(y)`, then
......@@ -37,7 +37,7 @@ Suppose our loss function is :math:`c(y)`, then
\frac{\partial c(y)}{\partial x} = \frac{\partial c(y)}{\partial y} \frac{\partial y}{\partial x}
Suppose :math:`z = f(W^T x + b)`, then
Suppose :math:`z = W^T x + b`, then
.. math::
......@@ -48,7 +48,7 @@ This derivative can be automatically computed by our base layer class.
Then, for fully connected layer, we need to compute:
.. math::
\frac{\partial z}{\partial x} = W, \frac{\partial z_j}{\partial W_{ij}} = x_i, \frac{\partial z}{\partial b} = \mathbf 1
where :math:`\mathbf 1` is an all one vector, :math:`W_{ij}` is the number at the i-th row and j-th column of the matrix :math:`W`, :math:`z_j` is the j-th component of the vector :math:`z`, and :math:`x_i` is the i-th component of the vector :math:`x`.
......@@ -322,7 +322,7 @@ All the gradient check unit tests are located in :code:`paddle/gserver/tests/tes
/* weight */ true);
}
}
If you are creating a new file for the test, such as :code:`paddle/gserver/tests/testFCGrad.cpp`, you need to add the file to :code:`paddle/gserver/tests/CMakeLists.txt`. An example is given below. All the unit tests will run when you execute the command :code:`make tests`. Notice that some layers might need high accuracy for the gradient check unit tests to work well. You need to configure :code:`WITH_DOUBLE` to `ON` when configuring cmake.
.. code-block:: bash
......
doc/howto/dev/write_docs_cn.rst
浏览文件 @ 60a78893
......@@ -41,7 +41,7 @@ PaddlePaddle文档需要准备的环境相对较复杂，所以我们推荐使
python -c "import py_paddle"
如果提示错误，那么用户需要在本地编译安装PaddlePaddle，请参考 `源码编译文档 <http://www.paddlepaddle.org/develop/doc/getstarted/build_and_install/build_from_source_en.html>`_ 。
如果提示错误，那么用户需要在本地编译安装PaddlePaddle，请参考 `源码编译文档 <http://doc.paddlepaddle.org/develop/doc/getstarted/build_and_install/build_from_source_en.html>`_ 。
注意，用户在首次编译安装PaddlePaddle时，请将WITH_DOC选项关闭。在编译安装正确之后，请再次确认py_paddle包已经安装，即可进行下一步操作。
如果提示正确，可以执行以下命令编译生成文档，即
......@@ -68,9 +68,9 @@ PaddlePaddle文档使用 `sphinx`_ 自动生成，用户可以参考sphinx教程
如何更新www.paddlepaddle.org文档
================================
开发者给PaddlePaddle代码增加的注释以PR的形式提交到github中，提交方式可参见 `贡献文档 <http://paddlepaddle.org/develop/doc_cn/howto/dev/contribute_to_paddle_cn.html>`_ 。
目前PaddlePaddle的develop分支的文档是自动触发更新的，用户可以分别查看最新的 `中文文档 <http://www.paddlepaddle.org/develop/doc_cn/>`_ 和
`英文文档 <http://www.paddlepaddle.org/develop/doc/>`_ 。
开发者给PaddlePaddle代码增加的注释以PR的形式提交到github中，提交方式可参见 `贡献文档 <http://doc.paddlepaddle.org/develop/doc_cn/howto/dev/contribute_to_paddle_cn.html>`_ 。
目前PaddlePaddle的develop分支的文档是自动触发更新的，用户可以分别查看最新的 `中文文档 <http://doc.paddlepaddle.org/develop/doc_cn/>`_ 和
`英文文档 <http://doc.paddlepaddle.org/develop/doc/>`_ 。
......
go/CMakeLists.txt
浏览文件 @ 60a78893
......@@ -17,3 +17,7 @@ add_subdirectory(pserver/client/c)
add_subdirectory(cmd/pserver)
add_subdirectory(cmd/master)
add_subdirectory(master/c)
add_subdirectory(master)
add_subdirectory(pserver)
add_subdirectory(pserver/client)
add_subdirectory(utils/networkhelper)
go/cmd/master/CMakeLists.txt
浏览文件 @ 60a78893
......@@ -12,4 +12,4 @@
# See the License for the specific language governing permissions and
# limitations under the License.
go_binary(master SRC master.go DEPS paddle_go_optimizer)
go_binary(master SRC master.go)
go/cmd/master/master.go
浏览文件 @ 60a78893
......@@ -11,6 +11,7 @@ import (
"github.com/namsral/flag"
log "github.com/sirupsen/logrus"
"github.com/topicai/candy"
"github.com/PaddlePaddle/Paddle/go/master"
"github.com/PaddlePaddle/Paddle/go/utils/networkhelper"
......@@ -20,11 +21,18 @@ func main() {
port := flag.Int("port", 8080, "port of the master server.")
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.")
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.")
logLevel := flag.String("log-level", "info",
"log level, possible values: debug, info, warning, error, fatal, panic")
flag.Parse()
level, e := log.ParseLevel(*logLevel)
candy.Must(e)
log.SetLevel(level)
if *endpoints == "" {
log.Warningln("-endpoints not set, fault tolerance not be enabled.")
}
......
go/cmd/pserver/pserver.go
浏览文件 @ 60a78893
......@@ -8,6 +8,7 @@ import (
"time"
"github.com/namsral/flag"
"github.com/topicai/candy"
"github.com/PaddlePaddle/Paddle/go/pserver"
log "github.com/sirupsen/logrus"
......@@ -18,53 +19,47 @@ func main() {
index := flag.Int("index", -1, "index of this pserver, should be larger or equal than 0")
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")
etcdTimeout := flag.Duration("etcd-timeout", 5*time.Second, "timeout for etcd calls")
numPservers := flag.Int("num-pservers", 1, "total pserver count in a training job")
checkpointPath := flag.String("checkpoint-path", "/checkpoints/", "save checkpoint path")
checkpointInterval := flag.Int("checkpoint-interval", 600, "save checkpoint per interval seconds")
checkpointInterval := flag.Duration("checkpoint-interval", 600*time.Second, "save checkpoint per interval seconds")
logLevel := flag.String("log-level", "info",
"log level, possible values: debug, info, warning, error, fatal, panic")
flag.Parse()
level, err := log.ParseLevel(*logLevel)
if err != nil {
panic(err)
}
candy.Must(err)
log.SetLevel(level)
var idx int
var cp pserver.Checkpoint
var e *pserver.EtcdClient
if *index >= 0 {
idx = *index
} else {
timeout := time.Second * time.Duration((*etcdTimeout))
e = pserver.NewEtcdClient(*etcdEndpoint, *numPservers, timeout)
idx, err = e.Register()
e = pserver.NewEtcdClient(*etcdEndpoint, *numPservers, *etcdTimeout)
idx, err = e.Register(*port)
candy.Must(err)
cp, err = pserver.NewCheckpointFromFile(*checkpointPath, idx, e)
if err != nil {
panic(err)
log.Errorf("Fetch checkpoint failed, %s", err)
}
}
s, err := pserver.NewService(idx, *checkpointInterval, *checkpointPath, e, cp)
if err != nil {
panic(err)
}
candy.Must(err)
err = rpc.Register(s)
if err != nil {
panic(err)
}
candy.Must(err)
rpc.HandleHTTP()
l, err := net.Listen("tcp", ":"+strconv.Itoa(*port))
if err != nil {
panic(err)
}
candy.Must(err)
log.Infof("start pserver at port %d", *port)
err = http.Serve(l, nil)
if err != nil {
panic(err)
}
candy.Must(err)
}
go/glide.lock
浏览文件 @ 60a78893
hash: b8f18ce6784bd3fadd9fed0b8443e7b658234ea785ae1f220723ae2c1f652aa7
updated: 2017-06-27T14:05:48.925262819+08:00
hash: a8faea3a363468a88917ddeb3b1c9ea36886fb2c622acbad42604fa9cb4d3855
updated: 2017-07-11T10:04:40.786745417+08:00
imports:
- name: github.com/coreos/etcd
version: 61fc123e7a8b14a0a258aa3f5c4159861b1ec2e7
version: cb2a496c4ddd1c87a9f280e116649b599999ec79
subpackages:
- auth/authpb
- clientv3
......@@ -22,7 +22,9 @@ imports:
- name: github.com/PaddlePaddle/recordio
version: edfb82af0739c84f241c87390ec5649c7b28c129
- name: github.com/sirupsen/logrus
version: 202f25545ea4cf9b191ff7f846df5d87c9382c2b
version: 7f976d3a76720c4c27af2ba716b85d2e0a7e38b1
- name: github.com/topicai/candy
version: 1b9030d056fa9f8c4b1f9c91b52fe4b8ab4cd8cc
- name: golang.org/x/net
version: c8c74377599bd978aee1cf3b9b63a8634051cec2
subpackages:
......@@ -34,11 +36,11 @@ imports:
- lex/httplex
- trace
- name: golang.org/x/sys
version: f7928cfef4d09d1b080aa2b6fd3ca9ba1567c733
version: abf9c25f54453410d0c6668e519582a9e1115027
subpackages:
- unix
- name: golang.org/x/text
version: 4e9ab9ee170f2a39bd66c92b3e0a47ff47a4bc77
version: cfdf022e86b4ecfb646e1efbd7db175dd623a8fa
subpackages:
- secure/bidirule
- transform
......
go/glide.yaml
浏览文件 @ 60a78893
......@@ -10,3 +10,4 @@ import:
version: ^1.7.4-pre
- package: github.com/sirupsen/logrus
version: ^1.0.0
- package: github.com/topicai/candy
go/master/CMakeLists.txt 0 → 100644
浏览文件 @ 60a78893
if(WITH_TESTING)
go_test(master_test)
endif()
go/master/c/client.go
浏览文件 @ 60a78893
......@@ -23,7 +23,6 @@ import (
log "github.com/sirupsen/logrus"
)
var nullPtr = unsafe.Pointer(uintptr(0))
var mu sync.Mutex
var handleMap = make(map[C.paddle_master_client]*master.Client)
var curHandle C.paddle_master_client
......@@ -114,13 +113,13 @@ func paddle_next_record(client C.paddle_master_client, record **C.uchar) C.int {
if err != nil {
// Error
// TODO: return the type of error?
*record = (*C.uchar)(nullPtr)
*record = (*C.uchar)(nil)
return -1
}
if len(r) == 0 {
// Empty record
*record = (*C.uchar)(nullPtr)
*record = (*C.uchar)(nil)
return 0
}
......
go/master/client.go
浏览文件 @ 60a78893
......@@ -2,6 +2,7 @@ package master
import (
"os"
"time"
"github.com/PaddlePaddle/Paddle/go/connection"
"github.com/PaddlePaddle/recordio"
......@@ -36,9 +37,9 @@ func (c *Client) getRecords() {
for {
t, err := c.getTask()
if err != nil {
// TODO(helin): wait before move on with next
// getTask call.
log.Errorln(err)
log.Errorf("Get task failed, sleep 3 seconds and continue, %s", err)
time.Sleep(3 * time.Second)
continue
}
......@@ -68,7 +69,10 @@ func (c *Client) getRecords() {
// We treat a task as finished whenever the last data
// instance of the task is read. This is not exactly
// correct, but a reasonable approximation.
c.taskFinished(t.ID)
err = c.taskFinished(t.Meta.ID)
if err != nil {
log.Errorln(err)
}
}
}
......@@ -118,6 +122,11 @@ func (c *Client) taskFinished(taskID int) error {
return c.conn.Call("Service.TaskFinished", taskID, nil)
}
// TaskFailed tell the master server as task is failed.
func (c *Client) taskFailed(meta TaskMeta) error {
return c.conn.Call("Service.TaskFailed", meta, nil)
}
// NextRecord returns next record in the dataset.
//
// NextRecord will block until the next record is available. It is
......
go/master/client_internal_test.go
浏览文件 @ 60a78893
......@@ -66,11 +66,21 @@ func TestGetFinishTask(t *testing.T) {
for i := 0; i < totalTask*chunkPerTask; i++ {
w := recordio.NewWriter(f, -1, -1)
w.Write(nil)
_, err = w.Write(nil)
if err != nil {
panic(err)
}
// call Close to force RecordIO writing a chunk.
w.Close()
err = w.Close()
if err != nil {
panic(err)
}
}
err = f.Close()
if err != nil {
panic(err)
}
f.Close()
// Manually intialize client to avoid calling c.getRecords()
c := &Client{}
......@@ -79,7 +89,11 @@ func TestGetFinishTask(t *testing.T) {
ch := make(chan string, 1)
ch <- addr
go c.monitorMaster(ch)
c.SetDataset([]string{path})
err = c.SetDataset([]string{path})
if err != nil {
panic(err)
}
checkOnePass := func(i int) {
var tasks []Task
for idx := 0; idx < totalTask; idx++ {
......@@ -95,10 +109,16 @@ func TestGetFinishTask(t *testing.T) {
t.Fatalf("Should get error, pass: %d\n", i)
}
err = c.taskFinished(tasks[0].ID)
err = c.taskFinished(tasks[0].Meta.ID)
if err != nil {
t.Fatalf("Error: %v, pass: %d\n", err, i)
}
err = c.taskFailed(tasks[0].Meta)
if err != nil {
t.Fatalf("Error: %v, pass: %d\n", err, i)
}
tasks = tasks[1:]
task, err := c.getTask()
if err != nil {
......@@ -107,7 +127,7 @@ func TestGetFinishTask(t *testing.T) {
tasks = append(tasks, task)
for _, task := range tasks {
err = c.taskFinished(task.ID)
err = c.taskFinished(task.Meta.ID)
if err != nil {
t.Fatalf("Error: %v, pass: %d\n", err, i)
}
......
go/master/client_test.go
浏览文件 @ 60a78893
......@@ -57,14 +57,30 @@ func TestNextRecord(t *testing.T) {
w := recordio.NewWriter(f, -1, -1)
for i := 0; i < total; i++ {
w.Write([]byte{byte(i)})
_, err = w.Write([]byte{byte(i)})
if err != nil {
panic(err)
}
}
err = w.Close()
if err != nil {
panic(err)
}
err = f.Close()
if err != nil {
panic(err)
}
w.Close()
f.Close()
curAddr := make(chan string, 1)
curAddr <- fmt.Sprintf(":%d", p)
c := master.NewClient(curAddr, 10)
c.SetDataset([]string{path})
err = c.SetDataset([]string{path})
if err != nil {
panic(err)
}
for pass := 0; pass < 50; pass++ {
received := make(map[byte]bool)
for i := 0; i < total; i++ {
......
go/master/etcd_client.go
浏览文件 @ 60a78893
......@@ -30,7 +30,7 @@ type EtcdClient struct {
// 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
// TODO(helin): gracefully shutdown etcd store. Because 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.
......@@ -60,7 +60,7 @@ func NewEtcdClient(endpoints []string, addr string, lockPath, addrPath, statePat
}
log.Debugf("Successfully acquired lock at %s.", lockPath)
put := clientv3.OpPut(addrPath, string(addr))
put := clientv3.OpPut(addrPath, addr)
resp, err := cli.Txn(context.Background()).If(lock.IsOwner()).Then(put).Commit()
if err != nil {
return nil, err
......
go/master/inmem_store.go
浏览文件 @ 60a78893
......@@ -4,7 +4,7 @@ import "sync"
// InMemStore is an in memory implementation of Store interface.
//
// It does not tolerate the fault that casues the program to crash.
// It does not tolerate the fault that causes the program to crash.
type InMemStore struct {
mu sync.Mutex
buf []byte
......
go/master/service.go
浏览文件 @ 60a78893
......@@ -31,30 +31,36 @@ type Chunk struct {
Index recordio.Index // chunk index
}
// TaskMeta is a struct which stores task's meta info.
type TaskMeta struct {
ID int
Epoch int
}
// Task is the basic unit of data instances assigned to trainers.
type Task struct {
ID int
Meta TaskMeta
Chunks []Chunk
}
type taskEntry struct {
Epoch int
NumTimeout int
Task Task
Task Task
// A task fails if it's timeout or trainer reports it exits unnormally.
NumFailure int
}
type taskQueues struct {
Todo []taskEntry
Pending map[int]taskEntry // map from task ID to task entry
Done []taskEntry
Failed []Task
Failed []taskEntry
}
// Service is the master server service.
type Service struct {
chunksPerTask int
timeoutDur time.Duration
timeoutMax int
failureMax int
ready chan struct{}
store Store
......@@ -73,7 +79,7 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
var cur taskEntry
for i, c := range chunks {
if i%chunksPerTask == 0 && len(cur.Task.Chunks) > 0 {
cur.Task.ID = id
cur.Task.Meta.ID = id
id++
result = append(result, cur)
cur.Task.Chunks = nil
......@@ -83,7 +89,7 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
}
if len(cur.Task.Chunks) > 0 {
cur.Task.ID = id
cur.Task.Meta.ID = id
result = append(result, cur)
}
......@@ -91,11 +97,11 @@ func partition(chunks []Chunk, chunksPerTask int) []taskEntry {
}
// NewService creates a new service.
func NewService(store Store, chunksPerTask int, timeoutDur time.Duration, timeoutMax int) (*Service, error) {
func NewService(store Store, chunksPerTask int, timeoutDur time.Duration, failureMax int) (*Service, error) {
s := &Service{}
s.chunksPerTask = chunksPerTask
s.timeoutDur = timeoutDur
s.timeoutMax = timeoutMax
s.failureMax = failureMax
s.taskQueues = taskQueues{}
s.taskQueues.Pending = make(map[int]taskEntry)
s.ready = make(chan struct{})
......@@ -154,7 +160,7 @@ func (s *Service) recover() (bool, error) {
// snapshot *must* be called with s.mu being held.
func (s *Service) snapshot() error {
// TOOD(helin): etcd request has a size limit, so the snapshot
// TODO(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
......@@ -209,6 +215,7 @@ func readChunks(globPaths []string) ([]Chunk, error) {
}
count := index.NumChunks()
log.Infof("readChunks: file %s has %d chunks", path, count)
for i := 0; i < count; i++ {
chunk := Chunk{
Path: path,
......@@ -257,6 +264,33 @@ func (s *Service) SetDataset(globPaths []string, dummy *int) error {
return nil
}
func (s *Service) processFailedTask(t taskEntry, epoch int) {
if t.Task.Meta.Epoch != epoch {
// new epoch, task launched after the
// schedule of this timeout check or failed status report.
return
}
defer func() {
err := s.snapshot()
if err != nil {
log.Errorln(err)
}
}()
delete(s.taskQueues.Pending, t.Task.Meta.ID)
t.NumFailure++
if t.NumFailure > s.failureMax {
log.Warningf("Task %v failed %d times, discard.", t.Task, t.NumFailure)
s.taskQueues.Failed = append(s.taskQueues.Failed, t)
return
}
log.Warningf("Task %v failed %d times, discard.", t.Task, t.NumFailure)
s.taskQueues.Todo = append(s.taskQueues.Todo, t)
}
func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() {
return func() {
s.mu.Lock()
......@@ -267,30 +301,7 @@ func (s *Service) checkTimeoutFunc(taskID int, epoch int) func() {
return
}
if t.Epoch != epoch {
// new epoch, task launched after the
// schedule of this timeout check.
return
}
defer func() {
err := s.snapshot()
if err != nil {
log.Errorln(err)
}
}()
delete(s.taskQueues.Pending, t.Task.ID)
t.NumTimeout++
if t.NumTimeout > s.timeoutMax {
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.", t.Task, t.NumTimeout)
s.taskQueues.Todo = append(s.taskQueues.Todo, t)
s.processFailedTask(t, epoch)
}
}
......@@ -339,18 +350,18 @@ func (s *Service) GetTask(dummy int, task *Task) error {
}
t := s.taskQueues.Todo[0]
t.Epoch++
t.Task.Meta.Epoch++
s.taskQueues.Todo = s.taskQueues.Todo[1:]
s.taskQueues.Pending[t.Task.ID] = t
s.taskQueues.Pending[t.Task.Meta.ID] = t
err := s.snapshot()
if err != nil {
return err
}
*task = t.Task
log.WithFields(s.logFields()).Infof("Task #%d dispatched.", task.ID)
log.WithFields(s.logFields()).Infof("Task #%v dispatched.", t.Task.Meta)
time.AfterFunc(s.timeoutDur, s.checkTimeoutFunc(t.Task.ID, t.Epoch))
time.AfterFunc(s.timeoutDur, s.checkTimeoutFunc(t.Task.Meta.ID, t.Task.Meta.Epoch))
return nil
}
......@@ -365,13 +376,12 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error {
t, ok := s.taskQueues.Pending[taskID]
if !ok {
err := errors.New("pending task not found")
log.WithFields(s.logFields()).Warningln("Pending task #%d not found.", taskID)
return err
return nil
}
// task finished, reset timeout
t.NumTimeout = 0
t.NumFailure = 0
s.taskQueues.Done = append(s.taskQueues.Done, t)
delete(s.taskQueues.Pending, taskID)
......@@ -389,3 +399,22 @@ func (s *Service) TaskFinished(taskID int, dummy *int) error {
}
return err
}
// TaskFailed tells the service that a task is failed.
func (s *Service) TaskFailed(meta TaskMeta, dummy *int) error {
select {
case <-s.ready:
}
s.mu.Lock()
defer s.mu.Unlock()
t, ok := s.taskQueues.Pending[meta.ID]
if !ok {
log.WithFields(s.logFields()).Warningln("TaskFailed:Pending task #%v not found.", t.Task.Meta)
return nil
}
s.processFailedTask(t, meta.Epoch)
return nil
}
go/master/service_internal_test.go
浏览文件 @ 60a78893
......@@ -30,7 +30,7 @@ func TestPartionIndex(t *testing.T) {
cs := make([]Chunk, 100)
ts := partition(cs, 20)
for i := range ts {
if ts[i].Task.ID != i {
if ts[i].Task.Meta.ID != i {
t.Error(ts[i], i)
}
}
......
go/pserver/CMakeLists.txt 0 → 100644
浏览文件 @ 60a78893
if(WITH_TESTING)
go_test(pserver_test DEPS paddle_go_optimizer)
endif()
go/pserver/client/CMakeLists.txt 0 → 100644
浏览文件 @ 60a78893
if(WITH_TESTING)
go_test(pserver_client_test DEPS paddle_go_optimizer)
endif()
go/pserver/client/c/.gitignore 0 → 100644
浏览文件 @ 60a78893
libpaddle_go_optimizer.a
go/pserver/client/c/CMakeLists.txt
浏览文件 @ 60a78893
cc_library(paddle_go_optimizer DEPS paddle_optimizer paddle_proto glog gflags protobuf)
target_link_libraries(paddle_go_optimizer stdc++ m)
# Copy library to the required place.
# See: go/pserver/optimizer.go:
# // #cgo LDFLAGS: ${SRCDIR}/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
add_custom_command(TARGET paddle_go_optimizer POST_BUILD
COMMAND cp "${CMAKE_CURRENT_BINARY_DIR}/libpaddle_go_optimizer.a" "${CMAKE_CURRENT_SOURCE_DIR}"
)
go_library(paddle_pserver_cclient STATIC DEPS paddle_go_optimizer)
if(WITH_TESTING)
# FIXME: this test requires pserver which is not managed by the test
......
go/pserver/client/c/cclient.go
浏览文件 @ 60a78893
......@@ -34,7 +34,6 @@ import (
log "github.com/sirupsen/logrus"
)
var nullPtr = unsafe.Pointer(uintptr(0))
var mu sync.Mutex
var handleMap = make(map[C.paddle_pserver_client]*client.Client)
var curHandle C.paddle_pserver_client
......@@ -63,7 +62,7 @@ func remove(client C.paddle_pserver_client) *client.Client {
}
func cArrayToSlice(p unsafe.Pointer, len int) []byte {
if p == nullPtr {
if p == nil {
return nil
}
......@@ -101,11 +100,11 @@ func paddle_new_pserver_client(addrs *C.char, selected int) C.paddle_pserver_cli
}
//export paddle_new_etcd_pserver_client
func paddle_new_etcd_pserver_client(etcd_endpoints *C.char, selected int) C.paddle_pserver_client {
func paddle_new_etcd_pserver_client(etcdEndpoints *C.char, selected int) C.paddle_pserver_client {
// TODO(Longfei: use etcd lock to decide which trainer to initialize the parameters)
addr := C.GoString(etcd_endpoints)
etcd_client := client.NewEtcd(addr)
c := client.NewClient(etcd_client, etcd_client.Desired(), selector(selected != 0))
addr := C.GoString(etcdEndpoints)
etcdClient := client.NewEtcd(addr)
c := client.NewClient(etcdClient, etcdClient.Desired(), selector(selected != 0))
return add(c)
}
......@@ -124,20 +123,20 @@ func paddle_begin_init_params(client C.paddle_pserver_client) C.int {
}
//export paddle_init_param
func paddle_init_param(client C.paddle_pserver_client, param C.paddle_parameter, param_config unsafe.Pointer, config_len C.int) C.int {
func paddle_init_param(client C.paddle_pserver_client, param C.paddle_parameter, paramConfig unsafe.Pointer, configLen C.int) C.int {
et := pserver.ElementType(param.element_type)
name := C.GoString(param.name)
content := cArrayToSlice(unsafe.Pointer(param.content), int(param.content_len))
pc := pserver.ParameterWithConfig{
Param: pserver.Parameter{Name: name, ElementType: et, Content: content},
Config: cArrayToSlice(param_config, int(config_len)),
Config: cArrayToSlice(paramConfig, int(configLen)),
}
c := get(client)
err := c.InitParam(pc)
if err != nil {
if err.Error() == pserver.AlreadyInitialized {
log.Warningf("parameter %s already initialized, treat paddle_init_param as sucessful.", name)
log.Warningf("parameter %s already initialized, treat paddle_init_param as successful.", name)
return C.PSERVER_OK
}
log.Errorln(err)
......@@ -153,7 +152,7 @@ func paddle_finish_init_params(client C.paddle_pserver_client) C.int {
err := c.FinishInitParams()
if err != nil {
if err.Error() == pserver.AlreadyInitialized {
log.Warningln("parameters already initialized, treat paddle_finish_init_params as sucessful.")
log.Warningln("parameters already initialized, treat paddle_finish_init_params as successful.")
return C.PSERVER_OK
}
......@@ -223,12 +222,12 @@ func paddle_get_params(client C.paddle_pserver_client, dst **C.paddle_parameter,
p := ps[i]
param := *(**C.paddle_parameter)(unsafe.Pointer((uintptr(unsafe.Pointer(dst)) + uintptr(i)*unsafe.Sizeof(*dst))))
if unsafe.Pointer(param) == nullPtr {
if unsafe.Pointer(param) == nil {
log.Errorln("must pre-allocate parameter.")
return C.PSERVER_ERROR
}
if unsafe.Pointer(param.content) != nullPtr {
if unsafe.Pointer(param.content) != nil {
if int(param.content_len) != len(p.Content) {
log.Errorf("the pre-allocated content len does not match parameter content len. Pre-allocated len: %d, returned len: %d", param.content_len, len(p.Content))
return C.PSERVER_ERROR
......
go/pserver/client/c/test/test_train.py
浏览文件 @ 60a78893
import paddle.v2 as paddle
import paddle.v2.dataset.uci_housing as uci_housing
import paddle.v2.master as master
import os
import cPickle as pickle
etcd_ip = os.getenv("MASTER_IP", "127.0.0.1")
etcd_endpoint = "http://" + etcd_ip + ":2379"
def cloud_reader():
print "connecting to master, etcd endpoints: ", etcd_endpoint
master_client = master.client(etcd_endpoint, 5, 64)
master_client.set_dataset(
["/pfs/dlnel/public/dataset/uci_housing/uci_housing-*-of-*"])
while 1:
r, e = master_client.next_record()
if not r:
break
yield pickle.loads(r)
def main():
......@@ -19,16 +37,16 @@ def main():
# create parameters
parameters = paddle.parameters.create(cost)
# create optimizer
# create optimizer of new remote updater to pserver
optimizer = paddle.optimizer.Momentum(momentum=0)
#TODO(zhihong) : replace optimizer with new OptimizerConfig
print "etcd endoint: ", etcd_endpoint
trainer = paddle.trainer.SGD(cost=cost,
parameters=parameters,
update_equation=optimizer,
is_local=False,
pserver_spec="localhost:3000")
pserver_spec=etcd_endpoint,
use_etcd=True)
# event_handler to print training and testing info
def event_handler(event):
......@@ -47,11 +65,11 @@ def main():
print "Test %d, %.2f" % (event.pass_id, result.cost)
# training
# NOTE: use uci_housing.train() as reader for non-paddlecloud training
trainer.train(
reader=paddle.batch(
paddle.reader.shuffle(
uci_housing.train(), buf_size=500),
batch_size=2),
cloud_reader, buf_size=500), batch_size=2),
feeding={'x': 0,
'y': 1},
event_handler=event_handler,
......
go/pserver/client/client.go
浏览文件 @ 60a78893
......@@ -233,7 +233,7 @@ func (c *Client) Save(path string) error {
func strHash(s string) uint32 {
h := fnv.New32a()
h.Write([]byte(s))
_, _ = h.Write([]byte(s))
return h.Sum32()
}
......
go/pserver/client/client_test.go
浏览文件 @ 60a78893
......@@ -3,11 +3,13 @@ package client_test
import (
"context"
"io/ioutil"
"math/rand"
"net"
"net/http"
"net/rpc"
"strconv"
"strings"
"sync"
"testing"
"time"
......@@ -42,7 +44,8 @@ func initClient() [numPserver]int {
ports[i] = p
go func(l net.Listener) {
s, err := pserver.NewService(0)
var cp pserver.Checkpoint
s, err := pserver.NewService(0, 1, "", nil, cp)
if err != nil {
panic(err)
}
......@@ -76,15 +79,33 @@ func initEtcdClient() {
log.Errorf("err %v", err)
}
ctx, cancel := context.WithTimeout(context.Background(), timeout)
client.Delete(ctx, pserver.PsDesired)
client.Delete(ctx, pserver.PsPath)
client.Put(ctx, pserver.PsDesired, strconv.Itoa(numPserver))
_, err = client.Delete(ctx, pserver.PsDesired)
if err != nil {
panic(err)
}
_, err = client.Delete(ctx, pserver.PsPath)
if err != nil {
panic(err)
}
_, err = client.Put(ctx, pserver.PsDesired, strconv.Itoa(numPserver))
if err != nil {
panic(err)
}
ports := initClient()
for i := 0; i < numPserver; i++ {
client.Put(ctx, pserver.PsPath+strconv.Itoa(i), ":"+strconv.Itoa(ports[i]))
_, err = client.Put(ctx, pserver.PsPath+strconv.Itoa(i), ":"+strconv.Itoa(ports[i]))
if err != nil {
panic(err)
}
}
cancel()
client.Close()
err = client.Close()
if err != nil {
panic(err)
}
}
type selector bool
......@@ -99,27 +120,34 @@ func (l lister) List() []client.Server {
return l
}
func ClientTest(t *testing.T, c *client.Client) {
func testClient(t *testing.T, c *client.Client) {
selected := c.BeginInitParams()
if !selected {
t.Fatal("should be selected.")
}
const numParameter = 100
const numParameter = 1000
config, err := ioutil.ReadFile("./c/test/testdata/optimizer.pb")
if err != nil {
t.Fatalf("read optimizer proto failed")
}
var wg sync.WaitGroup
for i := 0; i < numParameter; i++ {
var p pserver.Parameter
p.Name = "p_" + strconv.Itoa(i)
p.ElementType = pserver.Float32
p.Content = make([]byte, (i+1)*100)
err := c.InitParam(pserver.ParameterWithConfig{Param: p, Config: config})
if err != nil {
t.Fatal(err)
}
wg.Add(1)
go func(i int) {
var p pserver.Parameter
p.Name = "p_" + strconv.Itoa(i)
p.ElementType = pserver.Float32
p.Content = make([]byte, (i+1)*100)
err := c.InitParam(pserver.ParameterWithConfig{Param: p, Config: config})
if err != nil {
t.Fatal(err)
}
wg.Done()
}(i)
}
wg.Wait()
err = c.FinishInitParams()
if err != nil {
......@@ -127,7 +155,7 @@ func ClientTest(t *testing.T, c *client.Client) {
}
var grads []pserver.Gradient
for i := 0; i < numParameter/2; i++ {
for i := 0; i < numParameter; i++ {
var g pserver.Gradient
g.Name = "p_" + strconv.Itoa(i)
g.ElementType = pserver.Float32
......@@ -135,9 +163,31 @@ func ClientTest(t *testing.T, c *client.Client) {
grads = append(grads, g)
}
err = c.SendGrads(grads)
if err != nil {
t.Fatal(err)
const paramPerGroup = 10
const numGroups = numParameter / paramPerGroup
// shuffle send grads order
for i := range grads {
j := rand.Intn(i + 1)
grads[i], grads[j] = grads[j], grads[i]
}
for i := 0; i < numGroups; i++ {
var gs []pserver.Gradient
if i == numGroups-1 {
gs = grads[i*paramPerGroup:]
} else {
gs = grads[i*paramPerGroup : (i+1)*paramPerGroup]
}
wg.Add(1)
go func(gs []pserver.Gradient) {
err := c.SendGrads(gs)
if err != nil {
t.Fatal(err)
}
wg.Done()
}(gs)
}
names := make([]string, numParameter)
......@@ -145,20 +195,35 @@ func ClientTest(t *testing.T, c *client.Client) {
names[i] = "p_" + strconv.Itoa(i)
}
params, err := c.GetParams(names)
if err != nil {
t.Fatal(err)
}
for i := 0; i < numGroups; i++ {
var ns []string
if i == numGroups-1 {
ns = names[i*paramPerGroup:]
} else {
ns = names[i*paramPerGroup : (i+1)*paramPerGroup]
}
if len(names) != len(params) {
t.Fatalf("parameter size not match, need: %d, have: %d", len(names), len(params))
}
wg.Add(1)
go func(ns []string) {
params, err := c.GetParams(ns)
if err != nil {
t.Fatal(err)
}
for i := range params {
if names[i] != params[i].Name {
t.Fatalf("order of returned parameter does not required: parameter name: %s, required name: %s", names[i], params[i].Name)
}
if len(ns) != len(params) {
t.Fatalf("parameter size not match, need: %d, have: %d", len(names), len(params))
}
for i := range params {
if ns[i] != params[i].Name {
t.Fatalf("order of returned parameter does not required: parameter name: %s, required name: %s", ns[i], params[i].Name)
}
}
wg.Done()
}(ns)
}
wg.Wait()
}
func TestNativeClient(t *testing.T) {
......@@ -168,13 +233,14 @@ func TestNativeClient(t *testing.T) {
servers[i] = client.Server{Index: i, Addr: ":" + strconv.Itoa(pserverClientPorts[i])}
}
c1 := client.NewClient(lister(servers), len(servers), selector(true))
ClientTest(t, c1)
testClient(t, c1)
}
// TODO: tmperary disable etcdClient test for dependency of etcd)
// EtcdClient is a disabled test, since we have not embedded etcd into
// our test.
func EtcdClient(t *testing.T) {
initEtcdClient()
etcd_client := client.NewEtcd(etcdEndpoints)
c2 := client.NewClient(etcd_client, etcd_client.Desired(), selector(true))
ClientTest(t, c2)
etcdClient := client.NewEtcd(etcdEndpoints)
c2 := client.NewClient(etcdClient, etcdClient.Desired(), selector(true))
testClient(t, c2)
}
go/pserver/client/etcd_client.go
浏览文件 @ 60a78893
......@@ -12,7 +12,7 @@ import (
)
const (
DefaultEtcdTimeout time.Duration = 5 * time.Second
defaultEtcdTimeout time.Duration = 5 * time.Second
)
// EtcdClient is used by pserver client that is a part of trainer process.
......@@ -47,7 +47,7 @@ func (p *EtcdClient) Desired() int {
psDesired, err = strconv.Atoi(string(resp.Kvs[0].Value))
if err != nil {
log.Errorf("psDesired %s invalid %v", psDesired, err)
log.Errorf("psDesired %d invalid %v", psDesired, err)
time.Sleep(p.timeout)
continue
}
......@@ -106,11 +106,11 @@ func NewEtcd(endpoints string) *EtcdClient {
for {
cli, err = clientv3.New(clientv3.Config{
Endpoints: ep,
DialTimeout: DefaultEtcdTimeout,
DialTimeout: defaultEtcdTimeout,
})
if err != nil {
log.Errorf("Init etcd connection failed: %v", err)
time.Sleep(DefaultEtcdTimeout)
time.Sleep(defaultEtcdTimeout)
continue
}
break
......@@ -118,7 +118,7 @@ func NewEtcd(endpoints string) *EtcdClient {
log.Infof("Connected to etcd: %s\n", endpoints)
client := &EtcdClient{
client: cli,
timeout: DefaultEtcdTimeout,
timeout: defaultEtcdTimeout,
endpoints: ep,
}
return client
......
go/pserver/etcd_client.go
浏览文件 @ 60a78893
......@@ -16,7 +16,7 @@ import (
const (
// PsDesired is etcd path for store desired pserver count
PsDesired = "/ps_desired"
// PsAddr is the base dir for pserver to store their addr
// PsPath is the base dir for pserver to store their addr
PsPath = "/ps/"
// PsCheckpoint is the etcd path for store checkpoints information
PsCheckpoint = "/checkpoints/"
......@@ -49,7 +49,7 @@ func NewEtcdClient(endpoints string, numPservers int, timeout time.Duration) *Et
// Register registers the pserver on etcd
//
// Register returns the index of the current pserver.
func (e *EtcdClient) Register() (int, error) {
func (e *EtcdClient) Register(port int) (int, error) {
var err error
e.externalIP, err = networkhelper.GetExternalIP()
......@@ -116,7 +116,7 @@ func (e *EtcdClient) Register() (int, error) {
for {
ctx, cancel := context.WithTimeout(context.Background(), time.Second)
var err error
pserverIdx, err = e.registerPserverEtcd(ctx)
pserverIdx, err = e.registerPserverEtcd(ctx, port)
cancel()
if err != nil {
log.Warn(err)
......@@ -140,7 +140,7 @@ func (e *EtcdClient) initDesiredPservers(ctx context.Context, numPservers int) (
}
// registerPserverEtcd registers pserver node on etcd using transaction.
func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
func (e *EtcdClient) registerPserverEtcd(ctx context.Context, port int) (int, error) {
var idx int
_, err := concurrency.NewSTM(e.etcdClient, func(c concurrency.STM) error {
registered := false
......@@ -156,8 +156,9 @@ func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
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)
pserverAddr := e.externalIP + ":" + strconv.Itoa(port)
c.Put(psKey, pserverAddr, clientv3.WithLease(resp.ID))
log.Debugf("set pserver node %s with value %s", psKey, pserverAddr)
ch, kaerr := e.etcdClient.KeepAlive(context.TODO(), resp.ID)
if kaerr != nil {
log.Errorf("keepalive etcd node error: %v", kaerr)
......@@ -176,10 +177,10 @@ func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
break
}
}
if registered == true {
if registered {
return nil
}
return errors.New("not registerd, may due to already have enough pservers")
return errors.New("not registered, may due to already have enough pservers")
}, concurrency.WithAbortContext(ctx), concurrency.WithIsolation(concurrency.RepeatableReads))
if err != nil {
......@@ -189,13 +190,26 @@ func (e *EtcdClient) registerPserverEtcd(ctx context.Context) (int, error) {
return idx, nil
}
// PutKey put into etcd with value by key specified
func (e *EtcdClient) PutKey(key string, value []byte, timeout int) error {
ctx, cancel := context.WithTimeout(context.Background(), time.Second*time.Duration(timeout))
_, err := e.etcdClient.Put(ctx, key, string(value))
// GetKey gets the value by the specified key
func (e *EtcdClient) GetKey(key string, timeout time.Duration) ([]byte, error) {
ctx, cancel := context.WithTimeout(context.Background(), timeout)
resp, err := e.etcdClient.Get(ctx, key)
cancel()
if err != nil {
return err
return []byte{}, err
}
return nil
kvs := resp.Kvs
if len(kvs) == 0 {
return []byte{}, nil
}
v := kvs[0].Value
return v, nil
}
// PutKey put into etcd with value by key specified
func (e *EtcdClient) PutKey(key string, value []byte, timeout time.Duration) error {
ctx, cancel := context.WithTimeout(context.Background(), timeout)
_, err := e.etcdClient.Put(ctx, key, string(value))
cancel()
return err
}
go/pserver/optimizer.go
浏览文件 @ 60a78893
package pserver
// #cgo CFLAGS: -I ../../
// //FIXME: ldflags contain "build" path
// #cgo LDFLAGS: ${SRCDIR}/../../build/go/pserver/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
// #cgo LDFLAGS: ${SRCDIR}/client/c/libpaddle_go_optimizer.a -lstdc++ -lm
// #include "paddle/optimizer/optimizer.h"
// #include <stdlib.h>
// #include <string.h>
......@@ -15,15 +14,14 @@ import (
log "github.com/sirupsen/logrus"
)
var nullPtr = unsafe.Pointer(uintptr(0))
type optimizer struct {
opt *C.struct_paddle_optimizer
elementType ElementType
contentLen int
}
func cArrayToSlice(p unsafe.Pointer, len int) []byte {
if p == nullPtr {
if p == nil {
return nil
}
......@@ -38,25 +36,28 @@ func cArrayToSlice(p unsafe.Pointer, len int) []byte {
func newOptimizer(paramWithConfigs ParameterWithConfig, State []byte) *optimizer {
o := &optimizer{}
o.elementType = paramWithConfigs.Param.ElementType
o.contentLen = len(paramWithConfigs.Param.Content)
p := paramWithConfigs.Param
c := paramWithConfigs.Config
s := State
paramBufferSize := C.size_t(len(p.Content))
log.WithFields(log.Fields{
"ElementType": p.ElementType,
"ParamSize": len(p.Content),
"ParamSize": paramBufferSize,
"ConfigSize": len(c),
"StateSize": len(s),
}).Info("New Optimizer Created with config:")
var cbuffer unsafe.Pointer
cbuffer = C.malloc(C.size_t(len(p.Content)))
C.memcpy(cbuffer, unsafe.Pointer(&p.Content[0]), C.size_t(len(p.Content)))
cbuffer = C.malloc(paramBufferSize)
C.memcpy(cbuffer, unsafe.Pointer(&p.Content[0]), paramBufferSize)
var cstate unsafe.Pointer
if len(s) != 0 {
cstate = unsafe.Pointer(&s[0])
}
o.opt = C.paddle_create_optimizer((*C.uchar)(&c[0]), C.int(len(c)),
C.paddle_element_type(p.ElementType), cbuffer, C.int(len(p.Content)/C.sizeof_float), (*C.char)(cstate), C.int(len(s)))
C.paddle_element_type(p.ElementType), cbuffer, C.int(paramBufferSize), (*C.char)(cstate), C.int(len(s)))
return o
}
......@@ -68,8 +69,8 @@ func (o *optimizer) GetWeights() []byte {
func (o *optimizer) GetStates() []byte {
var cbuffer *C.char
cbuffer_len := C.paddle_optimizer_get_state(o.opt, &cbuffer)
return cArrayToSlice(unsafe.Pointer(cbuffer), int(cbuffer_len))
cbufferLen := C.paddle_optimizer_get_state(o.opt, &cbuffer)
return cArrayToSlice(unsafe.Pointer(cbuffer), int(cbufferLen))
}
func (o *optimizer) UpdateParameter(g Gradient) error {
......@@ -77,7 +78,11 @@ func (o *optimizer) UpdateParameter(g Gradient) error {
return fmt.Errorf("Name: %s, parameter and gradient element type not match, parameter: %v, gradient: %v", g.Name, o.elementType, g.ElementType)
}
r := C.paddle_update_parameter(o.opt, C.paddle_element_type(g.ElementType), unsafe.Pointer(&g.Content[0]), C.int(len(g.Content))/C.sizeof_float)
if o.contentLen != len(g.Content) {
return fmt.Errorf("Name: %s, parameter and gradient does not have same content len, parameter: %d, gradient: %d", g.Name, o.contentLen, len(g.Content))
}
r := C.paddle_update_parameter(o.opt, C.paddle_element_type(g.ElementType), unsafe.Pointer(&g.Content[0]), C.int(len(g.Content)))
if r != 0 {
return fmt.Errorf("optimizer update returned error code: %d", r)
}
......@@ -85,8 +90,8 @@ func (o *optimizer) UpdateParameter(g Gradient) error {
}
func (o *optimizer) Cleanup() {
if unsafe.Pointer(o.opt) != nullPtr {
if unsafe.Pointer(o.opt) != nil {
C.paddle_release_optimizer(o.opt)
o.opt = (*C.struct_paddle_optimizer)(nullPtr)
o.opt = (*C.struct_paddle_optimizer)(nil)
}
}
go/pserver/service.go
浏览文件 @ 60a78893
......@@ -9,6 +9,7 @@ import (
"encoding/json"
"errors"
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strconv"
......@@ -21,14 +22,14 @@ import (
// ElementType is the type of elements of a Parameter.
type ElementType int
// RPC error message.
const (
// AlreadyInitialized is true if pserver is initialized
AlreadyInitialized = "pserver already initialized"
// Uninitialized is true if pserver not fully initialized
Uninitialized = "pserver not fully initialized"
AlreadyInitialized = "pserver already initialized"
Uninitialized = "pserver not fully initialized"
CheckpointMD5Failed = "checkpoint file MD5 validation failed"
)
// Supported element types
// Supported element types.
const (
Int32 ElementType = iota
UInt32
......@@ -51,21 +52,15 @@ type ParameterWithConfig struct {
Config []byte // parameter configuration in Proto Buffer format
}
// ParameterCheckpoint is Parameter and State checkpoint
type ParameterCheckpoint struct {
ParamConfig ParameterWithConfig
State []byte
}
// checkpoint signature
// checkpointMeta saves checkpoint metadata
type checkpointMeta struct {
UUID string `json:"uuid"`
Md5sum string `json:"md5sum"`
Timestamp string `json:"timestamp"`
MD5 string `json:"md5"`
Timestamp int64 `json:"timestamp"`
}
// Checkpoint is the pserver shard persist in file
type Checkpoint []ParameterCheckpoint
type Checkpoint []parameterCheckpoint
// Gradient is the gradient of the parameter.
type Gradient Parameter
......@@ -81,12 +76,53 @@ type Service struct {
optMap map[string]*optimizer
}
// parameterCheckpoint saves parameter checkpoint
type parameterCheckpoint struct {
ParameterWithConfig
State []byte
}
// NewCheckpointFromFile loads parameters and state from checkpoint file
func NewCheckpointFromFile(cpPath string, idx int, e *EtcdClient) (Checkpoint, error) {
v, err := e.GetKey(PsPath+string(idx), 3*time.Second)
if err != nil {
return nil, err
}
var cpMeta checkpointMeta
if err = json.Unmarshal(v, &cpMeta); err != nil {
return nil, err
}
fn := filepath.Join(cpPath, cpMeta.UUID)
if _, err = os.Stat(fn); os.IsNotExist(err) {
return nil, err
}
content, err := ioutil.ReadFile(fn)
if err != nil {
return nil, err
}
h := md5.New()
md5 := hex.EncodeToString(h.Sum(content))
if md5 != cpMeta.MD5 {
return nil, errors.New(CheckpointMD5Failed)
}
dec := gob.NewDecoder(bytes.NewReader(content))
cp := Checkpoint{}
if err = dec.Decode(cp); err != nil {
return nil, err
}
return cp, nil
}
// NewService creates a new service, will bypass etcd registration if no
// endpoints specified.
func NewService(idx int, seconds int, path string, client *EtcdClient, cp Checkpoint) (*Service, error) {
// endpoints specified. It will recovery from checkpoint file if a exists a specified checkpoint.
func NewService(idx int, interval time.Duration, path string, client *EtcdClient, cp Checkpoint) (*Service, error) {
s := &Service{
idx: idx,
checkpointInterval: time.Second * time.Duration(seconds),
checkpointInterval: interval,
checkpointPath: path,
client: client,
}
......@@ -95,9 +131,11 @@ func NewService(idx int, seconds int, path string, client *EtcdClient, cp Checkp
if cp != nil {
for _, item := range cp {
p := item.ParamConfig
st := item.State
s.optMap[p.Param.Name] = newOptimizer(p, st)
p := ParameterWithConfig{
Param: item.Param,
Config: item.Config,
}
s.optMap[p.Param.Name] = newOptimizer(p, item.State)
}
}
return s, nil
......@@ -173,7 +211,7 @@ func (s *Service) GetParam(name string, parameter *Parameter) error {
// learning optimization methods are stochastic in
// nature. This race condition is allowed deliberately
// to save the program from making a copy of the
// paramter content.
// parameter content.
parameter.Name = name
parameter.ElementType = opt.elementType
parameter.Content = opt.GetWeights()
......@@ -181,56 +219,81 @@ func (s *Service) GetParam(name string, parameter *Parameter) error {
}
// pserver save checkpoint
func (s *Service) doCheckpoint() error {
func (s *Service) doCheckpoint() (err error) {
<-s.initialized
s.mu.Lock()
defer s.mu.Unlock()
cp := make([]ParameterCheckpoint, 0, len(s.optMap))
cp := make([]parameterCheckpoint, len(s.optMap))
index := 0
for name, opt := range s.optMap {
var pc ParameterCheckpoint
pc.ParamConfig.Param.Name = name
pc.ParamConfig.Param.ElementType = opt.elementType
pc.ParamConfig.Param.Content = opt.GetWeights()
var pc parameterCheckpoint
pc.Param.Name = name
pc.Param.ElementType = opt.elementType
pc.Param.Content = opt.GetWeights()
pc.State = opt.GetStates()
cp[index] = pc
index++
}
var buf bytes.Buffer
encoder := gob.NewEncoder(&buf)
err := encoder.Encode(cp)
err = encoder.Encode(cp)
if err != nil {
return err
return
}
cpMeta := checkpointMeta{}
cpMeta.UUID = s.checkpointPath + strconv.Itoa(s.idx)
cpMeta.Timestamp = time.Now().String()
cpMeta.Timestamp = time.Now().UnixNano()
h := md5.New()
cpMeta.Md5sum = hex.EncodeToString(h.Sum(buf.Bytes()))
cpMeta.MD5 = hex.EncodeToString(h.Sum(buf.Bytes()))
cpMetajson, err := json.Marshal(cpMeta)
if err != nil {
return
}
cpMetajson, _ := json.Marshal(cpMeta)
err = s.client.PutKey(filepath.Join(PsCheckpoint, strconv.Itoa(s.idx)), cpMetajson, 3)
err = s.client.PutKey(filepath.Join(PsCheckpoint, strconv.Itoa(s.idx)), cpMetajson, 3*time.Second)
if err != nil {
return err
return
}
if _, err = os.Stat(cpMeta.UUID); os.IsNotExist(err) {
log.Info("checkpoint does not exists.")
} else {
err = os.Remove(cpMeta.UUID)
log.Infof("checkpoint %s already exsits, removing ", cpMeta.UUID)
if err != nil {
log.Infof("Removing checkpoint %s failed", cpMeta.UUID)
} else {
log.Infof("checkpoint %s already exsits, removing ", cpMeta.UUID)
}
}
f, err := os.Create(cpMeta.UUID)
defer f.Close()
if err != nil {
return err
return
}
defer func() {
closeErr := f.Close()
if closeErr != nil {
if err != nil {
log.Errorln(closeErr)
} else {
// Set closeErr as return value.
err = closeErr
}
}
}()
writer := bufio.NewWriter(f)
_, err = writer.Write(buf.Bytes())
writer.Flush()
if err != nil {
return err
return
}
return nil
err = writer.Flush()
if err != nil {
return
}
return
}
go/pserver/service_test.go
浏览文件 @ 60a78893
......@@ -31,7 +31,7 @@ func TestServiceFull(t *testing.T) {
err = s.InitParam(pserver.ParameterWithConfig{Param: p, Config: config}, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
var p1 pserver.Parameter
......@@ -40,40 +40,40 @@ func TestServiceFull(t *testing.T) {
p1.ElementType = pserver.Float32
err = s.InitParam(pserver.ParameterWithConfig{Param: p1, Config: config}, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
err = s.FinishInitParams(0, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
var param pserver.Parameter
err = s.GetParam("param_b", &param)
if err != nil {
t.FailNow()
t.Fatal(err)
}
if !reflect.DeepEqual(param, p1) {
t.FailNow()
t.Fatal("not equal:", param, p1)
}
g1, g2 := pserver.Gradient(p1), pserver.Gradient(p)
err = s.SendGrad(g1, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
err = s.SendGrad(g2, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
var param1 pserver.Parameter
err = s.GetParam("param_a", &param1)
if err != nil {
t.FailNow()
t.Fatal(err)
}
// don't compare content, since it's already changed by
......@@ -82,7 +82,7 @@ func TestServiceFull(t *testing.T) {
p.Content = nil
if !reflect.DeepEqual(param1, p) {
t.FailNow()
t.Fatal("not equal:", param1, p)
}
}
......@@ -90,16 +90,16 @@ func TestMultipleInit(t *testing.T) {
var cp pserver.Checkpoint
s, err := pserver.NewService(0, 1, "", nil, cp)
if err != nil {
t.Error(err)
t.Fatal(err)
}
err = s.FinishInitParams(0, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
err = s.FinishInitParams(0, nil)
if err.Error() != pserver.AlreadyInitialized {
t.FailNow()
t.Fatal(err)
}
}
......@@ -108,7 +108,7 @@ func TestUninitialized(t *testing.T) {
s, err := pserver.NewService(0, 1, "", nil, cp)
err = s.SendGrad(pserver.Gradient{}, nil)
if err.Error() != pserver.Uninitialized {
t.FailNow()
t.Fatal(err)
}
}
......@@ -154,12 +154,12 @@ func TestBlockUntilInitialized(t *testing.T) {
err = s.InitParam(pserver.ParameterWithConfig{Param: p, Config: config}, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
err = s.FinishInitParams(0, nil)
if err != nil {
t.FailNow()
t.Fatal(err)
}
wg.Wait()
......
go/utils/networkhelper/CMakeLists.txt 0 → 100644
浏览文件 @ 60a78893
if(WITH_TESTING)
go_test(network_helper_test)
endif()
paddle/CMakeLists.txt
浏览文件 @ 60a78893
......@@ -8,13 +8,14 @@ add_subdirectory(gserver)
add_subdirectory(pserver)
add_subdirectory(trainer)
add_subdirectory(scripts)
add_subdirectory(optimizer)
add_subdirectory(string)
if(Boost_FOUND)
add_subdirectory(memory)
add_subdirectory(platform)
add_subdirectory(framework)
add_subdirectory(operators)
add_subdirectory(pybind)
endif()
if(WITH_C_API)
......
paddle/api/ConfigParser.cpp
浏览文件 @ 60a78893
......@@ -64,11 +64,7 @@ ModelConfig* TrainerConfig::getModelConfig() const {
ParameterConfig::ParameterConfig() : m(new ParameterConfigPrivate()) {}
ParameterConfig::~ParameterConfig() {
if (m) {
delete m;
}
}
ParameterConfig::~ParameterConfig() { delete m; }
ParameterConfig* ParameterConfig::createParameterConfigFromParameterSharedPtr(
void* ptr) {
......@@ -98,11 +94,7 @@ void* ParameterConfig::getRawPtr() { return m->getConfigPtr(); }
OptimizationConfig::OptimizationConfig() : m(new OptimizationConfigPrivate()) {}
OptimizationConfig::~OptimizationConfig() {
if (m) {
delete m;
}
}
OptimizationConfig::~OptimizationConfig() { delete m; }
std::string OptimizationConfig::toProtoString() {
return m->getConfig().SerializeAsString();
......
paddle/api/PaddleAPI.h
浏览文件 @ 60a78893
......@@ -843,7 +843,8 @@ public:
bool useSparseUpdater);
static ParameterUpdater* createNewRemoteUpdater(
OptimizationConfig* config,
const std::string pserverSpec) throw(UnsupportError);
const std::string pserverSpec,
const bool useEtcd) throw(UnsupportError);
~ParameterUpdater();
/**
......
paddle/api/ParameterOptimizer.cpp
浏览文件 @ 60a78893
......@@ -53,11 +53,7 @@ struct ParameterTraverseCallbackPrivate {
ParameterOptimizer::ParameterOptimizer() : m(new ParameterOptimizerPrivate()) {}
ParameterOptimizer::~ParameterOptimizer() {
if (m) {
delete m;
}
}
ParameterOptimizer::~ParameterOptimizer() { delete m; }
ParameterOptimizer* ParameterOptimizer::create(OptimizationConfig* config) {
CHECK(config != nullptr);
......@@ -104,11 +100,7 @@ std::vector<int> ParameterOptimizer::getParameterTypes() const {
ParameterTraverseCallback::ParameterTraverseCallback()
: m(new ParameterTraverseCallbackPrivate()) {}
ParameterTraverseCallback::~ParameterTraverseCallback() {
if (m) {
delete m;
}
}
ParameterTraverseCallback::~ParameterTraverseCallback() { delete m; }
void ParameterTraverseCallback::apply(const std::vector<Vector*>& vecs,
const ParameterConfig& conf,
......
paddle/api/ParameterUpdater.cpp
浏览文件 @ 60a78893
......@@ -33,11 +33,12 @@ ParameterUpdater *ParameterUpdater::createLocalUpdater(
ParameterUpdater *ParameterUpdater::createNewRemoteUpdater(
OptimizationConfig *config,
const std::string pserverSpec) throw(UnsupportError) {
const std::string pserverSpec,
const bool useEtcd) throw(UnsupportError) {
#ifndef PADDLE_WITHOUT_GOLANG
auto updater = new ParameterUpdater();
updater->m->updater.reset(new paddle::NewRemoteParameterUpdater(
config->m->getConfig(), pserverSpec));
config->m->getConfig(), pserverSpec, useEtcd));
return updater;
#else
throw UnsupportError();
......
paddle/api/Vector.cpp
浏览文件 @ 60a78893
......@@ -171,11 +171,7 @@ struct VectorPrivate {
Vector::Vector() : m(new VectorPrivate()) {}
Vector::~Vector() {
if (m) {
delete m;
}
}
Vector::~Vector() { delete m; }
Vector* Vector::createZero(size_t sz, bool useGpu) {
auto retVec = new Vector();
......
paddle/framework/CMakeLists.txt
浏览文件 @ 60a78893
# ddim lib
cc_library(ddim SRCS ddim.cc)
cc_library(enforce SRCS enforce.cc DEPS glog)
cc_test(enforce_test SRCS enforce_test.cc DEPS enforce)
cc_library(ddim SRCS ddim.cc DEPS eigen3)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
cc_test(tensor_test SRCS tensor_test.cc DEPS ddim)
cc_library(tensor SRCS tensor.cc DEPS ddim place enforce paddle_memory)
cc_test(tensor_test SRCS tensor_test.cc DEPS tensor)
cc_test(variable_test SRCS variable_test.cc)
cc_test(scope_test SRCS scope_test.cc)
cc_test(enforce_test SRCS enforce_test.cc)
proto_library(attr_type SRCS attr_type.proto)
proto_library(op_proto SRCS op_proto.proto DEPS attr_type)
cc_test(op_proto_test SRCS op_proto_test.cc DEPS op_proto protobuf)
proto_library(op_desc SRCS op_desc.proto DEPS attr_type)
cc_test(op_desc_test SRCS op_desc_test.cc DEPS op_desc protobuf)
cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_proto op_desc)
cc_library(operator SRCS operator.cc DEPS op_desc device_context tensor)
cc_test(operator_test SRCS operator_test.cc DEPS operator op_registry)
cc_library(op_registry SRCS op_registry.cc DEPS op_proto op_desc enforce)
cc_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry operator)
py_proto_compile(framework_py_proto SRCS attr_type.proto op_proto.proto op_desc.proto)
# Generate an empty __init__.py to make framework_py_proto as a valid python module.
add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
add_dependencies(framework_py_proto framework_py_proto_init)
proto_library(net_proto SRCS net_proto.proto DEPS op_proto)
cc_library(net SRCS net.cc DEPS operator net_proto op_registry)
cc_test(net_op_test SRCS net_op_test.cc DEPS net)
paddle/framework/ddim.cc
浏览文件 @ 60a78893
/* 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/ddim.h"
#include "paddle/framework/enforce.h"
namespace paddle {
namespace framework {
///@cond HIDDEN
/// @cond HIDDEN
template <int i>
Dim<i> make_dim(const int* d) {
......@@ -50,7 +65,7 @@ void make_ddim(DDim& ddim, const int* dims, int n) {
}
}
///@endcond
/// @endcond
DDim make_ddim(std::initializer_list<int> dims) {
DDim result(make_dim(0));
......@@ -64,11 +79,11 @@ DDim make_ddim(const std::vector<int>& dims) {
return result;
}
///@cond HIDDEN
/// @cond HIDDEN
// XXX For some reason, putting this in an anonymous namespace causes errors
class DynamicMutableIndexer : public boost::static_visitor<int&> {
public:
DynamicMutableIndexer(int idx) : idx_(idx) {}
explicit DynamicMutableIndexer(int idx) : idx_(idx) {}
template <int D>
int& operator()(Dim<D>& dim) const {
......@@ -81,7 +96,7 @@ class DynamicMutableIndexer : public boost::static_visitor<int&> {
class DynamicConstIndexer : public boost::static_visitor<int> {
public:
DynamicConstIndexer(int idx) : idx_(idx) {}
explicit DynamicConstIndexer(int idx) : idx_(idx) {}
template <int D>
int operator()(const Dim<D>& dim) const {
......@@ -92,7 +107,7 @@ class DynamicConstIndexer : public boost::static_visitor<int> {
int idx_;
};
///@endcond
/// @endcond
int& DDim::operator[](int idx) {
return boost::apply_visitor(DynamicMutableIndexer(idx), var);
......@@ -102,6 +117,8 @@ int DDim::operator[](int idx) const {
return boost::apply_visitor(DynamicConstIndexer(idx), var);
}
ssize_t DDim::size() const { return arity(*this); }
bool DDim::operator==(DDim d) const {
if (var.which() != d.getVar().which()) {
return false;
......@@ -155,11 +172,11 @@ int get(const DDim& ddim, int idx) { return ddim[idx]; }
void set(DDim& ddim, int idx, int value) { ddim[idx] = value; }
///@cond HIDDEN
/// @cond HIDDEN
struct VectorizeVisitor : public boost::static_visitor<> {
std::vector<int>& vector;
VectorizeVisitor(std::vector<int>& v) : vector(v) {}
explicit VectorizeVisitor(std::vector<int>& v) : vector(v) {}
template <typename T>
void operator()(const T& t) {
......@@ -169,7 +186,7 @@ struct VectorizeVisitor : public boost::static_visitor<> {
void operator()(const Dim<1>& t) { vector.push_back(t.head); }
};
///@endcond
/// @endcond
std::vector<int> vectorize(const DDim& ddim) {
std::vector<int> result;
......@@ -178,16 +195,59 @@ std::vector<int> vectorize(const DDim& ddim) {
return result;
}
struct ProductVisitor : public boost::static_visitor<ssize_t> {
template <int D>
ssize_t operator()(const Dim<D>& dim) {
return product(dim);
}
};
ssize_t product(const DDim& ddim) {
ssize_t result = 1;
std::vector<int> v = vectorize(ddim);
for (auto i : v) {
result *= i;
ProductVisitor visitor;
return boost::apply_visitor(visitor, ddim);
}
struct SliceVectorizeVisitor : public boost::static_visitor<> {
std::vector<int>& vector;
int begin;
int end;
SliceVectorizeVisitor(std::vector<int>& v, int b, int e)
: vector(v), begin(b), end(e) {
PADDLE_ENFORCE(begin < end,
"Begin index must be less than end index in ddim slice.");
PADDLE_ENFORCE(begin >= 0,
"Begin index can't be less than zero in ddim slice.");
}
return result;
template <int S>
void operator()(const Dim<S>& dim) {
if (begin == 0) {
vector.push_back(dim.head);
} else {
--begin;
}
--end;
if (end > 0) {
this->operator()(dim.tail);
}
}
void operator()(const Dim<1>& dim) {
PADDLE_ENFORCE(end == 1, "End index in ddim slice is out of bound.");
vector.push_back(dim.head);
}
};
DDim slice_ddim(const DDim& dim, int begin, int end) {
std::vector<int> vec;
vec.reserve(end - begin);
SliceVectorizeVisitor visitor(vec, begin, end);
boost::apply_visitor(visitor, dim);
return make_ddim(vec);
}
///\cond HIDDEN
/// \cond HIDDEN
struct ArityVisitor : boost::static_visitor<int> {
template <int D>
......@@ -196,15 +256,15 @@ struct ArityVisitor : boost::static_visitor<int> {
}
};
///\endcond
/// \endcond
int arity(const DDim& d) { return boost::apply_visitor(ArityVisitor(), d); }
///\cond HIDDEN
/// \cond HIDDEN
struct DDimPrinter : boost::static_visitor<void> {
std::ostream& os;
DDimPrinter(std::ostream& os_) : os(os_) {}
explicit DDimPrinter(std::ostream& os_) : os(os_) {}
template <typename T>
void operator()(const T& t) {
......@@ -212,7 +272,7 @@ struct DDimPrinter : boost::static_visitor<void> {
}
};
///\endcond
/// \endcond
std::ostream& operator<<(std::ostream& os, const DDim& ddim) {
DDimPrinter printer(os);
......@@ -220,5 +280,9 @@ std::ostream& operator<<(std::ostream& os, const DDim& ddim) {
return os;
}
DDim::DDim(std::initializer_list<int> init_list) {
*this = make_ddim(init_list);
}
} // namespace framework
} // namespace paddle
paddle/framework/ddim.h
浏览文件 @ 60a78893
/* 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 <initializer_list>
#include <stdexcept>
#include <vector>
#include "paddle/framework/dim.h"
#include "paddle/framework/enforce.h"
#include "unsupported/Eigen/CXX11/Tensor"
namespace paddle {
namespace framework {
......@@ -27,7 +42,9 @@ struct DDim {
DDim() : var(Dim<1>()) {}
template <int D>
DDim(const Dim<D>& in) : var(in) {}
explicit DDim(const Dim<D>& in) : var(in) {}
/*implicit*/ DDim(std::initializer_list<int> init_list);
template <int D>
DDim& operator=(const Dim<D>& in) {
......@@ -57,6 +74,8 @@ struct DDim {
DDim operator+(DDim d) const;
DDim operator*(DDim d) const;
ssize_t size() const;
};
/**
......@@ -81,6 +100,15 @@ std::vector<int> vectorize(const DDim& ddim);
ssize_t product(const DDim& ddim);
/**
* \brief Slice a ddim
*
* Slice dim with [begin, end).
* e.g. DDim d = make_ddim({1,2,3,4,5});
* slice_ddim(d, 1, 3); ====> {2,3}
*/
DDim slice_ddim(const DDim& dim, int begin, int end);
/**
* \brief What is the length of this dimension?
*
......@@ -91,6 +119,17 @@ int arity(const DDim& ddim);
std::ostream& operator<<(std::ostream&, const DDim&);
template <int NDIMS>
Eigen::DSizes<Eigen::DenseIndex, NDIMS> ToEigenDSizes(const DDim& dims) {
int rank = arity(dims);
PADDLE_ENFORCE(rank == NDIMS, "DDim and NDIMS must be same");
Eigen::DSizes<Eigen::DenseIndex, NDIMS> dsizes;
for (int d = 0; d < rank; d++) {
dsizes[d] = dims[d];
}
return dsizes;
}
} // namespace framework
} // namespace paddle
......
paddle/framework/ddim_test.cc
浏览文件 @ 60a78893
......@@ -49,9 +49,30 @@ TEST(DDim, Equality) {
// arity of a DDim
EXPECT_EQ(paddle::framework::arity(ddim), 3);
EXPECT_EQ(ddim.size(), 3);
// product of a DDim
EXPECT_EQ(paddle::framework::product(vddim), 45);
EXPECT_EQ(
paddle::framework::product(paddle::framework::make_ddim({3, 2, 5, 3})),
90);
// slice a DDim
paddle::framework::DDim ddim2 =
paddle::framework::make_ddim({1, 2, 3, 4, 5, 6});
paddle::framework::DDim ss = paddle::framework::slice_ddim(ddim2, 2, 5);
EXPECT_EQ(arity(ss), 3);
EXPECT_EQ(ss[0], 3);
EXPECT_EQ(ss[1], 4);
EXPECT_EQ(ss[2], 5);
paddle::framework::DDim ss2 = paddle::framework::slice_ddim(ddim2, 0, 6);
EXPECT_EQ(arity(ss2), 6);
EXPECT_EQ(ss2[0], 1);
EXPECT_EQ(ss2[1], 2);
EXPECT_EQ(ss2[2], 3);
EXPECT_EQ(ss2[3], 4);
EXPECT_EQ(ss2[4], 5);
EXPECT_EQ(ss2[5], 6);
}
TEST(DDim, Print) {
......
paddle/framework/dim.h
浏览文件 @ 60a78893
......@@ -266,29 +266,6 @@ HOSTDEVICE inline bool contained(const Dim<1>& idx, const Dim<1>& size) {
return ((0 <= idx.head) && (idx.head < size.head));
}
/**
* \brief Check if a size and a stride create a Fortran order contiguous
* block of memory.
*/
template <int i>
HOST bool contiguous(const Dim<i>& size, const Dim<i>& stride, int mul = 1) {
if (product(size) == 0) return true;
int contiguous_stride = get<0>(size) == 1 ? 0 : mul;
return (get<0>(stride) == contiguous_stride &&
contiguous(size.tail, stride.tail, mul * get<0>(size)));
}
///\cond HIDDEN
// Base case of contiguous, check the nth stride is the size of
// the prefix multiply of n-1 dims.
template <>
inline bool contiguous(const Dim<1>& size, const Dim<1>& stride, int mul) {
if (get<0>(size) == 0) return true;
int contiguous_stride = get<0>(size) == 1 ? 0 : mul;
return get<0>(stride) == contiguous_stride;
}
///\endcond
/**
* \brief Compute exclusive prefix-multiply of a Dim.
*/
......@@ -306,31 +283,6 @@ HOSTDEVICE inline Dim<1> ex_prefix_mul(const Dim<1>& src, int mul) {
}
///\endcond
/**
* \brief Calculate strides of a contiguous array of the given size
*
* Sets the stride for any dimension with an extent of 1 to 0.
* \param size Dim object containing the size of the array.
* \param base The base stride to use.
* \return Dim object the same size as \p size with the strides.
*/
template <int i>
HOSTDEVICE Dim<i> contiguous_strides(const Dim<i>& size, int base = 1) {
int stride = size.head == 1 ? 0 : base;
return Dim<i>(stride, contiguous_strides(size.tail, base * size.head));
}
///\cond HIDDEN
// Base case of contiguous_strides
template <>
HOSTDEVICE inline Dim<1> contiguous_strides(const Dim<1>& size, int base) {
int stride = size.head == 1 ? 0 : base;
return Dim<1>(stride);
}
///\endcond
/**
* Add two dimensions together
*/
......
paddle/framework/dim_test.cu
浏览文件 @ 60a78893
#include <thrust/device_vector.h>
#include <sstream>
#include "paddle/framework/dim.h"
#include "gtest/gtest.h"
#include "paddle/framework/dim.h"
__global__ void test(paddle::framework::Dim<2>* o) {
o[0] = paddle::framework::make_dim(5, 6);
o[0] = paddle::framework::make_dim(5, 6);
}
__global__ void dyn_idx_gpu(int* o) {
auto d = paddle::framework::make_dim(5, 6);
o[0] = d[1];
auto d = paddle::framework::make_dim(5, 6);
o[0] = d[1];
}
TEST(Dim, Equality) {
// construct a Dim on the CPU
auto a = paddle::framework::make_dim(3, 4);
EXPECT_EQ(paddle::framework::get<0>(a), 3);
EXPECT_EQ(paddle::framework::get<1>(a), 4);
// construct a Dim on the GPU
thrust::device_vector<paddle::framework::Dim<2>> t(2);
test<<<1,1>>>(thrust::raw_pointer_cast(t.data()));
a = t[0];
EXPECT_EQ(paddle::framework::get<0>(a), 5);
EXPECT_EQ(paddle::framework::get<1>(a), 6);
// linearization
auto b = paddle::framework::make_dim(7, 8);
EXPECT_EQ(paddle::framework::linearize(a, b), 83);
// product
EXPECT_EQ(paddle::framework::product(a), 30);
// mutate a Dim
paddle::framework::get<1>(b) = 10;
EXPECT_EQ(paddle::framework::get<0>(b), 7);
EXPECT_EQ(paddle::framework::get<1>(b), 10);
// dynamic access
paddle::framework::get(b, 0) = 8;
b[1] = 11;
EXPECT_EQ(paddle::framework::get<0>(b), 8);
EXPECT_EQ(paddle::framework::get<1>(b), 11);
EXPECT_EQ(paddle::framework::get(b, 0), 8);
EXPECT_EQ(b[1], 11);
// dynamic access on GPU
thrust::device_vector<int> r(1);
dyn_idx_gpu<<<1,1>>>(thrust::raw_pointer_cast(r.data()));
int res = r[0];
EXPECT_EQ(res, 6);
// ex_prefix_mul
paddle::framework::Dim<3> c = paddle::framework::ex_prefix_mul(paddle::framework::Dim<3>(3, 4, 5));
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 3);
EXPECT_EQ(paddle::framework::get<2>(c), 12);
// contiguous_strides
c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(10, 1, 10));
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 0);
EXPECT_EQ(paddle::framework::get<2>(c), 10);
c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(10, 10, 1));
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 10);
EXPECT_EQ(paddle::framework::get<2>(c), 0);
c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(1, 10, 10));
EXPECT_EQ(paddle::framework::get<0>(c), 0);
EXPECT_EQ(paddle::framework::get<1>(c), 1);
EXPECT_EQ(paddle::framework::get<2>(c), 10);
c = paddle::framework::contiguous_strides(paddle::framework::Dim<3>(2, 3, 4));
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 2);
EXPECT_EQ(paddle::framework::get<2>(c), 6);
// generate from an index
auto size = paddle::framework::make_dim(4, 5, 2);
c = paddle::framework::Dim<3>(14, size);
EXPECT_EQ(paddle::framework::get<0>(c), 2);
EXPECT_EQ(paddle::framework::get<1>(c), 3);
EXPECT_EQ(paddle::framework::get<2>(c), 0);
c = paddle::framework::Dim<3>(25, size);
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 1);
EXPECT_EQ(paddle::framework::get<2>(c), 1);
// construct a Dim on the CPU
auto a = paddle::framework::make_dim(3, 4);
EXPECT_EQ(paddle::framework::get<0>(a), 3);
EXPECT_EQ(paddle::framework::get<1>(a), 4);
// construct a Dim on the GPU
thrust::device_vector<paddle::framework::Dim<2>> t(2);
test<<<1, 1>>>(thrust::raw_pointer_cast(t.data()));
a = t[0];
EXPECT_EQ(paddle::framework::get<0>(a), 5);
EXPECT_EQ(paddle::framework::get<1>(a), 6);
// linearization
auto b = paddle::framework::make_dim(7, 8);
EXPECT_EQ(paddle::framework::linearize(a, b), 83);
// product
EXPECT_EQ(paddle::framework::product(a), 30);
// mutate a Dim
paddle::framework::get<1>(b) = 10;
EXPECT_EQ(paddle::framework::get<0>(b), 7);
EXPECT_EQ(paddle::framework::get<1>(b), 10);
// dynamic access
paddle::framework::get(b, 0) = 8;
b[1] = 11;
EXPECT_EQ(paddle::framework::get<0>(b), 8);
EXPECT_EQ(paddle::framework::get<1>(b), 11);
EXPECT_EQ(paddle::framework::get(b, 0), 8);
EXPECT_EQ(b[1], 11);
// dynamic access on GPU
thrust::device_vector<int> r(1);
dyn_idx_gpu<<<1, 1>>>(thrust::raw_pointer_cast(r.data()));
int res = r[0];
EXPECT_EQ(res, 6);
// ex_prefix_mul
paddle::framework::Dim<3> c =
paddle::framework::ex_prefix_mul(paddle::framework::Dim<3>(3, 4, 5));
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 3);
EXPECT_EQ(paddle::framework::get<2>(c), 12);
// generate from an index
auto size = paddle::framework::make_dim(4, 5, 2);
c = paddle::framework::Dim<3>(14, size);
EXPECT_EQ(paddle::framework::get<0>(c), 2);
EXPECT_EQ(paddle::framework::get<1>(c), 3);
EXPECT_EQ(paddle::framework::get<2>(c), 0);
c = paddle::framework::Dim<3>(25, size);
EXPECT_EQ(paddle::framework::get<0>(c), 1);
EXPECT_EQ(paddle::framework::get<1>(c), 1);
EXPECT_EQ(paddle::framework::get<2>(c), 1);
}
TEST(Dim, Bool) {
auto a = paddle::framework::make_dim(3, 4);
auto b = paddle::framework::make_dim(5, 6);
auto c = paddle::framework::make_dim(3, 4);
// in_bounds check
EXPECT_TRUE(paddle::framework::contained(a, b));
EXPECT_FALSE(paddle::framework::contained(b, a));
// comparison
EXPECT_TRUE(a == a);
EXPECT_FALSE(a == b);
EXPECT_TRUE(a == c);
// contiguous check
int x = 4, y = 5, z = 2;
paddle::framework::Dim<3> sizef(x, y, z);
paddle::framework::Dim<3> stridea(1, x, x*y);
paddle::framework::Dim<3> strideb(2, 2*x, 2*x*y);
paddle::framework::Dim<3> stridec(1, x, 2*x*y);
EXPECT_TRUE(paddle::framework::contiguous(sizef, stridea));
EXPECT_FALSE(paddle::framework::contiguous(sizef, strideb));
EXPECT_FALSE(paddle::framework::contiguous(sizef, stridec));
auto a = paddle::framework::make_dim(3, 4);
auto b = paddle::framework::make_dim(5, 6);
auto c = paddle::framework::make_dim(3, 4);
// in_bounds check
EXPECT_TRUE(paddle::framework::contained(a, b));
EXPECT_FALSE(paddle::framework::contained(b, a));
// comparison
EXPECT_TRUE(a == a);
EXPECT_FALSE(a == b);
EXPECT_TRUE(a == c);
}
TEST(Dim, Print) {
{
std::stringstream ss;
auto a = paddle::framework::make_dim(2, 3);
ss << a;
EXPECT_EQ(ss.str(), "2, 3");
}
{
std::stringstream ss;
ss << paddle::framework::make_dim(8);
EXPECT_EQ(ss.str(), "8");
}
{
std::stringstream ss;
auto a = paddle::framework::make_dim(2, 3);
ss << a;
EXPECT_EQ(ss.str(), "2, 3");
}
{
std::stringstream ss;
ss << paddle::framework::make_dim(8);
EXPECT_EQ(ss.str(), "8");
}
}
paddle/framework/enforce.cc 0 → 100644
浏览文件 @ 60a78893
/* 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/enforce.h"
paddle/framework/enforce.h
浏览文件 @ 60a78893
......@@ -10,6 +10,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <glog/logging.h>
#include <paddle/string/printf.h>
#include <exception>
#include <sstream>
......@@ -58,12 +59,17 @@ class EnforceNotMet : public std::exception {
/**
* @brief Enforce a condition, otherwise throw an EnforceNotMet
*/
#ifdef NDEBUG
#define PADDLE_ENFORCE(condition, ...) \
do { \
if (UNLIKELY(!(condition))) { \
PADDLE_THROW(__VA_ARGS__); \
} \
} while (0)
#else
#define PADDLE_ENFORCE(condition, ...) \
CHECK(condition) << ::paddle::string::Sprintf(__VA_ARGS__);
#endif
} // namespace framework
} // namespace paddle
paddle/framework/net.cc 0 → 100644
浏览文件 @ 60a78893
/*
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/net.h"
namespace paddle {
namespace framework {
void PlainNet::CompleteAddOp() {
std::unordered_set<std::string> input_set;
std::unordered_set<std::string> output_set;
std::unordered_set<std::string> temp_output;
for (auto& op : ops_) {
for (auto& ipt : op->inputs_) {
if (!Contains(output_set, ipt)) { // Not other op's output
input_set.insert(ipt);
} else {
temp_output.insert(ipt);
}
}
for (auto& opt : op->outputs_) {
output_set.insert(opt);
}
}
inputs_.reserve(input_set.size());
std::copy(input_set.begin(), input_set.end(), std::back_inserter(inputs_));
outputs_.reserve(output_set.size());
std::vector<int> tmp_index;
tmp_index.reserve(temp_output.size());
int idx = 0;
for (auto& opt : output_set) {
if (Contains(temp_output, opt)) {
tmp_index.push_back(idx);
}
outputs_.push_back(opt);
++idx;
}
attrs_["temporary_index"] = tmp_index;
add_op_done_ = true;
}
std::string PlainNet::DebugString() const {
std::ostringstream os;
os << this->type_ << ":" << std::endl;
for (auto& op : ops_) {
os << "\t" << op->DebugString() << std::endl;
}
return os.str();
}
} // namespace framework
} // namespace paddle
paddle/framework/net.h 0 → 100644
浏览文件 @ 60a78893
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <paddle/framework/op_desc.pb.h>
#include <paddle/framework/operator.h>
#include "paddle/framework/net_proto.pb.h"
#include "paddle/framework/op_proto.pb.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/scope.h"
#include "paddle/platform/device_context.h"
namespace paddle {
namespace framework {
/**
* @brief Network is also a type of Operator
*
* It will manage the operators it has.
*
* Network is the container and controller of a set of operators.
* A network object knows all Operators belonging to this network. Variables,
* which are inputs and outputs of these operators, are created and managed by a
* hierarchy of Scope objects.
*
* This is the base class of network, all the networks should implement the APIs
* it defines.
*/
class Net : public OperatorBase {
public:
virtual void AddOp(const OperatorPtr& op) = 0;
virtual void CompleteAddOp() = 0;
};
using NetPtr = std::shared_ptr<Net>;
/**
* @brief a basic implementation of Net.
*
* PlainNet is a very simple Net, it create a list of operators, and run them
* sequentially following the order they added.
*/
class PlainNet : public Net {
public:
/**
* Infer all the operators' input and output variables' shapes, will be called
* before every mini-batch
*/
void InferShape(const ScopePtr& scope) const override {
for (auto& op : ops_) {
op->InferShape(scope);
}
}
/**
* @brief Run the network.
*
* Run all the operators with the `scope`, if no scope is provided, default
* scope will be used instead. If no OpContext is provicded, default context
* will be used.
*/
void Run(const ScopePtr& scope,
const platform::DeviceContext& dev_ctx) const override {
for (auto& op : ops_) {
op->Run(scope, dev_ctx);
}
}
/**
* @brief Add an operator by ptr
*/
void AddOp(const OperatorPtr& op) override {
PADDLE_ENFORCE(!add_op_done_, "Cannot AddOp when this network is sealed");
ops_.push_back(op);
}
void CompleteAddOp() override;
std::string DebugString() const override;
std::vector<OperatorPtr> ops_;
private:
bool add_op_done_{false};
template <typename T, typename KeyType>
static bool Contains(T container, KeyType key) {
return container.find(key) != container.end();
}
};
} // namespace framework
} // namespace paddle
paddle/framework/net_op_test.cc 0 → 100644
浏览文件 @ 60a78893
#include <gtest/gtest.h>
#include <paddle/framework/net.h>
#include <paddle/framework/op_registry.h>
#include <paddle/framework/operator.h>
namespace pd = paddle::framework;
static int infer_shape_cnt = 0;
static int run_cnt = 0;
class TestOp : public pd::OperatorBase {
public:
void InferShape(const paddle::framework::ScopePtr& scope) const override {
++infer_shape_cnt;
}
void Run(const paddle::framework::ScopePtr& scope,
const paddle::platform::DeviceContext& dev_ctx) const override {
++run_cnt;
}
};
template <typename T>
void AssertSameVectorWithoutOrder(const std::vector<T>& expected,
const std::vector<T>& actual) {
ASSERT_EQ(expected.size(), actual.size());
std::unordered_set<T> expected_set;
for (auto& tmp : expected) {
expected_set.insert(tmp);
}
for (auto& act : actual) {
ASSERT_NE(expected_set.end(), expected_set.find(act));
}
}
TEST(OpKernel, all) {
auto net = std::make_shared<paddle::framework::PlainNet>();
ASSERT_NE(net, nullptr);
auto op1 = std::make_shared<TestOp>();
op1->inputs_ = {"x", "w1", "b1"};
op1->outputs_ = {"y"};
net->AddOp(op1);
auto op2 = std::make_shared<TestOp>();
op2->inputs_ = {"y", "w2", "b2"};
op2->outputs_ = {"z"};
net->AddOp(op2);
net->CompleteAddOp();
AssertSameVectorWithoutOrder({"x", "w1", "b1", "w2", "b2"}, net->inputs_);
AssertSameVectorWithoutOrder({"y", "z"}, net->outputs_);
auto tmp_idx_iter = net->attrs_.find("temporary_index");
ASSERT_NE(net->attrs_.end(), tmp_idx_iter);
auto& tmp_idx = boost::get<std::vector<int>>(tmp_idx_iter->second);
ASSERT_EQ(1UL, tmp_idx.size());
ASSERT_EQ("y", net->outputs_[tmp_idx[0]]);
auto scope = std::make_shared<pd::Scope>();
paddle::platform::CPUDeviceContext dev_ctx;
net->InferShape(scope);
net->Run(scope, dev_ctx);
ASSERT_EQ(2, infer_shape_cnt);
ASSERT_EQ(2, run_cnt);
ASSERT_THROW(net->AddOp(op2), paddle::framework::EnforceNotMet);
}
paddle/framework/net_proto.proto 0 → 100644
浏览文件 @ 60a78893
syntax="proto2";
package paddle.framework;
import "op_proto.proto";
message NetDesc {
// network identification
optional string name = 1;
// operator contains in network
repeated OpProto operators = 2;
// network type to run with. e.g "plainNet", "DAG"
optional string net_type = 3;
// num worker always
optional int32 num_workers = 4;
}
paddle/framework/net_test.cc 0 → 100644
浏览文件 @ 60a78893
/* 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/net.h"
#include "paddle/framework/op_registry.h"
#include <gtest/gtest.h>
namespace paddle {
namespace framework {
class FakeFC : public Operator {}
} // namespace framework
} // namespace paddle
paddle/framework/op_proto.proto
浏览文件 @ 60a78893
......@@ -34,6 +34,11 @@ message AttrProto {
// Supported attribute comments. It helps 3rd-party language generate doc-string.
required string comment = 3;
// If that attribute is generated, it means the Paddle third language
// binding has responsibility to fill that attribute. End-User should
// not set that attribute.
optional bool generated = 4 [default=false];
}
// Input or output message for 3rd-party language binding.
......@@ -45,6 +50,40 @@ message VarProto {
// The comment for that input. It helps 3rd-party language generate doc-string.
required string comment = 2;
// Is that input/output could be a list or not.
// If so, that Op should write a attributed named `input_format` or
// `output_format`.
//
// e.g.
// If the op is a fc op, the inputs are `X`, `W`, `b`. The `X` and `W`
// could be multiple, so the multiple of `X` and `W` is True, and OpDesc
// will hold a attribute of them.
//
// The Op desc of same fc could be
// {
// "type": "fc",
// "input": ["X1", "X2", "W1", "W2", "b"],
// "output": "fc.out",
// "attrs" : {
// "input_format": [0, 2, 4, 5]
// }
// }
//
optional bool multiple = 3 [default=false];
// It marks that output is a temporary output. That output is not used by
// user, but used by other op internally as input. If other op is not use
// that output, it could be optimized early.
//
// Attribute temporary_index will be set in OpDesc if there is some
// outputs are temporary.
//
// output = [ "xxx.out1", "xxx.tmp", "xxx.out2"],
// attrs = {
// "temporary_index": [1]
// }
optional bool temporary = 4 [default=false];
}
// Op protocol message for 3rd-party language binding.
......
paddle/framework/op_registry.cc 0 → 100644
浏览文件 @ 60a78893
/* 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/op_registry.h>
namespace paddle {
namespace framework {
template <>
void AttrTypeHelper::SetAttrType<int>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::INT);
}
template <>
void AttrTypeHelper::SetAttrType<float>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::FLOAT);
}
template <>
void AttrTypeHelper::SetAttrType<std::string>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::STRING);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<int>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::INTS);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<float>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::FLOATS);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<std::string>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::STRINGS);
}
} // namespace framework
} // namespace paddle
paddle/framework/op_registry.h
浏览文件 @ 60a78893
#pragma once
#include <algorithm>
#include <atomic>
#include <type_traits>
#include <unordered_map>
#include <unordered_set>
#include "paddle/framework/attr_checker.h"
//#include "paddle/framework/op_base.h"
#include "paddle/framework/op_desc.pb.h"
#include "paddle/framework/op_proto.pb.h"
#include "paddle/framework/operator.h"
namespace paddle {
namespace framework {
//==================For test================//
class OpBase {
public:
std::vector<std::string> inputs_;
std::vector<std::string> outputs_;
AttributeMap attr_map_;
virtual std::string Run() const = 0;
virtual ~OpBase() {}
};
//=========================================//
// helper class to set attribute type
struct AttrTypeHelper {
template <typename T>
......@@ -64,190 +56,344 @@ struct AttrTypeHelper {
}
};
template <>
void AttrTypeHelper::SetAttrType<int>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::INT);
}
template <>
void AttrTypeHelper::SetAttrType<float>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::FLOAT);
}
template <>
void AttrTypeHelper::SetAttrType<std::string>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::STRING);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<int>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::INTS);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<float>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::FLOATS);
}
template <>
void AttrTypeHelper::SetAttrType<std::vector<std::string>>(AttrProto* attr) {
attr->set_type(paddle::framework::AttrType::STRINGS);
}
// this class not only make proto but also init attribute checkers.
class OpProtoAndCheckerMaker {
public:
OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: proto_(proto), op_checker_(op_checker) {}
~OpProtoAndCheckerMaker() {
PADDLE_ENFORCE(validated_, "should call Validate after build");
}
void Validate() {
validated_ = true;
CheckNoDuplicatedInOutAttrs();
}
protected:
void AddInput(const std::string& name, const std::string& comment) {
void AddInput(const std::string& name, const std::string& comment,
bool multiple = false) {
auto input = proto_->mutable_inputs()->Add();
*(input->mutable_name()) = name;
*(input->mutable_comment()) = comment;
*input->mutable_name() = name;
*input->mutable_comment() = comment;
input->set_multiple(multiple);
if (multiple) {
SetHasMultipleInput();
}
}
void AddInputs(const std::string& name, const std::string& comment) {
AddInput(name, comment, true);
}
void AddOutput(const std::string& name, const std::string& comment) {
void AddOutput(const std::string& name, const std::string& comment,
bool temporary = false, bool multiple = false) {
auto output = proto_->mutable_outputs()->Add();
*(output->mutable_name()) = name;
*(output->mutable_comment()) = comment;
*output->mutable_name() = name;
*output->mutable_comment() = comment;
output->set_multiple(multiple);
if (multiple) {
SetHasMultipleOutput();
}
output->set_temporary(temporary);
if (temporary) {
SetHasTemporaryOutput();
}
}
void AddOutputs(const std::string& name, const std::string& comment,
bool temporary = false) {
AddOutput(name, comment, temporary, true);
}
template <typename T>
TypedAttrChecker<T>& AddAttr(const std::string& name,
const std::string& comment) {
const std::string& comment,
bool generated = false) {
auto attr = proto_->mutable_attrs()->Add();
*(attr->mutable_name()) = name;
*(attr->mutable_comment()) = comment;
*attr->mutable_name() = name;
*attr->mutable_comment() = comment;
attr->set_generated(generated);
AttrTypeHelper::SetAttrType<T>(attr);
return op_checker_->AddAttrChecker<T>(name);
}
void AddType(const std::string& op_type) { proto_->set_type(op_type); }
void AddComment(const std::string& comment) {
*(proto_->mutable_comment()) = comment;
}
private:
void SetHasMultiple(const std::string& in_out, bool* flag) {
if (!*flag) {
AddAttr<std::vector<int>>(in_out + "_format",
"The multiple index of " + in_out +
"\n"
R"DOC(
This attribute is used by Paddle core framework. Paddle's Op support each input
or output could be a list of variable. This attribute is used to show how that
list organized.
e.g.
input = ["a", "b", "c", "d", "e", "f"]
input_format = [0, 4, 5, 6]
means
The number of all input variables this op is six, and they are segmented into
three inputs.
The first input is input[0:4], second is input[4:5], third is input[5:6].
)DOC",
/*generated*/ true);
*flag = true;
}
}
void SetHasMultipleInput() { SetHasMultiple("input", &has_multiple_input_); }
void SetHasMultipleOutput() {
SetHasMultiple("output", &has_multiple_output_);
}
void SetHasTemporaryOutput() {
if (!has_temporary_output_) {
AddAttr<std::vector<int>>("temporary_index",
R"DOC(The temporary index of output.
Not all output of Paddle Op is used by user. For faster computation, each op
could output some its internal state to other op, other op could take that
output to make compute faster.
Add a mark to which output is temporary is helpful for future optimization.
)DOC",
/*generated*/ true)
.SetDefault(std::vector<int>());
has_temporary_output_ = true;
}
}
void CheckNoDuplicatedInOutAttrs() {
std::unordered_set<std::string> names;
auto checker = [&](const std::string& name) {
PADDLE_ENFORCE(!names.count(name), "[%s] is duplicated", name);
names.insert(name);
};
for (auto& attr : proto_->attrs()) {
checker(attr.name());
}
for (auto& input : proto_->inputs()) {
checker(input.name());
}
for (auto& output : proto_->outputs()) {
checker(output.name());
}
}
OpProto* proto_;
OpAttrChecker* op_checker_;
bool validated_{false};
bool has_multiple_input_{false};
bool has_multiple_output_{false};
bool has_temporary_output_{false};
};
class OpRegistry {
typedef std::function<OpBase*()> OpCreator;
using OpCreator = std::function<OperatorBase*()>;
using VarIndexMap = std::unordered_map<std::string, int>;
using VarNameList = std::vector<std::string>;
public:
template <typename OpType, typename ProtoMakerType>
static void RegisterOp(const std::string& op_type) {
creators_[op_type] = []() { return new OpType; };
OpProto& op_proto = protos_[op_type];
OpAttrChecker& op_checker = op_checkers_[op_type];
ProtoMakerType(&op_proto, &op_checker);
PADDLE_ENFORCE(op_proto.IsInitialized() == true,
"Fail to initialize %s's OpProto !", op_type);
}
static OpBase* CreateOp(const OpDesc& op_desc) {
std::string op_type = op_desc.type();
OpBase* op = (creators_.at(op_type))();
(op->inputs_).resize(op_desc.inputs_size());
for (int i = 0; i < op_desc.inputs_size(); ++i) {
(op->inputs_)[i] = op_desc.inputs(i);
}
(op->outputs_).resize(op_desc.outputs_size());
for (int i = 0; i < op_desc.outputs_size(); ++i) {
(op->outputs_)[i] = op_desc.outputs(i);
creators()[op_type] = [] { return new OpType; };
OpProto& op_proto = protos()[op_type];
OpAttrChecker& op_checker = op_checkers()[op_type];
auto maker = ProtoMakerType(&op_proto, &op_checker);
maker.Validate();
*op_proto.mutable_type() = op_type;
PADDLE_ENFORCE(
op_proto.IsInitialized(),
"Fail to initialize %s's OpProto, because %s is not initialized",
op_type, op_proto.InitializationErrorString());
VarIndexMaps()[op_type].reset(new VarIndexMap());
auto& varmap = *VarIndexMaps()[op_type];
int idx = 0;
for (auto& var : op_proto.inputs()) {
varmap[var.name()] = idx++;
}
for (int i = 0; i < op_desc.attrs_size(); ++i) {
const AttrDesc& ith_attr = op_desc.attrs(i);
std::string name = ith_attr.name();
(op->attr_map_)[name] = AttrTypeHelper::GetAttrValue(ith_attr);
idx = 0;
for (auto& var : op_proto.outputs()) {
varmap[var.name()] = idx++;
}
const OpAttrChecker& op_checker = op_checkers_.at(op_type);
op_checker.Check(op->attr_map_);
return op;
}
private:
static std::unordered_map<std::string, OpCreator> creators_;
static std::unordered_map<std::string, OpProto> protos_;
static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
};
std::unordered_map<std::string, std::function<OpBase*()>> OpRegistry::creators_;
std::unordered_map<std::string, OpProto> OpRegistry::protos_;
std::unordered_map<std::string, OpAttrChecker> OpRegistry::op_checkers_;
static OperatorPtr CreateOp(const std::string& type,
const VarNameList& inputs,
const VarNameList& outputs,
const AttributeMap& attrs) {
auto op_create_it = creators().find(type);
PADDLE_ENFORCE(op_create_it != creators().end(),
"Operator %s cannot be found", type);
auto op = op_create_it->second();
op->type_ = type;
op->inputs_ = inputs;
op->outputs_ = outputs;
op->attrs_ = attrs;
op_checkers().at(type).Check(op->attrs_);
GenerateTempVariableName(op);
{
auto var_index_it = VarIndexMaps().find(type);
if (var_index_it != VarIndexMaps().end()) {
op->in_out_idxs_ = var_index_it->second;
}
}
template <typename OpType, typename ProtoMakerType>
class OpRegisterHelper {
public:
OpRegisterHelper(std::string op_type) {
OpRegistry::RegisterOp<OpType, ProtoMakerType>(op_type);
op->Init();
return OperatorPtr(op);
}
};
#define REGISTER_OP(__op_class, __op_maker_class, __op_type) \
class __op_class##Register { \
private: \
const static OpRegisterHelper<__op_class, __op_maker_class> reg; \
}; \
const OpRegisterHelper<__op_class, __op_maker_class> \
__op_class##Register::reg(#__op_type);
static OperatorPtr CreateOp(const OpDesc& op_desc) {
std::vector<std::string> inputs;
inputs.reserve((size_t)op_desc.inputs_size());
std::copy(op_desc.inputs().begin(), op_desc.inputs().end(),
std::back_inserter(inputs));
// Demos
std::vector<std::string> outputs;
outputs.reserve((size_t)op_desc.outputs_size());
std::copy(op_desc.outputs().begin(), op_desc.outputs().end(),
std::back_inserter(outputs));
class CosineOp : public OpBase {
public:
virtual std::string Run() const {
std::string msg = "CosineOp runs! scale = " +
std::to_string(boost::get<float>(attr_map_.at("scale")));
return msg;
AttributeMap attrs;
for (auto& attr : op_desc.attrs()) {
attrs[attr.name()] = AttrTypeHelper::GetAttrValue(attr);
}
return CreateOp(op_desc.type(), inputs, outputs, attrs);
}
};
class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
AddAttr<float>("scale", "scale of cosine op")
.SetDefault(1.0)
.LargerThan(0.0);
AddType("cos");
AddComment("This is cos op");
static std::unordered_map<std::string, OpProto>& protos() {
static std::unordered_map<std::string, OpProto> protos_;
return protos_;
};
private:
static std::unordered_map<std::string, std::shared_ptr<VarIndexMap>>&
VarIndexMaps() {
static std::unordered_map<std::string, std::shared_ptr<VarIndexMap>> maps_;
return maps_;
}
};
REGISTER_OP(CosineOp, CosineOpProtoAndCheckerMaker, cos_sim)
static void GenerateTempVariableName(OperatorBase* op) {
static std::atomic<size_t> gUniqId(0UL);
for (auto& outname : op->outputs_) {
if (outname == OperatorBase::TMP_VAR_NAME()) {
outname += op->type_;
outname += "@";
outname += std::to_string(gUniqId.fetch_add(1));
}
}
}
class MyTestOp : public OpBase {
public:
virtual std::string Run() const {
std::string msg =
"MyTestOp runs! test_attr = " +
std::to_string(boost::get<int>(attr_map_.at("test_attr")));
return msg;
static std::unordered_map<std::string, OpCreator>& creators() {
static std::unordered_map<std::string, OpCreator> creators_;
return creators_;
}
static std::unordered_map<std::string, OpAttrChecker>& op_checkers() {
static std::unordered_map<std::string, OpAttrChecker> op_checkers_;
return op_checkers_;
};
};
class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
template <typename OpType, typename ProtoMakerType>
class OpRegisterHelper {
public:
MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
auto my_checker = [](int i) {
PADDLE_ENFORCE(i % 2 == 0, "'test_attr' must be even!");
};
AddAttr<int>("test_attr", "a simple test attribute")
.AddCustomChecker(my_checker);
AddType("my_test_op");
AddComment("This is my_test op");
OpRegisterHelper(const char* op_type) {
OpRegistry::RegisterOp<OpType, ProtoMakerType>(op_type);
}
};
REGISTER_OP(MyTestOp, MyTestOpProtoAndCheckerMaker, my_test_op)
/**
* check if MACRO is used in GLOBAL NAMESPACE.
*/
#define STATIC_ASSERT_GLOBAL_NAMESPACE(uniq_name, msg) \
struct __test_global_namespace_##uniq_name##__ {}; \
static_assert(std::is_same<::__test_global_namespace_##uniq_name##__, \
__test_global_namespace_##uniq_name##__>::value, \
msg)
/**
* Macro to Register Operator.
*/
#define REGISTER_OP(__op_type, __op_class, __op_maker_class) \
STATIC_ASSERT_GLOBAL_NAMESPACE(__reg_op__##__op_type, \
"REGISTER_OP must be in global namespace"); \
static ::paddle::framework::OpRegisterHelper<__op_class, __op_maker_class> \
__op_register_##__op_type##__(#__op_type); \
int __op_register_##__op_type##_handle__() { return 0; }
/**
* Macro to Register OperatorKernel.
*/
#define REGISTER_OP_KERNEL(type, DEVICE_TYPE, PlaceType, ...) \
STATIC_ASSERT_GLOBAL_NAMESPACE( \
__reg_op_kernel_##type##_##DEVICE_TYPE##__, \
"REGISTER_OP_KERNEL must be in global namespace"); \
struct __op_kernel_register__##type##__ { \
__op_kernel_register__##type##__() { \
::paddle::framework::OperatorWithKernel::OpKernelKey key; \
key.place_ = PlaceType(); \
::paddle::framework::OperatorWithKernel::AllOpKernels()[#type][key] \
.reset(new __VA_ARGS__()); \
} \
}; \
static __op_kernel_register__##type##__ __reg_kernel_##type##__; \
int __op_kernel_register_##type##_handle_##DEVICE_TYPE##__() { return 0; }
// (type, KernelType)
#define REGISTER_OP_GPU_KERNEL(type, ...) \
REGISTER_OP_KERNEL(type, GPU, ::paddle::platform::GPUPlace, __VA_ARGS__)
// (type, KernelType)
#define REGISTER_OP_CPU_KERNEL(type, ...) \
REGISTER_OP_KERNEL(type, CPU, ::paddle::platform::CPUPlace, __VA_ARGS__)
/**
* Macro to mark what Operator and Kernel we will use and tell the compiler to
* link them into target.
*/
#define USE_OP_WITHOUT_KERNEL(op_type) \
STATIC_ASSERT_GLOBAL_NAMESPACE( \
__use_op_without_kernel_##op_type, \
"USE_OP_WITHOUT_KERNEL must be in global namespace"); \
extern int __op_register_##op_type##_handle__(); \
static int __use_op_ptr_##op_type##_without_kernel__ \
__attribute__((unused)) = __op_register_##op_type##_handle__()
#define USE_OP_KERNEL(op_type, DEVICE_TYPE) \
STATIC_ASSERT_GLOBAL_NAMESPACE( \
__use_op_kernel_##op_type##_##DEVICE_TYPE##__, \
"USE_OP_KERNEL must be in global namespace"); \
extern int __op_kernel_register_##op_type##_handle_##DEVICE_TYPE##__(); \
static int __use_op_ptr_##op_type##_##DEVICE_TYPE##_kernel__ \
__attribute__((unused)) = \
__op_kernel_register_##op_type##_handle_##DEVICE_TYPE##__()
// use Operator with only cpu kernel.
#define USE_OP_CPU(op_type) \
USE_OP_WITHOUT_KERNEL(op_type); \
USE_OP_KERNEL(op_type, CPU)
#ifdef PADDLE_ONLY_CPU
#define USE_OP(op_type) USE_OP_CPU(op_type)
#else
#define USE_OP(op_type) \
USE_OP_CPU(op_type); \
USE_OP_KERNEL(op_type, GPU)
#endif
} // namespace framework
} // namespace paddle
paddle/framework/op_registry_test.cc
浏览文件 @ 60a78893
#include "paddle/framework/op_registry.h"
#include <gtest/gtest.h>
namespace pd = paddle::framework;
namespace paddle {
namespace framework {
class CosineOp : public OperatorBase {
public:
void Run(const ScopePtr& scope,
const platform::DeviceContext& dev_ctx) const override {}
void InferShape(const ScopePtr& scope) const override {}
};
class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
AddAttr<float>("scale", "scale of cosine op")
.SetDefault(1.0)
.LargerThan(0.0);
AddComment("This is cos op");
}
};
class MyTestOp : public OperatorBase {
public:
void InferShape(const ScopePtr& scope) const override {}
void Run(const ScopePtr& scope,
const platform::DeviceContext& dev_ctx) const override {}
};
class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInputs("input", "input of cosine op");
AddOutput("output", "output of cosine op",
/*temporary*/ true);
auto my_checker = [](int i) {
PADDLE_ENFORCE(i % 2 == 0, "'test_attr' must be even!");
};
AddAttr<int>("test_attr", "a simple test attribute")
.AddCustomChecker(my_checker);
AddComment("This is my_test op");
}
};
} // namespace framework
} // namespace paddle
REGISTER_OP(cos_sim, paddle::framework::CosineOp,
paddle::framework::CosineOpProtoAndCheckerMaker);
REGISTER_OP(my_test_op, paddle::framework::MyTestOp,
paddle::framework::MyTestOpProtoAndCheckerMaker);
TEST(OpRegistry, CreateOp) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("cos_sim");
op_desc.add_inputs("aa");
op_desc.add_outputs("bb");
float scale = 3.3;
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("scale");
attr->set_type(paddle::framework::AttrType::FLOAT);
attr->set_f(3.3);
attr->set_f(scale);
paddle::framework::OpBase* op =
paddle::framework::OperatorPtr op =
paddle::framework::OpRegistry::CreateOp(op_desc);
std::string debug_str = op->Run();
std::string str = "CosineOp runs! scale = " + std::to_string(3.3);
ASSERT_EQ(str.size(), debug_str.size());
for (size_t i = 0; i < debug_str.length(); ++i) {
ASSERT_EQ(debug_str[i], str[i]);
}
auto scope = std::make_shared<paddle::framework::Scope>();
paddle::platform::CPUDeviceContext dev_ctx;
op->Run(scope, dev_ctx);
float scale_get = op->GetAttr<float>("scale");
ASSERT_EQ(scale_get, scale);
}
TEST(OpRegistry, IllegalAttr) {
......@@ -35,7 +89,7 @@ TEST(OpRegistry, IllegalAttr) {
bool caught = false;
try {
paddle::framework::OpBase* op __attribute__((unused)) =
paddle::framework::OperatorPtr op __attribute__((unused)) =
paddle::framework::OpRegistry::CreateOp(op_desc);
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
......@@ -54,15 +108,22 @@ TEST(OpRegistry, DefaultValue) {
op_desc.add_inputs("aa");
op_desc.add_outputs("bb");
paddle::framework::OpBase* op =
ASSERT_TRUE(op_desc.IsInitialized());
paddle::framework::OperatorPtr op =
paddle::framework::OpRegistry::CreateOp(op_desc);
std::string debug_str = op->Run();
float default_value = 1.0;
std::string str = "CosineOp runs! scale = " + std::to_string(default_value);
ASSERT_EQ(str.size(), debug_str.size());
for (size_t i = 0; i < debug_str.length(); ++i) {
ASSERT_EQ(debug_str[i], str[i]);
}
auto scope = std::make_shared<paddle::framework::Scope>();
paddle::platform::CPUDeviceContext dev_ctx;
op->Run(scope, dev_ctx);
ASSERT_EQ(op->GetAttr<float>("scale"), 1.0);
}
static void SetInputFormat(paddle::framework::OpDesc* desc) {
auto attr = desc->add_attrs();
attr->set_name("input_format");
attr->set_type(paddle::framework::INTS);
attr->mutable_ints()->Add(0);
attr->mutable_ints()->Add(1);
}
TEST(OpRegistry, CustomChecker) {
......@@ -70,11 +131,12 @@ TEST(OpRegistry, CustomChecker) {
op_desc.set_type("my_test_op");
op_desc.add_inputs("ii");
op_desc.add_outputs("oo");
SetInputFormat(&op_desc);
// attr 'test_attr' is not set
bool caught = false;
try {
paddle::framework::OpBase* op __attribute__((unused)) =
paddle::framework::OperatorPtr op __attribute__((unused)) =
paddle::framework::OpRegistry::CreateOp(op_desc);
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
......@@ -93,7 +155,7 @@ TEST(OpRegistry, CustomChecker) {
attr->set_i(3);
caught = false;
try {
paddle::framework::OpBase* op __attribute__((unused)) =
paddle::framework::OperatorPtr op __attribute__((unused)) =
paddle::framework::OpRegistry::CreateOp(op_desc);
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
......@@ -111,12 +173,44 @@ TEST(OpRegistry, CustomChecker) {
attr->set_name("test_attr");
attr->set_type(paddle::framework::AttrType::INT);
attr->set_i(4);
paddle::framework::OpBase* op =
SetInputFormat(&op_desc);
paddle::framework::OperatorPtr op =
paddle::framework::OpRegistry::CreateOp(op_desc);
std::string debug_str = op->Run();
std::string str = "MyTestOp runs! test_attr = " + std::to_string(4);
ASSERT_EQ(str.size(), debug_str.size());
for (size_t i = 0; i < debug_str.length(); ++i) {
ASSERT_EQ(debug_str[i], str[i]);
paddle::platform::CPUDeviceContext dev_ctx;
auto scope = std::make_shared<paddle::framework::Scope>();
op->Run(scope, dev_ctx);
int test_attr = op->GetAttr<int>("test_attr");
ASSERT_EQ(test_attr, 4);
}
class TestAttrProtoMaker : public pd::OpProtoAndCheckerMaker {
public:
TestAttrProtoMaker(pd::OpProto* proto, pd::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddAttr<float>("scale", "scale of test op");
AddAttr<float>("scale", "scale of test op");
}
};
TEST(ProtoMaker, DuplicatedAttr) {
pd::OpProto op_proto;
pd::OpAttrChecker op_checker;
auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
ASSERT_THROW(proto_maker.Validate(), paddle::framework::EnforceNotMet);
}
class TestInOutProtoMaker : public pd::OpProtoAndCheckerMaker {
public:
TestInOutProtoMaker(pd::OpProto* proto, pd::OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of test op");
AddInput("input", "input of test op");
}
}
\ No newline at end of file
};
TEST(ProtoMaker, DuplicatedInOut) {
pd::OpProto op_proto;
pd::OpAttrChecker op_checker;
auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
ASSERT_THROW(proto_maker.Validate(), paddle::framework::EnforceNotMet);
}
paddle/framework/operator.cc 0 → 100644
浏览文件 @ 60a78893
/* 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 <algorithm>
#include "paddle/framework/operator.h"
namespace paddle {
namespace framework {
template <>
Eigen::DefaultDevice* KernelContext::GetEigenDevice<
platform::CPUPlace, Eigen::DefaultDevice>() const {
return device_context_.get_eigen_device<Eigen::DefaultDevice>();
}
#ifndef PADDLE_ONLY_CPU
template <>
Eigen::GpuDevice*
KernelContext::GetEigenDevice<platform::GPUPlace, Eigen::GpuDevice>() const {
return device_context_.get_eigen_device<Eigen::GpuDevice>();
}
#endif
const std::string& OperatorBase::Input(const std::string& name) const {
auto it = in_out_idxs_->find(name);
PADDLE_ENFORCE(it != in_out_idxs_->end(), "no key [%s] in in_out_idxs_",
name);
if (attrs_.count("input_format") == 0) {
return inputs_[it->second];
} else {
const auto& input_format = GetAttr<std::vector<int>>("input_format");
int idx = input_format[it->second];
return inputs_.at(idx);
}
}
std::vector<std::string> OperatorBase::Inputs(const std::string& name) const {
auto input_format = GetAttr<std::vector<int>>("input_format");
auto offset = in_out_idxs_->at(name);
return std::vector<std::string>{
inputs_.begin() + input_format.at(offset),
inputs_.begin() + input_format.at(offset + 1)};
}
const std::string& OperatorBase::Output(const std::string& name) const {
auto it = in_out_idxs_->find(name);
PADDLE_ENFORCE(it != in_out_idxs_->end(), "no key [%s] in in_out_idxs_",
name);
if (attrs_.count("output_format") == 0) {
return outputs_[it->second];
} else {
const auto& output_format = GetAttr<std::vector<int>>("output_format");
int idx = output_format[it->second];
return outputs_.at(idx);
}
}
std::vector<std::string> OperatorBase::Outputs(const std::string& name) const {
auto output_format = GetAttr<std::vector<int>>("output_format");
auto offset = in_out_idxs_->at(name);
return std::vector<std::string>{
outputs_.begin() + output_format.at(offset),
outputs_.begin() + output_format.at(offset + 1)};
}
std::string OperatorBase::DebugString() const {
std::stringstream ss;
ss << "Op(" << type_ << "), inputs:(";
for (size_t i = 0; i < inputs_.size(); ++i) {
ss << inputs_[i];
if (i != inputs_.size() - 1) {
ss << ", ";
}
}
ss << "), outputs:(";
for (size_t i = 0; i < outputs_.size(); ++i) {
ss << outputs_[i];
if (i != outputs_.size() - 1) {
ss << ", ";
}
}
ss << ").";
return ss.str();
}
} // namespace framework
} // namespace paddle
paddle/framework/operator.h 0 → 100644
浏览文件 @ 60a78893
/* 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 <string>
#include <unordered_map>
#include <vector>
#include "paddle/framework/attr_checker.h"
#include "paddle/framework/op_desc.pb.h"
#include "paddle/framework/op_proto.pb.h"
#include "paddle/framework/scope.h"
#include "paddle/framework/tensor.h"
#include "paddle/platform/device_context.h"
#include "paddle/platform/place.h"
#include "paddle/utils/Error.h"
namespace paddle {
namespace framework {
template <typename T>
struct EigenDeviceConverter;
template <>
struct EigenDeviceConverter<platform::CPUPlace> {
using EigenDeviceType = Eigen::DefaultDevice;
};
#ifndef PADDLE_ONLY_CPU
template <>
struct EigenDeviceConverter<platform::GPUPlace> {
using EigenDeviceType = Eigen::GpuDevice;
};
#endif
class OperatorBase;
using OperatorPtr = std::shared_ptr<OperatorBase>;
/**
* OperatorBase has the basic element that Net will call to do computation.
* Only CreateOperator from OpRegistry will new Operator directly. User
* should always construct a proto message OpDesc and call
* OpRegistry::CreateOp(op_desc) to get an Operator instance.
*/
class OperatorBase {
public:
/// If a variable is a empty variable, that name will be used.
static std::string EMPTY_VAR_NAME() { return "@EMPTY@"; }
/// If a variable is a temporary variable, that name will be set in Python,
/// but it will be convert to a unique name in scope after OpCreator.
static std::string TMP_VAR_NAME() { return "@TEMP@"; }
virtual ~OperatorBase() {}
template <typename T>
inline const T& GetAttr(const std::string& name) const {
PADDLE_ENFORCE(attrs_.count(name) != 0, "%s should be in AttributeMap",
name);
return boost::get<T>(attrs_.at(name));
}
virtual std::string DebugString() const;
/// Init will be called after CreateOperator, you can put some initialization
/// logic here.
virtual void Init() {}
/// InferShape infer the size of Variables used by this Operator with
/// information inside scope
virtual void InferShape(const ScopePtr& scope) const = 0;
/// Net will call this function to Run an op.
virtual void Run(const ScopePtr& scope,
const platform::DeviceContext& dev_ctx) const = 0;
// Get a input with argument's name described in `op_proto`
const std::string& Input(const std::string& name) const;
// Get a input which has multiple variables.
// TODO add a vector_view to prevent memory copy.
std::vector<std::string> Inputs(const std::string& name) const;
// Get a output with argument's name described in `op_proto`
const std::string& Output(const std::string& name) const;
// Get an output which has multiple variables.
// TODO add a vector_view to prevent memory copy.
std::vector<std::string> Outputs(const std::string& name) const;
public:
std::string type_;
std::vector<std::string> inputs_;
std::vector<std::string> outputs_;
AttributeMap attrs_;
// store the arguments' offset described in op_desc.
std::shared_ptr<std::unordered_map<std::string, int>> in_out_idxs_;
};
class KernelContext {
public:
KernelContext(const OperatorBase* op, const std::shared_ptr<Scope>& scope,
const platform::DeviceContext& device_context)
: op_(*op), scope_(scope), device_context_(device_context) {}
const Variable* Input(int index) const {
return scope_->GetVariable(op_.inputs_[index]);
}
Variable* Output(int index) const {
return scope_->GetVariable(op_.outputs_[index]);
}
const Variable* Input(const std::string& name) const {
return scope_->GetVariable(op_.Input(name));
}
const Variable* Output(const std::string& name) const {
return scope_->GetVariable(op_.Output(name));
}
const std::vector<const Variable*> Inputs(const std::string& name) const {
auto names = op_.Inputs(name);
std::vector<const Variable*> res;
std::transform(
names.begin(), names.end(), res.begin(),
[this](const std::string& name) { return scope_->GetVariable(name); });
return res;
}
const std::vector<const Variable*> Outputs(const std::string& name) const {
auto names = op_.Outputs(name);
std::vector<const Variable*> res;
std::transform(
names.begin(), names.end(), res.begin(),
[this](const std::string& name) { return scope_->GetVariable(name); });
return res;
}
template <typename PlaceType,
typename DeviceType =
typename EigenDeviceConverter<PlaceType>::EigenDeviceType>
DeviceType* GetEigenDevice() const;
platform::Place GetPlace() const { return device_context_.GetPlace(); }
const OperatorBase& op_;
const std::shared_ptr<Scope>& scope_;
const platform::DeviceContext& device_context_;
};
class OpKernel {
public:
/**
* KernelContext is the only parameter of Kernel Run function.
* Run will get input/output variables, state such as momentum and
* device resource such as CUDA stream, cublas handle, etc. from
* KernelContext. User should construct it before run the Operator.
*/
virtual void Compute(const KernelContext& context) const = 0;
virtual ~OpKernel() {}
};
template <typename T>
struct VarToTensor {};
template <>
struct VarToTensor<Tensor*> {
Tensor* operator()(Variable* var) { return var->GetMutable<Tensor>(); }
};
template <>
struct VarToTensor<const Tensor*> {
const Tensor* operator()(Variable* var) { return &var->Get<Tensor>(); }
};
class OperatorWithKernel : public OperatorBase {
public:
struct OpKernelKey {
platform::Place place_;
OpKernelKey() = default;
OpKernelKey(const platform::DeviceContext& dev_ctx) {
place_ = dev_ctx.GetPlace();
}
bool operator==(const OpKernelKey& o) const { return place_ == o.place_; }
};
struct OpKernelHash {
std::hash<bool> hash_;
size_t operator()(const OpKernelKey& key) const {
return hash_(platform::is_gpu_place(key.place_));
}
};
using OpKernelMap =
std::unordered_map<OpKernelKey, std::unique_ptr<OpKernel>, OpKernelHash>;
void Run(const ScopePtr& scope,
const platform::DeviceContext& dev_ctx) const final {
auto& opKernel = AllOpKernels().at(type_).at(OpKernelKey(dev_ctx));
opKernel->Compute(KernelContext(this, scope, dev_ctx));
}
static std::unordered_map<std::string /* op_type */, OpKernelMap>&
AllOpKernels() {
static std::unordered_map<std::string, OpKernelMap> g_all_op_kernels;
return g_all_op_kernels;
}
void InferShape(const std::shared_ptr<Scope>& scope) const final {
std::vector<const Tensor*> ins;
VarNamesToTensors(scope, inputs_, &ins);
std::vector<Tensor*> outs;
VarNamesToTensors(scope, outputs_, &outs);
InferShape(ins, outs);
};
private:
template <typename T>
void VarNamesToTensors(const std::shared_ptr<Scope>& scope,
const std::vector<std::string>& var_names,
std::vector<T>* container) const {
container->reserve(var_names.size());
VarToTensor<T> convert;
for (auto& name : var_names) {
auto var = scope->GetVariable(name);
if (var != nullptr) {
container->push_back(convert(var));
} else {
container->push_back(nullptr);
}
}
}
protected:
virtual void InferShape(const std::vector<const Tensor*>& inputs,
const std::vector<Tensor*>& outputs) const = 0;
};
} // namespace framework
} // namespace paddle
paddle/framework/operator_test.cc 0 → 100644
浏览文件 @ 60a78893
/* 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/operator.h"
#include "gtest/gtest.h"
#include "paddle/framework/op_registry.h"
namespace paddle {
namespace framework {
static int op_run_num = 0;
class OpWithoutKernelTest : public OperatorBase {
public:
void Init() override { x = 1; }
void InferShape(const ScopePtr& scope) const override {}
void Run(const ScopePtr& scope,
const platform::DeviceContext& dev_ctx) const override {
op_run_num++;
ASSERT_EQ((int)inputs_.size(), 1);
ASSERT_EQ((int)outputs_.size(), 1);
ASSERT_EQ(scope->GetVariable(inputs_[0]), nullptr);
ASSERT_EQ(x, 1);
ASSERT_NE(scope->GetVariable(outputs_[0]), nullptr);
}
public:
float x = 0;
};
class OpeWithoutKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
OpeWithoutKernelTestProtoAndCheckerMaker(OpProto* proto,
OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("input", "input of test op");
AddOutput("output", "output of test op");
AddAttr<float>("scale", "scale of cosine op");
AddComment("This is test op");
}
};
} // namespace framework
} // namespace paddle
REGISTER_OP(test_operator, paddle::framework::OpWithoutKernelTest,
paddle::framework::OpeWithoutKernelTestProtoAndCheckerMaker);
TEST(OperatorBase, all) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("test_operator");
*op_desc.mutable_inputs()->Add() = "IN1";
*op_desc.mutable_outputs()->Add() = "OUT1";
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("scale");
attr->set_type(paddle::framework::AttrType::FLOAT);
attr->set_f(3.14);
paddle::platform::CPUDeviceContext device_context;
auto scope = std::make_shared<paddle::framework::Scope>();
paddle::framework::OperatorPtr op =
paddle::framework::OpRegistry::CreateOp(op_desc);
scope->CreateVariable("OUT1");
ASSERT_EQ(paddle::framework::op_run_num, 0);
op->Run(scope, device_context);
ASSERT_EQ(paddle::framework::op_run_num, 1);
}
namespace paddle {
namespace framework {
class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("x", "input of test op");
AddOutput("y", "output of test op");
AddAttr<float>("scale", "scale of cosine op")
.SetDefault(1.0)
.LargerThan(0.0);
AddComment("This is test op");
}
};
static int cpu_kernel_run_num = 0;
class OpWithKernelTest : public OperatorWithKernel {
protected:
void InferShape(const std::vector<const Tensor*>& inputs,
const std::vector<Tensor*>& outputs) const override {}
};
template <typename T1, typename T2>
class CPUKernelTest : public OpKernel {
public:
void Compute(const KernelContext& ctx) const {
std::cout << "this is cpu kernel" << std::endl;
std::cout << ctx.op_.DebugString() << std::endl;
cpu_kernel_run_num++;
ASSERT_EQ(ctx.op_.Input("x"), "IN1");
ASSERT_EQ(ctx.op_.Output("y"), "OUT1");
}
};
// multiple inputs test
class OperatorMultiInputsTest : public OperatorBase {
public:
void Init() override { x = 1; }
void InferShape(const std::shared_ptr<Scope>& scope) const override {}
void Run(const std::shared_ptr<Scope>& scope,
const platform::DeviceContext& dev_ctx) const override {
ASSERT_EQ(scope->GetVariable(inputs_[0]), nullptr);
ASSERT_EQ(x, 1);
ASSERT_NE(scope->GetVariable(outputs_[0]), nullptr);
ASSERT_EQ(Input("x"), "IN1");
ASSERT_EQ(Input("y"), "OUT1");
}
public:
float x = 0;
};
class OpKernelTestMultiInputsProtoAndCheckerMaker
: public OpProtoAndCheckerMaker {
public:
OpKernelTestMultiInputsProtoAndCheckerMaker(OpProto* proto,
OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInputs("xs", "inputs of test op");
AddInput("k", "input of test op");
AddOutputs("ys", "outputs of test op");
AddAttr<float>("scale", "scale of cosine op")
.SetDefault(1.0)
.LargerThan(0.0);
AddComment("This is test op");
}
};
class CPUKernalMultiInputsTest : public OpKernel {
public:
void Compute(const KernelContext& ctx) const {
auto xs = ctx.op_.Inputs("xs");
ASSERT_EQ(xs.size(), 3UL);
ASSERT_EQ(xs[0], "x0");
ASSERT_EQ(xs[1], "x1");
ASSERT_EQ(xs[2], "x2");
auto k = ctx.op_.Input("k");
ASSERT_EQ(k, "k0");
auto ys = ctx.op_.Outputs("ys");
ASSERT_EQ(ys.size(), 2UL);
ASSERT_EQ(ys[0], "y0");
ASSERT_EQ(ys[1], "y1");
}
};
} // namespace framework
} // namespace paddle
REGISTER_OP(op_with_kernel, paddle::framework::OpWithKernelTest,
paddle::framework::OpKernelTestProtoAndCheckerMaker);
REGISTER_OP_CPU_KERNEL(op_with_kernel,
paddle::framework::CPUKernelTest<float, float>);
// test with single input
TEST(OpKernel, all) {
paddle::framework::OpDesc op_desc;
op_desc.set_type("op_with_kernel");
*op_desc.mutable_inputs()->Add() = "IN1";
*op_desc.mutable_outputs()->Add() = "OUT1";
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("scale");
attr->set_type(paddle::framework::AttrType::FLOAT);
attr->set_f(3.14);
paddle::platform::CPUDeviceContext cpu_device_context;
auto scope = std::make_shared<paddle::framework::Scope>();
paddle::framework::OperatorPtr op =
paddle::framework::OpRegistry::CreateOp(op_desc);
ASSERT_EQ(paddle::framework::cpu_kernel_run_num, 0);
op->Run(scope, cpu_device_context);
ASSERT_EQ(paddle::framework::cpu_kernel_run_num, 1);
}
REGISTER_OP(op_multi_inputs_with_kernel, paddle::framework::OpWithKernelTest,
paddle::framework::OpKernelTestMultiInputsProtoAndCheckerMaker);
REGISTER_OP_CPU_KERNEL(op_multi_inputs_with_kernel,
paddle::framework::CPUKernalMultiInputsTest);
// test with multi inputs
TEST(OpKernel, multi_inputs) {
using namespace paddle::framework;
OpDesc op_desc;
op_desc.set_type("op_multi_inputs_with_kernel");
*op_desc.mutable_inputs()->Add() = "x0";
*op_desc.mutable_inputs()->Add() = "x1";
*op_desc.mutable_inputs()->Add() = "x2";
*op_desc.mutable_inputs()->Add() = "k0";
*op_desc.mutable_outputs()->Add() = "y0";
*op_desc.mutable_outputs()->Add() = "y1";
auto attr = op_desc.mutable_attrs()->Add();
attr->set_name("scale");
attr->set_type(paddle::framework::AttrType::FLOAT);
attr->set_f(3.14);
auto attr0 = op_desc.mutable_attrs()->Add();
attr0->set_name("input_format");
attr0->set_type(paddle::framework::AttrType::INTS);
auto input_format = attr0->mutable_ints();
input_format->Add(0); // x0
input_format->Add(3); // k
input_format->Add(4); // end
auto attr1 = op_desc.mutable_attrs()->Add();
attr1->set_name("output_format");
attr1->set_type(paddle::framework::AttrType::INTS);
auto output_format = attr1->mutable_ints();
output_format->Add(0); // y0
output_format->Add(2); // y1
paddle::platform::CPUDeviceContext cpu_device_context;
auto scope = std::make_shared<Scope>();
OperatorPtr op(paddle::framework::OpRegistry::CreateOp(op_desc));
op->Run(scope, cpu_device_context);
}
paddle/framework/scope.h
浏览文件 @ 60a78893
......@@ -23,6 +23,9 @@ limitations under the License. */
namespace paddle {
namespace framework {
class Scope;
using ScopePtr = std::shared_ptr<Scope>;
/**
* @brief Scope that manage all variables.
*
......@@ -41,7 +44,7 @@ class Scope {
/**
* @brief Initialize a Scope with parent.
*/
explicit Scope(const std::shared_ptr<Scope>& parent) : parent_(parent) {}
explicit Scope(const ScopePtr& parent) : parent_(parent) {}
/**
* @brief Create Variable
......@@ -88,7 +91,7 @@ class Scope {
private:
std::unordered_map<std::string, std::unique_ptr<Variable>> vars_;
std::shared_ptr<Scope> parent_{nullptr};
ScopePtr parent_{nullptr};
};
} // namespace framework
......
paddle/framework/tensor.cc 0 → 100644
浏览文件 @ 60a78893
/* 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/tensor.h>
namespace paddle {
namespace framework {}
} // namespace paddle
paddle/framework/tensor.h
浏览文件 @ 60a78893
......@@ -14,84 +14,245 @@ limitations under the License. */
#pragma once
#include <cstdint>
#include <cstring>
#include <memory>
#include <type_traits>
#include <typeindex>
#include "paddle/framework/ddim.h"
#include "paddle/framework/enforce.h"
#include "paddle/framework/tensor_types.h"
#include "paddle/memory/memory.h"
#include "paddle/platform/place.h"
#include "unsupported/Eigen/CXX11/Tensor"
namespace paddle {
namespace pybind {
namespace details { // forward declare
template <bool less, size_t i, typename... args>
struct CastToPyBufferImpl;
} // namespace details
} // namespace pybind
namespace framework {
class Tensor {
public:
Tensor() : offset_(0) {}
template <typename T>
const T* data() const {
PADDLE_ENFORCE(holder_ != nullptr,
"Tensor::data must be called after Tensor::mutable_data.");
return static_cast<const T*>(holder_->Ptr());
CheckDims<T>();
return reinterpret_cast<const T*>(
reinterpret_cast<uintptr_t>(holder_->ptr()) + offset_);
}
template <typename T>
T* raw_data() const {
CheckDims<T>();
return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
offset_);
}
template <typename T>
T* mutable_data(DDim dims, platform::Place place) {
set_dims(dims);
return mutable_data<T>(place);
}
template <typename T, // must be POD types
typename std::enable_if<std::is_pod<T>::value>::type* = nullptr>
T* mutable_data(DDim dims, paddle::platform::Place place) {
template <typename T>
T* mutable_data(platform::Place place) {
PADDLE_ENFORCE(product(dims_) > 0,
"Tensor's numel must be larger than zero to call "
"Tensor::mutable_data. Call Tensor::set_dim first.");
if (holder_ == nullptr ||
!(holder_->Place() ==
!(holder_->place() ==
place) /* some versions of boost::variant don't have operator!= */
|| holder_->Size() < product(dims) * sizeof(T)) {
holder_.reset(new PlaceholderImpl<T>(place, product(dims) * sizeof(T)));
|| holder_->size() < product(dims_) * sizeof(T) + offset_) {
if (platform::is_cpu_place(place)) {
holder_.reset(new PlaceholderImpl<T, platform::CPUPlace>(
boost::get<platform::CPUPlace>(place), product(dims_) * sizeof(T)));
} else if (platform::is_gpu_place(place)) {
#ifdef PADDLE_ONLY_CPU
PADDLE_THROW("'GPUPlace' is not supported in CPU only device.");
#else
holder_.reset(new PlaceholderImpl<T, platform::GPUPlace>(
boost::get<platform::GPUPlace>(place), product(dims_) * sizeof(T)));
#endif
} else {
PADDLE_THROW("Unknown 'place'.");
}
offset_ = 0;
}
return reinterpret_cast<T*>(reinterpret_cast<uintptr_t>(holder_->ptr()) +
offset_);
}
template <typename T, size_t NDIMS>
typename TTypes<T, NDIMS>::Tensor shaped(DDim new_dims) {
Eigen::array<Eigen::DenseIndex, NDIMS> dims =
paddle::framework::ToEigenDSizes<NDIMS>(new_dims);
return typename TTypes<T, NDIMS>::Tensor(raw_data<T>(), dims);
}
template <typename T, size_t NDIMS>
typename TTypes<T, NDIMS>::Tensor tensor() {
return typename TTypes<T, NDIMS>::Tensor(
raw_data<T>(), paddle::framework::ToEigenDSizes<NDIMS>(dims_));
}
// flat to rank = 1
template <typename T>
typename TTypes<T>::Flat flat() {
return shaped<T, 1>(make_ddim({static_cast<int>(product(dims_))}));
}
// to TensorType Vec
template <typename T>
typename TTypes<T>::Vec vec() {
return tensor<T, 1>();
}
// to TensorType Matrix
template <typename T>
typename TTypes<T>::Matrix matrix() {
return tensor<T, 2>();
}
// const versions of all the methods above.
template <typename T, size_t NDIMS>
typename TTypes<T, NDIMS>::Tensor shaped(DDim new_dims) const {
Eigen::array<Eigen::DenseIndex, NDIMS> dims =
paddle::framework::ToEigenDSizes<NDIMS>(new_dims);
return typename TTypes<T, NDIMS>::Tensor(data<T>(), dims);
}
template <typename T, size_t NDIMS>
typename TTypes<T, NDIMS>::ConstantTensor tensor() const {
return typename TTypes<T, NDIMS>::Tensor(
data<T>(), paddle::framework::ToEigenDSizes<NDIMS>(dims_));
}
template <typename T>
typename TTypes<T>::ConstFlat flat() const {
return shaped<T, 1>(make_ddim({static_cast<int>(product(dims_))}));
}
template <typename T>
typename TTypes<T>::ConstVec vec() const {
return tensor<T, 1>();
}
template <typename T>
typename TTypes<T>::ConstMatrix matrix() const {
return tensor<T, 2>();
}
template <typename T>
void ShareDataFrom(const Tensor& src) {
src.CheckDims<T>();
holder_ = src.holder_;
set_dims(src.dims());
offset_ = src.offset_;
}
template <typename T>
void CopyFrom(const Tensor& src, platform::Place dst_place) {
PADDLE_ENFORCE(platform::is_cpu_place(src.holder_->place()) &&
platform::is_cpu_place(dst_place),
"Tensor::CopyFrom only support CPU now.");
src.CheckDims<T>();
size_t size = product(src.dims_) * sizeof(T);
set_dims(src.dims());
const void* src_ptr = static_cast<const void*>(src.data<T>());
void* dst_ptr = static_cast<void*>(mutable_data<T>(dst_place));
memcpy(dst_ptr, src_ptr, size);
}
template <typename T>
Tensor Slice(const int& begin_idx, const int& end_idx) const {
CheckDims<T>();
PADDLE_ENFORCE(begin_idx >= 0 && end_idx <= dims_[0],
"Slice index is less than zero or out of bound.");
PADDLE_ENFORCE(begin_idx < end_idx,
"Begin index must be less than end index.");
PADDLE_ENFORCE(dims_[0] != 1, "Can not slice a tensor with dims_[0] = 1.");
std::vector<int> d = vectorize(dims_);
int base = 1;
for (size_t i = 1; i < d.size(); ++i) {
base *= d[i];
}
return static_cast<T*>(holder_->Ptr());
Tensor dst;
dst.holder_ = holder_;
DDim dst_dims = dims_;
dst_dims[0] = end_idx - begin_idx;
dst.set_dims(dst_dims);
dst.offset_ = offset_ + begin_idx * base * sizeof(T);
return dst;
}
template <typename T, // must be POD types
typename std::enable_if<std::is_pod<T>::value>::type* = nullptr>
T* mutable_data(DDim dims) {
return mutable_data<T>(dims, paddle::platform::get_place());
void set_dims(const DDim& dims) {
if (dims == dims_) {
return;
}
dims_ = dims;
}
DDim dims() const { return dims_; }
private:
// Placeholder hides type T, so it doesn't appear as a template
// parameter of Variable.
struct Placeholder {
virtual ~Placeholder() {}
virtual void* Ptr() const = 0;
virtual paddle::platform::Place Place() const = 0;
virtual size_t Size() const = 0;
virtual void* ptr() const = 0;
virtual platform::Place place() const = 0;
virtual size_t size() const = 0;
virtual std::type_index type() const = 0;
};
template <typename T>
template <typename T, typename PlaceType>
struct PlaceholderImpl : public Placeholder {
private:
template <typename PType>
class Deleter {
public:
Deleter(platform::Place place) : place_(place) {}
void operator()(T* ptr) {
paddle::memory::Free(place_, static_cast<void*>(ptr));
}
Deleter(PType place) : place_(place) {}
void operator()(T* ptr) { memory::Free(place_, static_cast<void*>(ptr)); }
private:
paddle::platform::Place place_;
PType place_;
};
public:
PlaceholderImpl(paddle::platform::Place place, size_t size)
: ptr_(static_cast<T*>(paddle::memory::Alloc(place, size)),
Deleter(place)),
PlaceholderImpl(PlaceType place, size_t size)
: ptr_(static_cast<T*>(memory::Alloc(place, size)),
Deleter<PlaceType>(place)),
place_(place),
size_(size) {}
virtual void* Ptr() const { return static_cast<void*>(ptr_.get()); }
virtual size_t Size() const { return size_; }
virtual paddle::platform::Place Place() const { return place_; }
virtual void* ptr() const { return static_cast<void*>(ptr_.get()); }
virtual size_t size() const { return size_; }
virtual paddle::platform::Place place() const { return place_; }
virtual std::type_index type() const { return std::type_index(typeid(T)); }
std::unique_ptr<T, Deleter> ptr_;
paddle::platform::Place place_; // record the place of ptr_.
size_t size_; // size of the memory block.
std::unique_ptr<T, Deleter<PlaceType>> ptr_;
platform::Place place_; // record the place of ptr_.
size_t size_; // size of the memory block.
};
template <typename T>
inline void CheckDims() const {
PADDLE_ENFORCE(holder_ != nullptr,
"Tenosr holds no memory. Call Tensor::mutable_data first.");
PADDLE_ENFORCE(holder_->size() >= product(dims_) * sizeof(T) + offset_,
"Tensor's dims_ is out of bound. Call Tensor::mutable_data "
"first to re-allocate memory.");
}
std::shared_ptr<Placeholder> holder_; // holds the memory block if allocated.
DDim dims_;
size_t offset_; // marks the begin of tensor data area.
template <bool less, size_t i, typename... args>
friend struct paddle::pybind::details::CastToPyBufferImpl;
};
} // namespace framework
......
paddle/framework/tensor_test.cc
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......@@ -15,15 +15,28 @@
#include <gtest/gtest.h>
#include <string>
TEST(Tensor, ASSERT) {
paddle::framework::Tensor cpu_tensor;
TEST(Tensor, Dims) {
using namespace paddle::framework;
using namespace paddle::platform;
Tensor tt;
tt.set_dims(make_ddim({2, 3, 4}));
DDim dims = tt.dims();
ASSERT_EQ(arity(dims), 3);
for (int i = 0; i < 3; ++i) {
EXPECT_EQ(i + 2, dims[i]);
}
}
TEST(Tensor, DataAssert) {
paddle::framework::Tensor src_tensor;
bool caught = false;
try {
const double* p __attribute__((unused)) = cpu_tensor.data<double>();
src_tensor.data<double>();
} catch (paddle::framework::EnforceNotMet err) {
caught = true;
std::string msg = "Tensor::data must be called after Tensor::mutable_data.";
std::string msg =
"Tenosr holds no memory. Call Tensor::mutable_data first.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
......@@ -32,54 +45,168 @@ TEST(Tensor, ASSERT) {
ASSERT_TRUE(caught);
}
/* mutable_data() is not tested at present
/* following tests are not available at present
because Memory::Alloc() and Memory::Free() have not been ready.
*/
TEST(Tensor, MutableData) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor cpu_tensor;
Tensor src_tensor;
float* p1 = nullptr;
float* p2 = nullptr;
// initialization
p1 = cpu_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), CPUPlace());
EXPECT_NE(p1, nullptr);
// set cpu_tensor a new dim with large size
// set src_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 = cpu_tensor.mutable_data<float>(make_ddim({3, 4}));
p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), CPUPlace());
EXPECT_NE(p2, nullptr);
EXPECT_NE(p1, p2);
// set cpu_tensor a new dim with same size
// set src_tensor a new dim with same size
// momery block is supposed to be unchanged
p1 = cpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}));
p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), CPUPlace());
EXPECT_EQ(p1, p2);
// set cpu_tensor a new dim with smaller size
// set src_tensor a new dim with smaller size
// momery block is supposed to be unchanged
p2 = cpu_tensor.mutable_data<float>(make_ddim({2, 2}));
p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), CPUPlace());
EXPECT_EQ(p1, p2);
}
#ifdef __CUDACC__
{
Tensor gpu_tensor;
Tensor src_tensor;
float* p1 = nullptr;
float* p2 = nullptr;
// initialization
p1 = gpu_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
p1 = src_tensor.mutable_data<float>(make_ddim({1, 2, 3}), GPUPlace());
EXPECT_NE(p1, nullptr);
// set gpu_tensor a new dim with large size
// set src_tensor a new dim with large size
// momery is supposed to be re-allocated
p2 = gpu_tensor.mutable_data<float>(make_ddim({3, 4}));
p2 = src_tensor.mutable_data<float>(make_ddim({3, 4}), GPUPlace());
EXPECT_NE(p2, nullptr);
EXPECT_NE(p1, p2);
// set gpu_tensor a new dim with same size
// set src_tensor a new dim with same size
// momery block is supposed to be unchanged
p1 = gpu_tensor.mutable_data<float>(make_ddim({2, 2, 3}));
p1 = src_tensor.mutable_data<float>(make_ddim({2, 2, 3}), GPUPlace());
EXPECT_EQ(p1, p2);
// set gpu_tensor a new dim with smaller size
// set src_tensor a new dim with smaller size
// momery block is supposed to be unchanged
p2 = gpu_tensor.mutable_data<float>(make_ddim({2, 2}));
p2 = src_tensor.mutable_data<float>(make_ddim({2, 2}), GPUPlace());
EXPECT_EQ(p1, p2);
}
#endif
}
TEST(Tensor, ShareDataFrom) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor src_tensor;
Tensor dst_tensor;
// Try to share data form uninitialized tensor
bool caught = false;
try {
dst_tensor.ShareDataFrom<float>(src_tensor);
} catch (EnforceNotMet err) {
caught = true;
std::string msg =
"Tenosr holds no memory. Call Tensor::mutable_data first.";
const char* what = err.what();
for (size_t i = 0; i < msg.length(); ++i) {
ASSERT_EQ(what[i], msg[i]);
}
}
ASSERT_TRUE(caught);
src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), CPUPlace());
dst_tensor.ShareDataFrom<int>(src_tensor);
ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
}
#ifdef __CUDACC__
{
Tensor src_tensor;
Tensor dst_tensor;
src_tensor.mutable_data<int>(make_ddim({2, 3, 4}), GPUPlace());
dst_tensor.ShareDataFrom<int>(src_tensor);
ASSERT_EQ(src_tensor.data<int>(), dst_tensor.data<int>());
}
#endif
}
TEST(Tensor, Slice) {
using namespace paddle::framework;
using namespace paddle::platform;
{
Tensor src_tensor;
src_tensor.mutable_data<int>(make_ddim({5, 3, 4}), CPUPlace());
Tensor slice_tensor = src_tensor.Slice<int>(1, 3);
DDim slice_dims = slice_tensor.dims();
ASSERT_EQ(arity(slice_dims), 3);
EXPECT_EQ(slice_dims[0], 2);
EXPECT_EQ(slice_dims[1], 3);
EXPECT_EQ(slice_dims[2], 4);
uintptr_t src_data_address =
reinterpret_cast<uintptr_t>(src_tensor.data<int>());
uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
src_tensor.mutable_data<int>(src_tensor.dims(), CPUPlace()));
uintptr_t slice_data_address =
reinterpret_cast<uintptr_t>(slice_tensor.data<int>());
uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
slice_tensor.mutable_data<int>(slice_tensor.dims(), CPUPlace()));
EXPECT_EQ(src_data_address, src_mutable_data_address);
EXPECT_EQ(slice_data_address, slice_mutable_data_address);
EXPECT_EQ(src_data_address + 3 * 4 * 1 * sizeof(int), slice_data_address);
}
#ifdef __CUDACC__
{
Tensor src_tensor;
src_tensor.mutable_data<double>(make_ddim({6, 9}), GPUPlace());
Tensor slice_tensor = src_tensor.Slice<double>(2, 6);
DDim slice_dims = slice_tensor.dims();
ASSERT_EQ(arity(slice_dims), 2);
EXPECT_EQ(slice_dims[0], 4);
EXPECT_EQ(slice_dims[1], 9);
uintptr_t src_data_address =
reinterpret_cast<uintptr_t>(src_tensor.data<double>());
uintptr_t src_mutable_data_address = reinterpret_cast<uintptr_t>(
src_tensor.mutable_data<double>(src_tensor.dims(), GPUPlace()));
uintptr_t slice_data_address =
reinterpret_cast<uintptr_t>(slice_tensor.data<double>());
uintptr_t slice_mutable_data_address = reinterpret_cast<uintptr_t>(
slice_tensor.mutable_data<double>(slice_tensor.dims(), GPUPlace()));
EXPECT_EQ(src_data_address, src_mutable_data_address);
EXPECT_EQ(slice_data_address, slice_mutable_data_address);
EXPECT_EQ(src_data_address + 9 * 2 * sizeof(double), slice_data_address);
}
#endif
}
TEST(Tensor, CopyFrom) {
using namespace paddle::framework;
using namespace paddle::platform;
Tensor src_tensor;
int* src_ptr = src_tensor.mutable_data<int>(make_ddim({3, 3}), CPUPlace());
int arr[9] = {1, 2, 3, 4, 5, 6, 7, 8, 9};
memcpy(src_ptr, arr, 9 * sizeof(int));
Tensor dst_tensor;
dst_tensor.CopyFrom<int>(src_tensor, CPUPlace());
const int* dst_ptr = dst_tensor.data<int>();
ASSERT_NE(src_ptr, dst_ptr);
for (size_t i = 0; i < 9; ++i) {
EXPECT_EQ(src_ptr[i], dst_ptr[i]);
}
Tensor slice_tensor = src_tensor.Slice<int>(1, 2);
dst_tensor.CopyFrom<int>(slice_tensor, CPUPlace());
const int* slice_ptr = slice_tensor.data<int>();
dst_ptr = dst_tensor.data<int>();
ASSERT_NE(dst_ptr, slice_ptr);
for (size_t i = 0; i < 3; ++i) {
EXPECT_EQ(dst_ptr[i], slice_ptr[i]);
}
}
*/
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paddle/function/CMakeLists.txt
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......@@ -11,7 +11,6 @@ if(WITH_GPU)
endif()
if(USE_NNPACK)
include(nnpack/nnpack.cmake)
list(APPEND cpp_files nnpack/NNPACKConvOp.cpp)
if(WITH_TESTING)
add_unittest(NNPACKConvOpTest nnpack/NNPACKConvOpTest.cpp)
......
paddle/function/GemmConvOp.cpp
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......@@ -117,8 +117,7 @@ public:
ConvFunctionBase::init(config);
}
virtual void check(const BufferArgs& inputs,
const BufferArgs& outputs) override {
void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
const TensorShape& input = inputs[0].shape();
const TensorShape& filter = inputs[1].shape();
const TensorShape& output = outputs[0].shape();
......@@ -217,8 +216,7 @@ public:
ConvFunctionBase::init(config);
}
virtual void check(const BufferArgs& inputs,
const BufferArgs& outputs) override {
void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
const TensorShape& output = inputs[0].shape();
const TensorShape& filter = inputs[1].shape();
const TensorShape& input = outputs[0].shape();
......@@ -311,8 +309,7 @@ public:
ConvFunctionBase::init(config);
}
virtual void check(const BufferArgs& inputs,
const BufferArgs& outputs) override {
void check(const BufferArgs& inputs, const BufferArgs& outputs) override {
const TensorShape& output = inputs[0].shape();
const TensorShape& input = inputs[1].shape();
const TensorShape& filter = outputs[0].shape();
......
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