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Paddle
提交 23560d08 编写于 作者: L lujun
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Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix-api-doc-20190220

上级 da92a2ce c6bd434f
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Showing with 4605 addition and 1781 deletion
AUTHORS.md
浏览文件 @ 23560d08
......@@ -44,6 +44,7 @@
| qingqing01 | Qing-Qing Dang |
| reyoung | Yang Yu |
| Sand3r- | Michal Gallus |
| sfraczek | Sylwester Fraczek |
| Superjom | Chun-Wei Yan |
| tensor-tang | Jian Tang |
| tianbingsz | Tian-Bing Xu |
......@@ -54,6 +55,7 @@
| wangyang59 | Yang Wang |
| wangzhen-nlp | Zhen Wang |
| wen-bo-yang | Wen-Bo Yang |
| wojtuss | Wojciech Uss |
| wwhu | Wei-Wei Hu |
| xinghai-sun | Xing-Hai Sun |
| Xreki | Yi-Qun Liu |
......
CMakeLists.txt
浏览文件 @ 23560d08
......@@ -54,23 +54,12 @@ option(WITH_NGRAPH "Compile PaddlePaddle with nGraph support." OFF)
option(WITH_DSO "Compile PaddlePaddle with dynamic linked CUDA" ON)
option(WITH_TESTING "Compile PaddlePaddle with unit testing" OFF)
option(WITH_PYTHON "Compile PaddlePaddle with python interpreter" ON)
option(WITH_DOUBLE "Compile PaddlePaddle with double precision" OFF)
option(WITH_RDMA "Compile PaddlePaddle with RDMA support" OFF)
option(WITH_TIMER "Compile PaddlePaddle with stats timer" OFF)
option(WITH_PROFILER "Compile PaddlePaddle with GPU profiler and gperftools" OFF)
option(WITH_JEMALLOC "Compile PaddlePaddle with jemalloc" OFF)
option(WITH_DOC "Compile PaddlePaddle with documentation" OFF)
option(WITH_COVERAGE "Compile PaddlePaddle with code coverage" OFF)
option(COVERALLS_UPLOAD "Package code coverage data to coveralls" OFF)
option(ON_TRAVIS "Exclude special unit test on Travis CI" OFF)
option(WITH_FLUID_ONLY "Compile PaddlePaddle fluid only" OFF)
option(WITH_GOLANG "Compile PaddlePaddle with GOLANG" OFF)
option(GLIDE_INSTALL "Download and install go dependencies " ON)
option(WITH_DISTRIBUTE "Compile with distributed support" OFF)
option(WITH_PSLIB "Compile with pslib support" OFF)
option(USE_EIGEN_FOR_BLAS "Use matrix multiplication in Eigen" OFF)
option(EIGEN_USE_THREADS "Compile with multi-threaded Eigen" OFF)
option(WITH_ARM_FP16 "Use half precision support on armv8.2-a cpu" OFF)
option(WITH_CONTRIB "Compile the third-party contributation" OFF)
option(REPLACE_ENFORCE_GLOG "Replace PADDLE_ENFORCE with glog/CHECK for better debug." OFF)
option(WITH_ANAKIN "Compile with Anakin library" OFF)
......@@ -105,8 +94,6 @@ endif()
if (WIN32)
set(WITH_DISTRIBUTE OFF CACHE STRING
"Disable DISTRIBUTE when compiling for Windows" FORCE)
set(WITH_FLUID_ONLY ON CACHE STRING
"Enable FLUID_ONLY when compiling for Windows" FORCE)
endif()
set(THIRD_PARTY_PATH "${CMAKE_BINARY_DIR}/third_party" CACHE STRING
......@@ -148,7 +135,6 @@ include(external/openblas) # download, build, install openblas
include(external/mkldnn) # download, build, install mkldnn
include(external/ngraph) # download, build, install nGraph
include(external/boost) # download boost
include(external/any) # download libn::any
include(external/eigen) # download eigen3
include(external/pybind11) # download pybind11
include(external/cares)
......@@ -225,7 +211,6 @@ include(generic) # simplify cmake module
include(package) # set paddle packages
include(ccache) # set ccache for compilation
include(util) # set unittest and link libs
include(rdma) # set rdma libraries
include(version) # set PADDLE_VERSION
include(coveralls) # set code coverage
include(inference_lib) # add paddle fluid inference libraries
......@@ -233,38 +218,11 @@ include(inference_lib) # add paddle fluid inference libraries
include_directories("${PADDLE_SOURCE_DIR}")
set(EXTERNAL_LIBS
gflags
glog
${CBLAS_LIBRARIES}
protobuf
zlib
${PYTHON_LIBRARIES}
)
if(WITH_PSLIB)
list(APPEND EXTERNAL_LIBS pslib)
list(APPEND EXTERNAL_LIBS pslib_brpc)
list(APPEND EXTERNAL_LIBS libmct)
endif(WITH_PSLIB)
if(WITH_AMD_GPU)
find_package(HIP)
include(hip)
endif(WITH_AMD_GPU)
if(WITH_MKLML)
list(APPEND EXTERNAL_LIBS ${MKLML_IOMP_LIB})
endif()
if(WITH_LIBXSMM)
list(APPEND EXTERNAL_LIBS ${LIBXSMM_LIBS})
endif()
if(WITH_MKLDNN)
list(APPEND EXTERNAL_LIBS ${MKLDNN_LIB})
endif()
set(PADDLE_PYTHON_BUILD_DIR "${CMAKE_CURRENT_BINARY_DIR}/python/build")
set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "-O3 -g -DNDEBUG")
......
README.md
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......@@ -3,8 +3,8 @@
English | [简体中文](./README_cn.md)
[![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://paddlepaddle.org/documentation/docs/en/1.2/getstarted/index_en.html)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](http://paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/index.html)
[![Documentation Status](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](http://paddlepaddle.org/documentation/docs/en/1.3/beginners_guide/index_en.html)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](http://paddlepaddle.org/documentation/docs/zh/1.3/beginners_guide/index.html)
[![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)
......@@ -18,7 +18,7 @@ learning to many products at Baidu.
Our vision is to enable deep learning for everyone via PaddlePaddle.
Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddle/releases) to track the latest feature of PaddlePaddle.
### Latest PaddlePaddle Release: [Fluid 1.2.0](https://github.com/PaddlePaddle/Paddle/tree/release/1.2)
### Latest PaddlePaddle Release: [Fluid 1.3.0](https://github.com/PaddlePaddle/Paddle/tree/release/1.3)
### Install Latest Stable Release:
```
# Linux CPU
......@@ -26,9 +26,9 @@ pip install paddlepaddle
# Linux GPU cuda9cudnn7
pip install paddlepaddle-gpu
# Linux GPU cuda8cudnn7
pip install paddlepaddle-gpu==1.2.0.post87
pip install paddlepaddle-gpu==1.3.0.post87
# Linux GPU cuda8cudnn5
pip install paddlepaddle-gpu==1.2.0.post85
pip install paddlepaddle-gpu==1.3.0.post85
# For installation on other platform, refer to http://paddlepaddle.org/
```
......@@ -75,26 +75,26 @@ pip install paddlepaddle-gpu==1.2.0.post85
## Installation
It is recommended to read [this doc](http://paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/install/index_cn.html) on our website.
It is recommended to read [this doc](http://paddlepaddle.org/documentation/docs/en/1.3/beginners_guide/index_en.html) on our website.
## Documentation
We provide [English](http://paddlepaddle.org/documentation/docs/en/1.2/getstarted/index_en.html) and
[Chinese](http://paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/index.html) documentation.
We provide [English](http://paddlepaddle.org/documentation/docs/en/1.3/beginners_guide/index_en.html) and
[Chinese](http://paddlepaddle.org/documentation/docs/zh/1.3/beginners_guide/index.html) documentation.
- [Deep Learning 101](https://github.com/PaddlePaddle/book)
You might want to start from this online interactive book that can run in a Jupyter Notebook.
- [Distributed Training](http://paddlepaddle.org/documentation/docs/zh/1.2/user_guides/howto/training/cluster_howto.html)
- [Distributed Training](http://paddlepaddle.org/documentation/docs/en/1.3/user_guides/howto/training/multi_node_en.html)
You can run distributed training jobs on MPI clusters.
- [Python API](http://paddlepaddle.org/documentation/docs/zh/1.2/api_cn/index_cn.html)
- [Python API](http://paddlepaddle.org/documentation/docs/en/1.3/api/index_en.html)
Our new API enables much shorter programs.
- [How to Contribute](http://paddlepaddle.org/documentation/docs/zh/1.2/advanced_usage/development/contribute_to_paddle/index_cn.html)
- [How to Contribute](http://paddlepaddle.org/documentation/docs/en/1.3/advanced_usage/development/contribute_to_paddle/index_en.html)
We appreciate your contributions!
......
README_cn.md
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......@@ -3,8 +3,8 @@
[English](./README.md) | 简体中文
[![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://paddlepaddle.org/documentation/docs/en/1.2/getstarted/index_en.html)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](http://paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/index.html)
[![Documentation Status](https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat)](http://paddlepaddle.org/documentation/docs/en/1.3/beginners_guide/index_en.html)
[![Documentation Status](https://img.shields.io/badge/中文文档-最新-brightgreen.svg)](http://paddlepaddle.org/documentation/docs/zh/1.3/beginners_guide/index.html)
[![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)
......@@ -16,7 +16,7 @@ PaddlePaddle (PArallel Distributed Deep LEarning) 是一个简单易用、高效
跟进PaddlePaddle最新特性请参考我们的[版本说明](https://github.com/PaddlePaddle/Paddle/releases)
### PaddlePaddle最新版本: [Fluid 1.2.0](https://github.com/PaddlePaddle/Paddle/tree/release/1.2)
### PaddlePaddle最新版本: [Fluid 1.3.0](https://github.com/PaddlePaddle/Paddle/tree/release/1.3)
### 安装最新稳定版本:
```
# Linux CPU
......@@ -24,9 +24,9 @@ pip install paddlepaddle
# Linux GPU cuda9cudnn7
pip install paddlepaddle-gpu
# Linux GPU cuda8cudnn7
pip install paddlepaddle-gpu==1.2.0.post87
pip install paddlepaddle-gpu==1.3.0.post87
# Linux GPU cuda8cudnn5
pip install paddlepaddle-gpu==1.2.0.post85
pip install paddlepaddle-gpu==1.3.0.post85
# 其他平台上的安装指引请参考 http://paddlepaddle.org/
```
......@@ -57,26 +57,26 @@ pip install paddlepaddle-gpu==1.2.0.post85
## 安装
推荐阅读官网上的[安装说明](http://paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/install/index_cn.html)
推荐阅读官网上的[安装说明](http://paddlepaddle.org/documentation/docs/zh/1.3/beginners_guide/install/index_cn.html)
## 文档
我们提供[英文](http://paddlepaddle.org/documentation/docs/en/1.2/getstarted/index_en.html)和
[中文](http://paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/index.html) 文档
我们提供[英文](http://paddlepaddle.org/documentation/docs/en/1.3/beginners_guide/index_en.html)和
[中文](http://paddlepaddle.org/documentation/docs/zh/1.3/beginners_guide/index.html) 文档
- [深度学习101](https://github.com/PaddlePaddle/book)
或许您想从这个在线交互式书籍开始，可以在Jupyter Notebook中运行
- [分布式训练](http://paddlepaddle.org/documentation/docs/zh/1.2/user_guides/howto/training/cluster_howto.html)
- [分布式训练](http://paddlepaddle.org/documentation/docs/zh/1.3/user_guides/howto/training/multi_node.html)
可以在MPI集群上运行分布式训练任务
- [Python API](http://paddlepaddle.org/documentation/docs/zh/1.2/api_cn/index_cn.html)
- [Python API](http://paddlepaddle.org/documentation/docs/zh/1.3/api_cn/index_cn.html)
新的API支持代码更少更简洁的程序
- [贡献方式](http://paddlepaddle.org/documentation/docs/zh/1.2/advanced_usage/development/contribute_to_paddle/index_cn.html)
- [贡献方式](http://paddlepaddle.org/documentation/docs/zh/1.3/advanced_usage/development/contribute_to_paddle/index_cn.html)
欢迎您的贡献!
......
cmake/configure.cmake
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......@@ -20,31 +20,10 @@ if(WITH_DSO)
add_definitions(-DPADDLE_USE_DSO)
endif(WITH_DSO)
if(WITH_DOUBLE)
add_definitions(-DPADDLE_TYPE_DOUBLE)
endif(WITH_DOUBLE)
if(WITH_ARM_FP16)
add_definitions(-DPADDLE_ARM_FP16)
add_definitions("-march=armv8.2-a+fp16+simd")
endif(WITH_ARM_FP16)
if(WITH_TESTING)
add_definitions(-DPADDLE_WITH_TESTING)
endif(WITH_TESTING)
if(NOT WITH_TIMER)
add_definitions(-DPADDLE_DISABLE_TIMER)
endif(NOT WITH_TIMER)
if(USE_EIGEN_FOR_BLAS)
add_definitions(-DPADDLE_USE_EIGEN_FOR_BLAS)
endif(USE_EIGEN_FOR_BLAS)
if(EIGEN_USE_THREADS)
add_definitions(-DEIGEN_USE_THREADS)
endif(EIGEN_USE_THREADS)
if(NOT WITH_PROFILER)
add_definitions(-DPADDLE_DISABLE_PROFILER)
endif(NOT WITH_PROFILER)
......@@ -78,10 +57,6 @@ if(WIN32)
endif(NOT MSVC)
endif(WIN32)
if(NOT WITH_GOLANG)
add_definitions(-DPADDLE_WITHOUT_GOLANG)
endif(NOT WITH_GOLANG)
if(WITH_PSLIB)
add_definitions(-DPADDLE_WITH_PSLIB)
endif()
......@@ -171,55 +146,6 @@ if(WITH_DISTRIBUTE)
add_definitions(-DPADDLE_WITH_DISTRIBUTE)
endif()
if(WITH_GOLANG)
# we need to symlink Paddle directory into GOPATH. If we
# don't do it and we have code that depends on Paddle, go
# get ./... will download a new Paddle repo from Github,
# without the changes in our current Paddle repo that we
# want to build.
set(GOPATH "${CMAKE_CURRENT_BINARY_DIR}/go")
file(MAKE_DIRECTORY ${GOPATH})
set(PADDLE_IN_GOPATH "${GOPATH}/src/github.com/PaddlePaddle/Paddle")
file(MAKE_DIRECTORY "${PADDLE_IN_GOPATH}")
set(PADDLE_GO_PATH "${CMAKE_SOURCE_DIR}/go")
add_custom_target(go_path)
add_custom_command(TARGET go_path
# Symlink Paddle directory into GOPATH
COMMAND mkdir -p ${PADDLE_IN_GOPATH}
COMMAND rm -rf ${PADDLE_IN_GOPATH}
COMMAND ln -sf ${CMAKE_SOURCE_DIR} ${PADDLE_IN_GOPATH}
# Automatically get all dependencies specified in the source code
# We can't run `go get -d ./...` for every target, because
# multiple `go get` can not run concurrently, but make need to be
# able to run with multiple jobs.
WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
)
if (GLIDE_INSTALL)
if(EXISTS $ENV{GOPATH}/bin/glide)
set(GLIDE "$ENV{GOPATH}/bin/glide")
else()
message(FATAL_ERROR "no glide executeble found: $ENV{GOPATH}/bin/glide")
endif()
# 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 ${PADDLE_SOURCE_DIR}/go/glide.lock
WORKING_DIRECTORY "${PADDLE_IN_GOPATH}/go"
)
# 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 ${CMAKE_BINARY_DIR}/glide go_path)
endif()
endif(WITH_GOLANG)
if(WITH_GRPC)
add_definitions(-DPADDLE_WITH_GRPC)
endif(WITH_GRPC)
......
cmake/cuda.cmake
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......@@ -168,10 +168,7 @@ elseif (${CUDA_VERSION} LESS 11.0) # CUDA 10.x
endif()
include_directories(${CUDA_INCLUDE_DIRS})
list(APPEND EXTERNAL_LIBS ${CUDA_LIBRARIES} ${CUDA_rt_LIBRARY})
if(NOT WITH_DSO)
# TODO(panyx0718): CUPTI only allows DSO?
list(APPEND EXTERNAL_LIBS ${CUDNN_LIBRARY} ${CUPTI_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_curand_LIBRARY} ${NCCL_LIBRARY})
if(WIN32)
set_property(GLOBAL PROPERTY CUDA_MODULES ${CUDNN_LIBRARY} ${CUDA_CUBLAS_LIBRARIES} ${CUDA_curand_LIBRARY})
endif(WIN32)
......
cmake/external/anakin.cmake
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......@@ -74,5 +74,3 @@ add_dependencies(anakin_shared extern_anakin)
add_library(anakin_saber SHARED IMPORTED GLOBAL)
set_property(TARGET anakin_saber PROPERTY IMPORTED_LOCATION ${ANAKIN_SABER_LIB})
add_dependencies(anakin_saber extern_anakin)
list(APPEND external_project_dependencies anakin_shared anakin_saber)
cmake/external/any.cmake 已删除 100644 → 0
浏览文件 @ da92a2ce
INCLUDE(ExternalProject)
SET(ANY_SOURCE_DIR ${THIRD_PARTY_PATH}/any)
INCLUDE_DIRECTORIES(${ANY_SOURCE_DIR}/src/extern_lib_any)
ExternalProject_Add(
extern_lib_any
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/PaddlePaddle/any.git"
GIT_TAG "15595d8324be9e8a9a80d9ae442fdd12bd66df5d"
PREFIX ${ANY_SOURCE_DIR}
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
TEST_COMMAND ""
)
if (${CMAKE_VERSION} VERSION_LESS "3.3.0")
set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/lib_any_dummy.c)
file(WRITE ${dummyfile} "const char * dummy_any = \"${dummyfile}\";")
add_library(lib_any STATIC ${dummyfile})
else()
add_library(lib_any INTERFACE)
endif()
add_dependencies(lib_any extern_lib_any)
add_definitions(-DANY_IMPL_ANY_CAST_MOVEABLE)
LIST(APPEND external_project_dependencies lib_any)
cmake/external/boost.cmake
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......@@ -57,5 +57,4 @@ else()
endif()
add_dependencies(boost ${BOOST_PROJECT})
list(APPEND external_project_dependencies boost)
set(Boost_INCLUDE_DIR ${BOOST_INCLUDE_DIR})
cmake/external/brpc.cmake
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......@@ -69,5 +69,3 @@ SET_PROPERTY(TARGET brpc PROPERTY IMPORTED_LOCATION ${BRPC_LIBRARIES})
ADD_DEPENDENCIES(brpc extern_brpc)
add_definitions(-DBRPC_WITH_GLOG)
LIST(APPEND external_project_dependencies brpc)
cmake/external/cub.cmake
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......@@ -31,5 +31,3 @@ else()
endif()
add_dependencies(cub extern_cub)
LIST(APPEND external_project_dependencies cub)
cmake/external/dlpack.cmake
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......@@ -27,5 +27,3 @@ else()
endif()
add_dependencies(dlpack extern_dlpack)
LIST(APPEND external_project_dependencies dlpack)
cmake/external/eigen.cmake
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......@@ -52,5 +52,3 @@ else()
endif()
add_dependencies(eigen3 extern_eigen3)
LIST(APPEND external_project_dependencies eigen3)
cmake/external/gflags.cmake
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......@@ -61,8 +61,6 @@ ADD_LIBRARY(gflags STATIC IMPORTED GLOBAL)
SET_PROPERTY(TARGET gflags PROPERTY IMPORTED_LOCATION ${GFLAGS_LIBRARIES})
ADD_DEPENDENCIES(gflags extern_gflags)
LIST(APPEND external_project_dependencies gflags)
# On Windows (including MinGW), the Shlwapi library is used by gflags if available.
if (WIN32)
include(CheckIncludeFileCXX)
......
cmake/external/glog.cmake
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......@@ -72,5 +72,3 @@ ADD_LIBRARY(glog STATIC IMPORTED GLOBAL)
SET_PROPERTY(TARGET glog PROPERTY IMPORTED_LOCATION ${GLOG_LIBRARIES})
ADD_DEPENDENCIES(glog extern_glog gflags)
LINK_LIBRARIES(glog gflags)
LIST(APPEND external_project_dependencies glog)
cmake/external/gtest.cmake
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......@@ -79,5 +79,4 @@ IF(WITH_TESTING OR (WITH_DISTRIBUTE AND NOT WITH_GRPC))
SET_PROPERTY(TARGET gtest_main PROPERTY IMPORTED_LOCATION ${GTEST_MAIN_LIBRARIES})
ADD_DEPENDENCIES(gtest_main extern_gtest)
LIST(APPEND external_project_dependencies gtest gtest_main)
ENDIF(WITH_TESTING OR (WITH_DISTRIBUTE AND NOT WITH_GRPC))
cmake/external/leveldb.cmake
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......@@ -39,6 +39,3 @@ ADD_DEPENDENCIES(extern_leveldb snappy)
ADD_LIBRARY(leveldb STATIC IMPORTED GLOBAL)
SET_PROPERTY(TARGET leveldb PROPERTY IMPORTED_LOCATION ${LEVELDB_LIBRARIES})
ADD_DEPENDENCIES(leveldb extern_leveldb)
LIST(APPEND external_project_dependencies leveldb)
cmake/external/libmct.cmake
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......@@ -72,7 +72,4 @@ else()
add_library(libmct INTERFACE)
endif()
#ADD_LIBRARY(libmct SHARED IMPORTED GLOBAL)
ADD_DEPENDENCIES(libmct ${LIBMCT_PROJECT})
LIST(APPEND external_project_dependencies libmct)
cmake/external/libxsmm.cmake
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......@@ -53,5 +53,3 @@ MESSAGE(STATUS "Libxsmm library: ${LIBXSMM_LIBS}")
include_directories(${LIBXSMM_INCLUDE_DIR})
ADD_DEFINITIONS(-DPADDLE_WITH_LIBXSMM)
ADD_DEPENDENCIES(libxsmm extern_libxsmm)
LIST(APPEND external_project_dependencies libxsmm)
cmake/external/mkldnn.cmake
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......@@ -89,7 +89,6 @@ SET_PROPERTY(TARGET shared_mkldnn PROPERTY IMPORTED_LOCATION ${MKLDNN_LIB})
ADD_DEPENDENCIES(shared_mkldnn ${MKLDNN_PROJECT})
MESSAGE(STATUS "MKLDNN library: ${MKLDNN_LIB}")
add_definitions(-DPADDLE_WITH_MKLDNN)
LIST(APPEND external_project_dependencies shared_mkldnn)
# generate a static dummy target to track mkldnn dependencies
# for cc_library(xxx SRCS xxx.c DEPS mkldnn)
......
cmake/external/mklml.cmake
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......@@ -73,4 +73,3 @@ INCLUDE_DIRECTORIES(${MKLML_INC_DIR})
ADD_LIBRARY(mklml SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET mklml PROPERTY IMPORTED_LOCATION ${MKLML_LIB})
ADD_DEPENDENCIES(mklml ${MKLML_PROJECT})
LIST(APPEND external_project_dependencies mklml)
cmake/external/ngraph.cmake
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......@@ -77,4 +77,3 @@ add_dependencies(ngraph ${NGRAPH_PROJECT})
target_compile_definitions(ngraph INTERFACE -DPADDLE_WITH_NGRAPH)
target_include_directories(ngraph INTERFACE ${NGRAPH_INC_DIR})
target_link_libraries(ngraph INTERFACE ${NGRAPH_SHARED_LIB})
LIST(APPEND external_project_dependencies ngraph)
cmake/external/openblas.cmake
浏览文件 @ 23560d08
......@@ -11,11 +11,6 @@
# 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.
IF(USE_EIGEN_FOR_BLAS)
return()
ENDIF(USE_EIGEN_FOR_BLAS)
INCLUDE(cblas)
IF(NOT ${CBLAS_FOUND})
......@@ -91,7 +86,6 @@ ENDIF()
IF(NOT ${CBLAS_FOUND})
ADD_DEPENDENCIES(cblas extern_openblas)
LIST(APPEND external_project_dependencies cblas)
ELSE()
IF("${CBLAS_PROVIDER}" STREQUAL "MKLML")
ADD_DEPENDENCIES(cblas mklml)
......
cmake/external/protobuf.cmake
浏览文件 @ 23560d08
......@@ -129,7 +129,6 @@ macro(PROMPT_PROTOBUF_LIB)
ADD_DEPENDENCIES(protoc ${dep})
ENDFOREACH()
LIST(APPEND external_project_dependencies protobuf)
RETURN()
endmacro()
macro(SET_PROTOBUF_VERSION)
......@@ -203,7 +202,7 @@ FUNCTION(build_protobuf TARGET_NAME BUILD_FOR_HOST)
ENDIF()
SET(PROTOBUF_REPO "https://github.com/google/protobuf.git")
SET(PROTOBUF_TAG "v3.6.1")
SET(PROTOBUF_TAG "9f75c5aa851cd877fb0d93ccc31b8567a6706546")
ExternalProject_Add(
${TARGET_NAME}
......@@ -231,7 +230,7 @@ FUNCTION(build_protobuf TARGET_NAME BUILD_FOR_HOST)
)
ENDFUNCTION()
SET(PROTOBUF_VERSION 3.6.1)
SET(PROTOBUF_VERSION 3.1.0)
IF(NOT PROTOBUF_FOUND)
build_protobuf(extern_protobuf FALSE)
......
cmake/external/pslib.cmake
浏览文件 @ 23560d08
......@@ -70,4 +70,3 @@ ExternalProject_Add(
ADD_LIBRARY(pslib SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET pslib PROPERTY IMPORTED_LOCATION ${PSLIB_LIB})
ADD_DEPENDENCIES(pslib ${PSLIB_PROJECT})
LIST(APPEND external_project_dependencies pslib)
cmake/external/pslib_brpc.cmake
浏览文件 @ 23560d08
......@@ -70,4 +70,3 @@ ExternalProject_Add(
ADD_LIBRARY(pslib_brpc SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET pslib_brpc PROPERTY IMPORTED_LOCATION ${PSLIB_BRPC_LIB})
ADD_DEPENDENCIES(pslib_brpc ${PSLIB_BRPC_PROJECT})
LIST(APPEND external_project_dependencies pslib_brpc)
cmake/external/python.cmake
浏览文件 @ 23560d08
......@@ -74,8 +74,8 @@ IF(PYTHONINTERP_FOUND)
find_python_module(wheel REQUIRED)
find_python_module(google.protobuf REQUIRED)
FIND_PACKAGE(NumPy REQUIRED)
IF(${PY_GOOGLE.PROTOBUF_VERSION} AND ${PY_GOOGLE.PROTOBUF_VERSION} VERSION_LESS "3.6.1")
MESSAGE(FATAL_ERROR "Found Python Protobuf ${PY_GOOGLE.PROTOBUF_VERSION} < 3.6.1, "
IF(${PY_GOOGLE.PROTOBUF_VERSION} AND ${PY_GOOGLE.PROTOBUF_VERSION} VERSION_LESS "3.0.0")
MESSAGE(FATAL_ERROR "Found Python Protobuf ${PY_GOOGLE.PROTOBUF_VERSION} < 3.0.0, "
"please use pip to upgrade protobuf. pip install -U protobuf")
ENDIF()
ENDIF(PYTHONINTERP_FOUND)
......
cmake/external/threadpool.cmake
浏览文件 @ 23560d08
......@@ -26,5 +26,3 @@ else()
endif()
add_dependencies(simple_threadpool extern_threadpool)
LIST(APPEND external_project_dependencies simple_threadpool)
cmake/external/warpctc.cmake
浏览文件 @ 23560d08
......@@ -83,5 +83,3 @@ INCLUDE_DIRECTORIES(${THIRD_PARTY_PATH}/install) # For Paddle code to include wa
ADD_LIBRARY(warpctc SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET warpctc PROPERTY IMPORTED_LOCATION ${WARPCTC_LIBRARIES})
ADD_DEPENDENCIES(warpctc extern_warpctc)
LIST(APPEND external_project_dependencies warpctc)
cmake/external/xbyak.cmake
浏览文件 @ 23560d08
......@@ -55,4 +55,3 @@ else()
endif()
add_dependencies(xbyak ${XBYAK_PROJECT})
list(APPEND external_project_dependencies xbyak)
cmake/external/xxhash.cmake
浏览文件 @ 23560d08
......@@ -71,5 +71,3 @@ add_library(xxhash STATIC IMPORTED GLOBAL)
set_property(TARGET xxhash PROPERTY IMPORTED_LOCATION ${XXHASH_LIBRARIES})
include_directories(${XXHASH_INCLUDE_DIR})
add_dependencies(xxhash extern_xxhash)
LIST(APPEND external_project_dependencies xxhash)
cmake/external/zlib.cmake
浏览文件 @ 23560d08
......@@ -57,5 +57,3 @@ ENDIF(WIN32)
ADD_LIBRARY(zlib STATIC IMPORTED GLOBAL)
SET_PROPERTY(TARGET zlib PROPERTY IMPORTED_LOCATION ${ZLIB_LIBRARIES})
ADD_DEPENDENCIES(zlib extern_zlib)
LIST(APPEND external_project_dependencies zlib)
cmake/hip.cmake
浏览文件 @ 23560d08
......@@ -11,8 +11,6 @@ include_directories("/opt/rocm/rocrand/include")
include_directories("/opt/rocm/rccl/include")
include_directories("/opt/rocm/thrust")
list(APPEND EXTERNAL_LIBS "-L/opt/rocm/lib/ -lhip_hcc")
set(HIP_HCC_FLAGS "${HIP_HCC_FLAGS} -fPIC -DPADDLE_WITH_HIP -std=c++11" )
if(WITH_DSO)
......@@ -31,22 +29,12 @@ if(WITH_GRPC)
set(HIP_HCC_FLAGS "${HIP_HCC_FLAGS} -DPADDLE_WITH_GRPC")
endif(WITH_GRPC)
if(NOT WITH_GOLANG)
set(HIP_HCC_FLAGS "${HIP_HCC_FLAGS} -DPADDLE_WITHOUT_GOLANG")
endif(NOT WITH_GOLANG)
if(WITH_MKLDNN)
set(HIP_HCC_FLAGS "${HIP_HCC_FLAGS} -DPADDLE_WITH_MKLDNN")
endif(WITH_MKLDNN)
set(HIP_HCC_FLAGS "${HIP_HCC_FLAGS} -DANY_IMPL_ANY_CAST_MOVEABLE")
if(NOT WITH_RDMA)
set(HIP_HCC_FLAGS "${HIP_HCC_FLAGS} -DPADDLE_DISABLE_RDMA")
endif(NOT WITH_RDMA)
if(CMAKE_BUILD_TYPE STREQUAL "Debug")
list(APPEND HIP_HCC_FLAGS ${CMAKE_CXX_FLAGS_DEBUG})
elseif(CMAKE_BUILD_TYPE STREQUAL "RelWithDebInfo")
......
cmake/rdma.cmake 已删除 100644 → 0
浏览文件 @ da92a2ce
# user should download rdma first from subversion repository
# execute following instruction to download svn mannally
# svn co https://svn.baidu.com/sys/ip/trunk/rdma/sockrdmav1 rdma/
# svn co https://svn.baidu.com/sys/ip/trunk/rdma/thirdparty rdma/
# we use static output in svn repositories to avoid implict bugs from not standard runtime env.
if(WITH_RDMA)
set(RDMA_ROOT $ENV{RDMA_ROOT} CACHE PATH "Folder contains RDMA sock library and thirdparty library")
function(generate_rdma_links)
#redirect to current DIR to isolate the pollution from system runtime environment
#it can benifits unified control for different gcc environment.
#e.g, by default gcc48 did not refer /usr/lib64 which could contain low version
#runtime libraries that will crash process while loading it. That redirect trick
#can fix it.
execute_process(
COMMAND mkdir -p librdma
COMMAND ln -s -f /usr/lib64/libibverbs.so.1.0.0 librdma/libibverbs.so.1
COMMAND ln -s -f /usr/lib64/libibverbs.so.1.0.0 librdma/libibverbs.so
COMMAND ln -s -f /usr/lib64/librdmacm.so.1.0.0 librdma/librdmacm.so.1
COMMAND ln -s -f /usr/lib64/librdmacm.so.1.0.0 librdma/librdmacm.so
COMMAND ln -s -f /lib64/libnl.so.1.1.4 librdma/libnl.so.1
COMMAND ln -s -f /lib64/libnl.so.1.1.4 librdma/libnl.so
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}
)
endfunction(generate_rdma_links)
#check and set headers
find_path(RDMA_INC_SXISOCK sxi_sock.h PATHS ${RDMA_ROOT}/sockrdmav1/output/include)
find_path(RDMA_INC_XIO libxio.h PATHS ${RDMA_ROOT}/thirdparty/output/accelio)
find_path(RDMA_INC_EVENT event2 PATHS ${RDMA_ROOT}/thirdparty/output/libevent)
find_path(RDMA_INC_NUMA numa.h PATHS ${RDMA_ROOT}/thirdparty/output/libnuma)
#check and set libs
find_library(RDMA_LIB_SXISOCK NAMES sxisock PATHS ${RDMA_ROOT}/sockrdmav1/output)
find_library(RDMA_LIB_XIO NAMES xio PATHS ${RDMA_ROOT}/thirdparty/output/accelio)
find_library(RDMA_LIB_EVENT NAMES event PATHS ${RDMA_ROOT}/thirdparty/output/libevent)
find_library(RDMA_LIB_EVENT_CORE NAMES event_core PATHS ${RDMA_ROOT}/thirdparty/output/libevent)
find_library(RDMA_LIB_EVENT_EXTRA NAMES event_extra PATHS ${RDMA_ROOT}/thirdparty/output/libevent)
find_library(RDMA_LIB_EVENT_PTHREADS NAMES event_pthreads PATHS ${RDMA_ROOT}/thirdparty/output/libevent)
find_library(RDMA_LIB_NUMA NAMES numa PATHS ${RDMA_ROOT}/thirdparty/output/libnuma)
if(
RDMA_INC_SXISOCK AND
RDMA_INC_XIO AND
RDMA_INC_EVENT AND
RDMA_INC_NUMA AND
RDMA_LIB_SXISOCK AND
RDMA_LIB_XIO AND
RDMA_LIB_EVENT AND
RDMA_LIB_EVENT_CORE AND
RDMA_LIB_EVENT_EXTRA AND
RDMA_LIB_EVENT_PTHREADS AND
RDMA_LIB_NUMA
)
set(RDMA_INC_DIR
${RDMA_INC_SXISOCK}
${RDMA_INC_XIO}
${RDMA_INC_EVENT}
${RDMA_INC_NUMA})
set(RDMA_LIBS
${RDMA_LIB_SXISOCK}
${RDMA_LIB_XIO}
${RDMA_LIB_EVENT}
${RDMA_LIB_EVENT_CORE}
${RDMA_LIB_EVENT_EXTRA}
${RDMA_LIB_EVENT_PTHREADS}
${RDMA_LIB_NUMA}
)
set(RDMA_LD_FLAGS "-L./librdma -libverbs -lrdmacm -Xlinker -rpath ./librdma")
include_directories("${RDMA_INC_DIR}")
else()
#if this module is not called, RDMA_INC_DIR RDMA_LIBS will be null, so top module always refer this variable
message(FATAL_ERROR, "RDMA libraries are not found, try to set RDMA_ROOT or check all related libraries.")
endif()
else(WITH_RDMA)
set(RDMA_LIBS "")
set(RDMA_LD_FLAGS "")
add_definitions(-DPADDLE_DISABLE_RDMA)
endif(WITH_RDMA)
cmake/tensorrt.cmake
浏览文件 @ 23560d08
......@@ -33,6 +33,5 @@ if(TENSORRT_FOUND)
message(STATUS "Current TensorRT header is ${TENSORRT_INCLUDE_DIR}/NvInfer.h. "
"Current TensorRT version is v${TENSORRT_MAJOR_VERSION}. ")
include_directories(${TENSORRT_INCLUDE_DIR})
list(APPEND EXTERNAL_LIBS ${TENSORRT_LIBRARY})
add_definitions(-DPADDLE_WITH_TENSORRT)
endif()
paddle/contrib/float16/run_float16_demo.sh
浏览文件 @ 23560d08
......@@ -14,9 +14,7 @@ cmake .. -DWITH_AVX=OFF \
-DWITH_MKL=OFF \
-DWITH_GPU=ON \
-DWITH_TESTING=ON \
-DWITH_TIMER=ON \
-DWITH_PROFILER=ON \
-DWITH_FLUID_ONLY=ON
make -j `nproc`
pip install -U "$WHEEL_PATH/$(ls $WHEEL_PATH)"
......
paddle/fluid/API.spec
浏览文件 @ 23560d08
......@@ -71,7 +71,7 @@ paddle.fluid.initializer.NumpyArrayInitializer.__init__ ArgSpec(args=['self', 'v
paddle.fluid.layers.fc ArgSpec(args=['input', 'size', 'num_flatten_dims', 'param_attr', 'bias_attr', 'act', 'is_test', 'name'], varargs=None, keywords=None, defaults=(1, None, None, None, False, None))
paddle.fluid.layers.embedding ArgSpec(args=['input', 'size', 'is_sparse', 'is_distributed', 'padding_idx', 'param_attr', 'dtype'], varargs=None, keywords=None, defaults=(False, False, None, None, 'float32'))
paddle.fluid.layers.dynamic_lstm ArgSpec(args=['input', 'size', 'h_0', 'c_0', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'float32', None))
paddle.fluid.layers.dynamic_lstmp ArgSpec(args=['input', 'size', 'proj_size', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None))
paddle.fluid.layers.dynamic_lstmp ArgSpec(args=['input', 'size', 'proj_size', 'param_attr', 'bias_attr', 'use_peepholes', 'is_reverse', 'gate_activation', 'cell_activation', 'candidate_activation', 'proj_activation', 'dtype', 'name', 'h_0', 'c_0', 'cell_clip', 'proj_clip'], varargs=None, keywords=None, defaults=(None, None, True, False, 'sigmoid', 'tanh', 'tanh', 'tanh', 'float32', None, None, None, None, None))
paddle.fluid.layers.dynamic_gru ArgSpec(args=['input', 'size', 'param_attr', 'bias_attr', 'is_reverse', 'gate_activation', 'candidate_activation', 'h_0', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, False, 'sigmoid', 'tanh', None, False))
paddle.fluid.layers.gru_unit ArgSpec(args=['input', 'hidden', 'size', 'param_attr', 'bias_attr', 'activation', 'gate_activation', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, 'tanh', 'sigmoid', False))
paddle.fluid.layers.linear_chain_crf ArgSpec(args=['input', 'label', 'param_attr'], varargs=None, keywords=None, defaults=(None,))
......@@ -121,6 +121,7 @@ paddle.fluid.layers.sequence_reshape ArgSpec(args=['input', 'new_dim'], varargs=
paddle.fluid.layers.transpose ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,))
paddle.fluid.layers.im2sequence ArgSpec(args=['input', 'filter_size', 'stride', 'padding', 'input_image_size', 'out_stride', 'name'], varargs=None, keywords=None, defaults=(1, 1, 0, None, 1, None))
paddle.fluid.layers.nce ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False))
paddle.fluid.layers.sampled_softmax_with_cross_entropy ArgSpec(args=['logits', 'label', 'num_samples', 'num_true', 'remove_accidental_hits', 'use_customized_samples', 'customized_samples', 'customized_probabilities', 'seed'], varargs=None, keywords=None, defaults=(1, True, False, None, None, 0))
paddle.fluid.layers.hsigmoid ArgSpec(args=['input', 'label', 'num_classes', 'param_attr', 'bias_attr', 'name', 'path_table', 'path_code', 'is_custom', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, False, False))
paddle.fluid.layers.beam_search ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 'scores', 'beam_size', 'end_id', 'level', 'is_accumulated', 'name', 'return_parent_idx'], varargs=None, keywords=None, defaults=(0, True, None, False))
paddle.fluid.layers.row_conv ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None))
......@@ -427,7 +428,7 @@ paddle.fluid.optimizer.MomentumOptimizer.__init__ ArgSpec(args=['self', 'learnin
paddle.fluid.optimizer.MomentumOptimizer.apply_gradients ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None)
paddle.fluid.optimizer.MomentumOptimizer.backward ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None))
paddle.fluid.optimizer.MomentumOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
paddle.fluid.optimizer.AdagradOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'epsilon', 'regularization', 'name'], varargs=None, keywords=None, defaults=(1e-06, None, None))
paddle.fluid.optimizer.AdagradOptimizer.__init__ ArgSpec(args=['self', 'learning_rate', 'epsilon', 'regularization', 'name', 'initial_accumulator_value'], varargs=None, keywords=None, defaults=(1e-06, None, None, 0.0))
paddle.fluid.optimizer.AdagradOptimizer.apply_gradients ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None)
paddle.fluid.optimizer.AdagradOptimizer.backward ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set', 'callbacks'], varargs=None, keywords=None, defaults=(None, None, None, None))
paddle.fluid.optimizer.AdagradOptimizer.minimize ArgSpec(args=['self', 'loss', 'startup_program', 'parameter_list', 'no_grad_set'], varargs=None, keywords=None, defaults=(None, None, None))
......
paddle/fluid/framework/details/all_reduce_deps_pass.cc
浏览文件 @ 23560d08
......@@ -30,8 +30,6 @@ namespace paddle {
namespace framework {
namespace details {
static constexpr char kAllOpDescs[] = "all_op_descs";
VarHandle* GetValidInput(const OpHandleBase* a) {
for (auto p : a->Inputs()) {
VarHandle* b = dynamic_cast<VarHandle*>(p);
......
paddle/fluid/framework/details/all_reduce_op_handle.cc
浏览文件 @ 23560d08
......@@ -53,7 +53,7 @@ AllReduceOpHandle::AllReduceOpHandle(ir::Node *node,
#endif
void AllReduceOpHandle::RunImpl() {
platform::RecordEvent record_event(Name(), dev_ctxes_.cbegin()->second);
platform::RecordEvent record_event(Name());
WaitInputVarGenerated();
auto in_var_handles = DynamicCast<VarHandle>(this->Inputs());
......
paddle/fluid/framework/details/broadcast_op_handle.cc
浏览文件 @ 23560d08
......@@ -22,7 +22,7 @@ namespace framework {
namespace details {
void BroadcastOpHandle::RunImpl() {
platform::RecordEvent record_event(Name(), dev_ctxes_.begin()->second);
platform::RecordEvent record_event(Name());
if (places_.size() == 1) return;
......@@ -30,7 +30,7 @@ void BroadcastOpHandle::RunImpl() {
VarHandle *in_var_handle;
{
auto in_var_handles = DynamicCast<VarHandle>(inputs_);
PADDLE_ENFORCE_EQ(in_var_handles.size(), 1,
PADDLE_ENFORCE_EQ(in_var_handles.size(), 1UL,
"The number of input should be one.");
in_var_handle = in_var_handles[0];
}
......
paddle/fluid/framework/details/build_strategy.cc
浏览文件 @ 23560d08
......@@ -34,9 +34,11 @@ namespace details {
static inline bool SeqOnlyAllReduceOps(const BuildStrategy &strategy) {
// Should fix the allreduce op order if scheduling
// them in multiple threads or processes to avoid hang.
// NOTE: ParallelGraph would execute this pass on each graph, so
// don't need to append it here.
return (!strategy.enable_sequential_execution_ &&
strategy.num_trainers_ > 1) ||
strategy.enable_parallel_graph_;
strategy.num_trainers_ > 1) &&
!strategy.enable_parallel_graph_;
}
class ParallelExecutorPassBuilder : public ir::PassBuilder {
......@@ -133,12 +135,15 @@ class ParallelExecutorPassBuilder : public ir::PassBuilder {
void AppendMultiDevPass(const BuildStrategy &strategy) {
ir::Pass *multi_devices_pass;
if (strategy_.is_distribution_) {
VLOG(3) << "multi device parameter server mode";
multi_devices_pass = AppendPass("dist_multi_devices_pass").get();
} else {
if (strategy.reduce_ == BuildStrategy::ReduceStrategy::kAllReduce) {
VLOG(3) << "multi devices collective mode with allreduce";
multi_devices_pass =
AppendPass("allreduce_mode_multi_devices_pass").get();
} else if (strategy.reduce_ == BuildStrategy::ReduceStrategy::kReduce) {
VLOG(3) << "multi deivces collective mode with reduce";
multi_devices_pass = AppendPass("reduce_mode_multi_devices_pass").get();
} else {
PADDLE_THROW("Unknown reduce strategy.");
......
paddle/fluid/framework/details/data_balance_op_handle.cc
浏览文件 @ 23560d08
......@@ -86,7 +86,7 @@ std::vector<std::array<int, 3>> DataBalanceOpHandle::GetBalancePlan(
}
void DataBalanceOpHandle::RunImpl() {
PADDLE_ENFORCE_GT(places_.size(), 1,
PADDLE_ENFORCE_GT(places_.size(), 1UL,
"Data balance can only be enabled when the number of "
"places to run larger than 1.");
auto in_var_handles = DynamicCast<VarHandle>(this->Inputs());
......
paddle/fluid/framework/details/fuse_vars_op_handle.cc
浏览文件 @ 23560d08
......@@ -23,7 +23,7 @@ void FuseVarsOpHandle::RunImpl() {
auto in_var_handles = DynamicCast<VarHandle>(this->Inputs());
auto out_var_handles = DynamicCast<VarHandle>(this->Outputs());
PADDLE_ENFORCE_EQ(in_var_handles.size(), 0);
PADDLE_ENFORCE_EQ(in_var_handles.size(), 0UL);
PADDLE_ENFORCE_EQ(out_var_handles.size() - 1, inputs_numel_.size(), "");
auto scope = local_scope_->FindVar(kLocalExecScopeName)->Get<Scope *>();
......
paddle/fluid/framework/details/fused_broadcast_op_handle.cc
浏览文件 @ 23560d08
......@@ -22,7 +22,7 @@ namespace framework {
namespace details {
void FusedBroadcastOpHandle::RunImpl() {
platform::RecordEvent record_event(Name(), dev_ctxes_.begin()->second);
platform::RecordEvent record_event(Name());
if (places_.size() == 1UL) return;
......
paddle/fluid/framework/details/memory_optimize_helper.cc
浏览文件 @ 23560d08
......@@ -129,7 +129,13 @@ size_t NodeSize(const VarDesc& node) {
}
size_t NodeSize(ir::Node* n) {
auto* desc = FindVarDescInBlock(n);
VarDesc* desc = nullptr;
// some op do not have block pointer
if (n->inputs[0]->Op() != nullptr) {
desc = FindVarDescInBlock(n);
} else {
desc = n->Var();
}
return NodeSize(*desc);
}
......
paddle/fluid/framework/details/memory_optimize_helper.h
浏览文件 @ 23560d08
......@@ -29,8 +29,6 @@ namespace paddle {
namespace framework {
namespace details {
constexpr char kAllOpDescs[] = "all_op_descs";
std::vector<ir::Node*> SortOpLikeDescOrder(const ir::Graph& graph);
// NOTE(dzh): A ordered set for node reuse in memory optimize.
......
paddle/fluid/framework/details/memory_optimize_pass.cc
浏览文件 @ 23560d08
......@@ -194,7 +194,8 @@ void MemoryOptimizePass::SubGraphOptimize(OpDesc* op_desc) const {
// effect. Because it is a single op in graph. No need to
// update the ir nodes.
sub_op_desc->Rename(var->Name(), cache->Name());
if (sub_op_desc->Block()->HasVar(var->Name())) {
if (sub_op_desc->Block() != nullptr &&
sub_op_desc->Block()->HasVar(var->Name())) {
sub_op_desc->Block()->RemoveVar(var->Name());
}
}
......@@ -235,7 +236,13 @@ void MemoryOptimizePass::RenameVarInGraphDesc(const std::string& var,
auto* op_desc = op->Op();
op_desc->RenameInput(var, cache_var);
op_desc->RenameOutput(var, cache_var);
if (op_desc->Block()->HasVar(var)) op_desc->Block()->RemoveVar(var);
if (op_desc->Block() != nullptr) {
op_desc->Block()->RemoveVar(var);
} else {
LOG(WARNING) << "op " << op->Name() << " not know its block."
<< "Is the op_desc created without block pointer? "
<< "Can not find " << var << " in Block(0)";
}
op_desc->Flush();
}
}
......
paddle/fluid/framework/details/multi_devices_graph_pass.cc
浏览文件 @ 23560d08
......@@ -392,20 +392,32 @@ void MultiDevSSAGraphBuilderBase::CreateComputationalOp(ir::Graph *result,
void MultiDevSSAGraphBuilderBase::CreateAllReduceOp(
ir::Graph *result, const std::string &og) const {
OpHandleBase *op_handle = nullptr;
auto append_allreduce_op = [&](
const std::vector<Scope *> &scopes,
const std::vector<platform::Place> &places) -> OpHandleBase * {
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
result->Get<GraphOps>(kGraphOps).emplace_back(new AllReduceOpHandle(
result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation),
local_scopes_, places_, nccl_ctxs_));
scopes, places, nccl_ctxs_));
#else
result->Get<GraphOps>(kGraphOps).emplace_back(new AllReduceOpHandle(
result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation),
local_scopes_, places_));
scopes, places));
#endif
auto *op_handle = result->Get<GraphOps>(kGraphOps).back();
return result->Get<GraphOps>(kGraphOps).back();
};
if (!strategy_.enable_parallel_graph_)
op_handle = append_allreduce_op(local_scopes_, places_);
for (size_t i = 0; i < places_.size(); ++i) {
auto &p = places_[i];
SetCommunicationContext(op_handle, p);
if (strategy_.enable_parallel_graph_) {
op_handle = append_allreduce_op({local_scopes_[i]}, {places_[i]});
}
SetCommunicationContext(op_handle, places_[i]);
auto &vars = result->Get<GraphVars>(kGraphVars)[i][og];
PADDLE_ENFORCE(!vars.empty());
auto &prev_grad = vars.back();
......@@ -413,7 +425,7 @@ void MultiDevSSAGraphBuilderBase::CreateAllReduceOp(
auto var =
new VarHandle(result->CreateEmptyNode(og, ir::Node::Type::kVariable),
vars.size(), i, og, p);
vars.size(), i, og, places_[i]);
vars.emplace_back(var);
op_handle->AddOutput(var);
}
......@@ -925,9 +937,21 @@ void DistSSAGraphBuilder::InsertCollectiveOp(ir::Graph *result,
}
void DistSSAGraphBuilder::InsertPostprocessOps(ir::Graph *result) const {
if (need_broadcast_var_ ||
(UseGPU() &&
strategy_.reduce_ == BuildStrategy::ReduceStrategy::kReduce)) {
// broad cast received parameters when training in parameter server mode.
if (need_broadcast_var_) {
// There are 4 conditions:
// 1. GPU && Reduce: Reduce gradient then broadcast gradient to other GPUS.
// Need to broadcast received parameters to other GPU.
// 2. GPU && AllReduce: AllReduce all graident to each GPU. Need to
// broadcast received parameters to other GPU.
// 3. CPU && AllReduce: AllReduce all gradient to each thread. Need to
// broadcast received parameters to other scope.
// 4. CPU && Reduce: because all parameters share the same memory, did not
// broadcast received parameters.
if (!UseGPU() &&
strategy_.reduce_ == BuildStrategy::ReduceStrategy::kReduce) {
return;
}
if (strategy_.fuse_broadcast_op_) {
CreateFusedBroadcastOp(result, bcast_var_name_set_);
} else {
......
paddle/fluid/framework/details/multi_devices_helper.h
浏览文件 @ 23560d08
......@@ -36,13 +36,14 @@ namespace details {
// map from variable name to variables. The variables, who have the same name,
// will have a differsent version. The offset in the
// `std::vector<VarHandle*>` is the version of varaibles.
typedef std::vector<std::unordered_map<std::string, std::vector<VarHandle*>>>
typedef std::vector<std::unordered_map<std::string, std::vector<VarHandle *>>>
GraphVars;
const char kGraphVars[] = "vars";
// aux variables to represent dependency. Useful to resolve data hazard.
typedef std::unordered_set<VarHandleBase*> GraphDepVars;
typedef std::unordered_set<VarHandleBase *> GraphDepVars;
const char kGraphDepVars[] = "dep_vars";
} // namespace details
} // namespace framework
} // namespace paddle
paddle/fluid/framework/details/op_handle_base.h
浏览文件 @ 23560d08
......@@ -70,6 +70,9 @@ class OpHandleBase {
auto it = dev_ctxes_.find(place);
return it != dev_ctxes_.end() ? it->second : nullptr;
}
const std::map<platform::Place, platform::DeviceContext *> &DeviceContext() {
return dev_ctxes_;
}
void SetDeviceContext(platform::Place place, platform::DeviceContext *ctx_) {
dev_ctxes_[place] = ctx_;
......
paddle/fluid/framework/details/parallel_ssa_graph_executor.cc
浏览文件 @ 23560d08
......@@ -13,22 +13,92 @@
// limitations under the License.
#include "paddle/fluid/framework/details/parallel_ssa_graph_executor.h"
#include "paddle/fluid/framework/ir/graph_helper.h"
namespace paddle {
namespace framework {
namespace details {
std::vector<std::unique_ptr<ir::Graph>>
ParallelSSAGraphExecutor::SeparateMultiDevicesGraph(
std::unique_ptr<ir::Graph> &&graph) {
std::vector<std::unique_ptr<ir::Graph>> graphs;
graphs.reserve(places_.size());
for (size_t i = 0; i < places_.size(); ++i) {
ProgramDesc empty;
graphs.emplace_back(std::unique_ptr<ir::Graph>(new ir::Graph(empty)));
auto &g = graphs.back();
g->Set(kGraphVars, new GraphVars(1UL));
g->Set(kGraphDepVars, new GraphDepVars);
}
auto op_handles = ir::FilterByNodeWrapper<OpHandleBase>(*graph);
for (auto &op : op_handles) {
auto &dev_ctx = op->DeviceContext();
auto &p = dev_ctx.begin()->first;
int dev_id = boost::get<platform::CUDAPlace>(p).device;
auto &dev_dummys = graphs[dev_id]->Get<GraphDepVars>(kGraphDepVars);
graphs[dev_id]->AddNode(graph->RemoveNode(op->Node()).release());
for (auto &var : op->Inputs()) {
auto dummy_ptr = dynamic_cast<DummyVarHandle *>(var);
if (dummy_ptr) {
dev_dummys.insert(var);
if (graph->Nodes().count(var->Node()))
graphs[dev_id]->AddNode(graph->RemoveNode(var->Node()).release());
}
}
for (auto &var : op->Outputs()) {
auto dummy_ptr = dynamic_cast<DummyVarHandle *>(var);
if (dummy_ptr) {
dev_dummys.insert(var);
if (graph->Nodes().count(var->Node()))
graphs[dev_id]->AddNode(graph->RemoveNode(var->Node()).release());
}
}
}
for (size_t dev_id = 0; dev_id < places_.size(); ++dev_id) {
auto &dev_vars = graphs[dev_id]->Get<GraphVars>(kGraphVars)[0];
auto &origin_vars = graph->Get<GraphVars>(kGraphVars)[dev_id];
for (auto &name_pair : origin_vars) {
dev_vars.emplace(name_pair.first, name_pair.second);
for (auto &version_pair : name_pair.second) {
if (graph->Nodes().count(version_pair->Node())) {
graphs[dev_id]->AddNode(
graph->RemoveNode(version_pair->Node()).release());
}
}
}
}
return graphs;
}
ParallelSSAGraphExecutor::ParallelSSAGraphExecutor(
const ExecutionStrategy &strategy, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
std::vector<std::unique_ptr<ir::Graph>> &&graphs)
const framework::ProgramDesc &main_prog, std::unique_ptr<ir::Graph> &&graph)
: strategy_(std::move(strategy)),
local_scopes_(std::move(local_scopes)),
pool_(places.size() >= 2 ? new ::ThreadPool(places.size()) : nullptr),
places_(std::move(places)),
graphs_(std::move(graphs)) {
main_prog_(main_prog),
// TODO(Yancey1989): Copying graphs is not safely since it deleted the
// attrs.
graphs_(SeparateMultiDevicesGraph(std::move(graph))) {
PADDLE_ENFORCE_EQ(places_.size(), local_scopes_.size());
auto seq_allreduce_pass =
ir::PassRegistry::Instance().Get("all_reduce_deps_pass");
seq_allreduce_pass->Erase(details::kAllOpDescs);
seq_allreduce_pass->Set<const std::vector<OpDesc *>>(
details::kAllOpDescs,
new std::vector<OpDesc *>(main_prog_.Block(0).AllOps()));
for (size_t i = 0; i < graphs_.size(); ++i) {
graphs_[i] = seq_allreduce_pass->Apply(std::move(graphs_[i]));
}
// set the correct size of thread pool to each device.
strategy_.num_threads_ = strategy_.num_threads_ < places_.size()
? 1UL
......@@ -37,7 +107,7 @@ ParallelSSAGraphExecutor::ParallelSSAGraphExecutor(
<< " to run the operators of the graph on each device.";
for (size_t i = 0; i < places.size(); ++i) {
executors_.emplace_back(new details::ThreadedSSAGraphExecutor(
strategy_, {local_scopes_[i]}, {places_[i]}, std::move(graphs_[i])));
strategy_, local_scopes_, {places_[i]}, std::move(graphs_.at(i))));
}
}
......
paddle/fluid/framework/details/parallel_ssa_graph_executor.h
浏览文件 @ 23560d08
......@@ -18,7 +18,9 @@
#include <vector>
#include "ThreadPool.h"
#include "paddle/fluid/framework/details/multi_devices_helper.h"
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
#include "paddle/fluid/framework/ir/graph.h"
namespace paddle {
namespace framework {
......@@ -29,17 +31,23 @@ class ParallelSSAGraphExecutor : public SSAGraphExecutor {
ParallelSSAGraphExecutor(const ExecutionStrategy &strategy,
const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
std::vector<std::unique_ptr<ir::Graph>> &&graphs);
const framework::ProgramDesc &main_prog,
std::unique_ptr<ir::Graph> &&graph);
~ParallelSSAGraphExecutor() final = default;
const ir::Graph &Graph() const override { return *graphs_[0]; }
FeedFetchList Run(const std::vector<std::string> &fetch_tensors) override;
private:
std::vector<std::unique_ptr<ir::Graph>> SeparateMultiDevicesGraph(
std::unique_ptr<ir::Graph> &&graph);
ExecutionStrategy strategy_;
std::vector<Scope *> local_scopes_;
std::unique_ptr<::ThreadPool> pool_{nullptr};
std::vector<platform::Place> places_;
framework::ProgramDesc main_prog_;
std::vector<std::unique_ptr<ir::Graph>> graphs_;
std::vector<std::unique_ptr<details::ThreadedSSAGraphExecutor>> executors_;
......
paddle/fluid/framework/details/reduce_op_handle.cc
浏览文件 @ 23560d08
......@@ -139,7 +139,7 @@ void ReduceOpHandle::GatherSelectedRows(
#endif
void ReduceOpHandle::RunImpl() {
platform::RecordEvent record_event(Name(), dev_ctxes_.cbegin()->second);
platform::RecordEvent record_event(Name());
if (places_.size() == 1) return;
// the input and output may have dummy var.
......@@ -153,7 +153,7 @@ void ReduceOpHandle::RunImpl() {
{
auto out_var_handles = DynamicCast<VarHandle>(outputs_);
PADDLE_ENFORCE_EQ(out_var_handles.size(), 1,
PADDLE_ENFORCE_EQ(out_var_handles.size(), 1UL,
"The number of output should be one.");
out_var_handle = out_var_handles.front();
}
......
paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc
浏览文件 @ 23560d08
......@@ -63,7 +63,7 @@ FeedFetchList ScopeBufferedSSAGraphExecutor::Run(
eptr = std::current_exception();
}
platform::RecordEvent e("ScopeBufferedSSAGraphExecutorAfterRun", nullptr);
platform::RecordEvent e("ScopeBufferedSSAGraphExecutorAfterRun");
++drop_scope_counter_;
bool stream_end = false;
......
paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
浏览文件 @ 23560d08
......@@ -37,7 +37,7 @@ ThreadedSSAGraphExecutor::ThreadedSSAGraphExecutor(
FeedFetchList ThreadedSSAGraphExecutor::Run(
const std::vector<std::string> &fetch_tensors) {
std::unique_ptr<platform::RecordEvent> event(
new platform::RecordEvent("ThreadedSSAGraphExecutorPrepare", nullptr));
new platform::RecordEvent("ThreadedSSAGraphExecutorPrepare"));
std::unordered_map<OpHandleBase *, size_t> pending_ops;
std::unordered_set<VarHandleBase *> pending_vars;
auto ready_vars = std::make_shared<BlockingQueue<VarHandleBase *>>();
......@@ -219,7 +219,7 @@ void ThreadedSSAGraphExecutor::RunOp(
VLOG(10) << op << " " << op->Name() << " Done ";
running_ops_--;
ready_var_q->Extend(op->Outputs());
VLOG(10) << op << " " << op->Name() << "Signal posted";
VLOG(10) << op << " " << op->Name() << " Signal posted";
} catch (...) {
exception_holder_.Catch(std::current_exception());
}
......
paddle/fluid/framework/ir/CMakeLists.txt
浏览文件 @ 23560d08
......@@ -102,6 +102,7 @@ cc_test(test_seqpool_concat_fuse_pass SRCS seqpool_concat_fuse_pass_tester.cc DE
cc_test(test_is_test_pass SRCS is_test_pass_tester.cc DEPS is_test_pass)
if (WITH_MKLDNN)
cc_test(test_depthwise_conv_mkldnn_pass SRCS mkldnn/depthwise_conv_mkldnn_pass_tester.cc DEPS depthwise_conv_mkldnn_pass)
cc_test(test_conv_bias_mkldnn_fuse_pass SRCS mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc DEPS conv_bias_mkldnn_fuse_pass naive_executor)
cc_test(test_conv_relu_mkldnn_fuse_pass SRCS mkldnn/conv_relu_mkldnn_fuse_pass_tester.cc DEPS conv_relu_mkldnn_fuse_pass)
cc_test(test_conv_elementwise_add_mkldnn_fuse_pass SRCS mkldnn/conv_elementwise_add_mkldnn_fuse_pass_tester.cc DEPS conv_elementwise_add_mkldnn_fuse_pass)
endif ()
paddle/fluid/framework/ir/attention_lstm_fuse_pass.h
浏览文件 @ 23560d08
......@@ -22,7 +22,8 @@ namespace ir {
class AttentionLSTMFusePass : public FusePassBase {
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.h
浏览文件 @ 23560d08
......@@ -31,7 +31,8 @@ class ConvAffineChannelFusePass : public FusePassBase {
virtual ~ConvAffineChannelFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"conv_affine_channel_fuse"};
};
......@@ -40,7 +41,8 @@ class ConvEltwiseAddAffineChannelFusePass : public FusePassBase {
virtual ~ConvEltwiseAddAffineChannelFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"conv_eltwiseadd_affine_channel_fuse"};
};
......
paddle/fluid/framework/ir/conv_bn_fuse_pass.cc
浏览文件 @ 23560d08
......@@ -169,7 +169,7 @@ std::unique_ptr<ir::Graph> ConvBNFusePass::ApplyImpl(
if (has_bias && conv->Op()->Input("Bias").size() > 0) {
// reuse existing conv bias node
auto conv_bias_names = conv->Op()->Input("Bias");
PADDLE_ENFORCE_EQ(conv_bias_names.size(), 1);
PADDLE_ENFORCE_EQ(conv_bias_names.size(), 1UL);
auto* conv_bias_var = scope->FindVar(conv_bias_names[0]);
auto* conv_bias_tensor = conv_bias_var->GetMutable<LoDTensor>();
PADDLE_ENFORCE_EQ(conv_bias_tensor->dims(),
......
paddle/fluid/framework/ir/conv_bn_fuse_pass.h
浏览文件 @ 23560d08
......@@ -31,7 +31,8 @@ class ConvBNFusePass : public FusePassBase {
virtual ~ConvBNFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"conv_bn_fuse"};
};
......@@ -40,7 +41,8 @@ class ConvEltwiseAddBNFusePass : public FusePassBase {
virtual ~ConvEltwiseAddBNFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"conv_eltwiseadd_bn_fuse"};
};
......
paddle/fluid/framework/ir/conv_elementwise_add2_act_fuse_pass.h
浏览文件 @ 23560d08
......@@ -25,7 +25,8 @@ class ConvElementwiseAdd2ActFusePass : public FusePassBase {
virtual ~ConvElementwiseAdd2ActFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/ir/conv_elementwise_add_act_fuse_pass.h
浏览文件 @ 23560d08
......@@ -25,7 +25,8 @@ class ConvElementwiseAddActFusePass : public FusePassBase {
virtual ~ConvElementwiseAddActFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h
浏览文件 @ 23560d08
......@@ -25,7 +25,8 @@ class ConvElementwiseAddFusePass : public FusePassBase {
virtual ~ConvElementwiseAddFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/ir/embedding_fc_lstm_fuse_pass.h
浏览文件 @ 23560d08
......@@ -14,6 +14,8 @@
#pragma once
#include <string>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
......@@ -30,7 +32,8 @@ class EmbeddingFCLSTMFusePass : public FusePassBase {
virtual ~EmbeddingFCLSTMFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"embedding_fc_lstm_fuse"};
};
......
paddle/fluid/framework/ir/fc_fuse_pass.h
浏览文件 @ 23560d08
......@@ -12,6 +12,8 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
......@@ -29,7 +31,8 @@ class FCFusePass : public FusePassBase {
virtual ~FCFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/ir/fc_gru_fuse_pass.h
浏览文件 @ 23560d08
......@@ -30,7 +30,8 @@ class FCGRUFusePass : public FusePassBase {
virtual ~FCGRUFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"fc_gru_fuse"};
};
......@@ -41,7 +42,8 @@ class MulGRUFusePass : public FusePassBase {
virtual ~MulGRUFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"fc_nobias_gru_fuse"};
};
......
paddle/fluid/framework/ir/fc_lstm_fuse_pass.h
浏览文件 @ 23560d08
......@@ -14,6 +14,8 @@
#pragma once
#include <string>
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
......@@ -30,7 +32,8 @@ class FCLstmFusePass : public FusePassBase {
virtual ~FCLstmFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"fc_lstm_fuse"};
};
......@@ -40,7 +43,8 @@ class MulLstmFusePass : public FusePassBase {
virtual ~MulLstmFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"fc_nobias_lstm_fuse"};
};
......
paddle/fluid/framework/ir/fuse_elewise_add_act_pass.h
浏览文件 @ 23560d08
......@@ -32,7 +32,8 @@ class FuseElewiseAddActPass : public FusePassBase {
virtual ~FuseElewiseAddActPass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
std::unique_ptr<ir::Graph> FuseElewiseAddAct(
std::unique_ptr<ir::Graph> graph,
......
paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.cc
浏览文件 @ 23560d08
......@@ -111,7 +111,7 @@ std::unique_ptr<ir::Graph> FuseReluDepthwiseConvPass::FuseReluDepthwiseConv(
xg_var = subgraph.at(xg)->Var();
}
PADDLE_ENFORCE_EQ(layer_op->Input("Input").size(), 1);
PADDLE_ENFORCE_EQ(layer_op->Input("Input").size(), 1UL);
PADDLE_ENFORCE_EQ(layer_op->Input("Input")[0], y_var->Name());
layer_op->SetInput("Input", {x_var->Name()});
subgraph.at(layer)->inputs.push_back(subgraph.at(x));
......@@ -119,13 +119,13 @@ std::unique_ptr<ir::Graph> FuseReluDepthwiseConvPass::FuseReluDepthwiseConv(
VLOG(4) << "replace " << y_var->Name() << " -> " << x_var->Name();
if (!only_forward) {
PADDLE_ENFORCE_EQ(layer_g_op->Input("Input").size(), 1);
PADDLE_ENFORCE_EQ(layer_g_op->Input("Input").size(), 1UL);
PADDLE_ENFORCE_EQ(layer_g_op->Input("Input")[0], y_var->Name());
layer_g_op->SetInput("Input", {x_var->Name()});
subgraph.at(layer_g)->inputs.push_back(subgraph.at(x));
subgraph.at(x)->outputs.push_back(subgraph.at(layer_g));
PADDLE_ENFORCE_EQ(layer_g_op->Output(GradVarName("Input")).size(), 1);
PADDLE_ENFORCE_EQ(layer_g_op->Output(GradVarName("Input")).size(), 1UL);
PADDLE_ENFORCE_EQ(layer_g_op->Output(GradVarName("Input"))[0],
yg_var->Name());
layer_g_op->SetOutput(GradVarName("Input"), {xg_var->Name()});
......
paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.h
浏览文件 @ 23560d08
......@@ -32,7 +32,8 @@ class FuseReluDepthwiseConvPass : public FusePassBase {
virtual ~FuseReluDepthwiseConvPass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
std::unique_ptr<ir::Graph> FuseReluDepthwiseConv(
std::unique_ptr<ir::Graph> graph, bool only_forward) const;
};
......
paddle/fluid/framework/ir/graph.h
浏览文件 @ 23560d08
......@@ -26,6 +26,14 @@ limitations under the License. */
namespace paddle {
namespace framework {
namespace details {
// This attr is not recommended, because the graph should not dependence
// the program once it is built.
constexpr char kAllOpDescs[] = "all_op_descs";
} // namespace details
namespace ir {
/*
......@@ -168,10 +176,13 @@ class Graph {
return ret;
}
void RemoveNode(ir::Node *node) {
std::unique_ptr<ir::Node> RemoveNode(ir::Node *node) {
PADDLE_ENFORCE(node_set_.find(node) != node_set_.end());
node_set_.erase(node);
std::unique_ptr<ir::Node> ret;
ret.reset(nodes_.at(node).release());
nodes_.erase(node);
node_set_.erase(node);
return ret;
}
// NOTE low performance, but simple and secure.
......@@ -184,13 +195,6 @@ class Graph {
return nullptr;
}
void ResolveHazard(
const std::map<std::string, std::vector<ir::Node *>> &var_nodes);
private:
std::map<std::string, std::vector<ir::Node *>> InitFromProgram(
const ProgramDesc &program);
// This method takes ownership of `node`.
ir::Node *AddNode(ir::Node *node) {
PADDLE_ENFORCE(node_set_.find(node) == node_set_.end());
......@@ -199,6 +203,13 @@ class Graph {
return node;
}
void ResolveHazard(
const std::map<std::string, std::vector<ir::Node *>> &var_nodes);
private:
std::map<std::string, std::vector<ir::Node *>> InitFromProgram(
const ProgramDesc &program);
// NOTE: program_ shouldn't be exposed to user.
const ProgramDesc program_;
std::map<std::string, boost::any> attrs_;
......
paddle/fluid/framework/ir/graph_pattern_detector.cc
浏览文件 @ 23560d08
......@@ -38,7 +38,7 @@ size_t PDPattern::id_ = 0UL;
PDNode *PDPattern::NewNode(const std::string &name) {
if (!name.empty()) {
PADDLE_ENFORCE_EQ(node_map_.count(name), 0,
PADDLE_ENFORCE_EQ(node_map_.count(name), 0UL,
"PDNode's name should be unique, get duplicate [%s]",
name);
}
......@@ -51,7 +51,7 @@ PDNode *PDPattern::NewNode(const std::string &name) {
PDNode *PDPattern::NewNode(PDNode::teller_t &&teller, const std::string &name) {
if (!name.empty()) {
PADDLE_ENFORCE_EQ(node_map_.count(name), 0,
PADDLE_ENFORCE_EQ(node_map_.count(name), 0UL,
"PDNode's name should be unique, get duplicate [%s]",
name);
}
......
paddle/fluid/framework/ir/identity_scale_op_clean_pass.h
浏览文件 @ 23560d08
......@@ -22,7 +22,8 @@ namespace ir {
class IdentityScaleOpCleanPass : public FusePassBase {
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
private:
virtual ~IdentityScaleOpCleanPass() = default;
......
paddle/fluid/framework/ir/lock_free_optimize_pass.h
浏览文件 @ 23560d08
......@@ -60,7 +60,8 @@ class LockFreeOptimizePass : public Pass {
virtual ~LockFreeOptimizePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
private:
// Create a new sgd node via current optimizer node
......
paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.h
浏览文件 @ 23560d08
......@@ -29,7 +29,8 @@ class ConvBiasFusePass : public FusePassBase {
virtual bool is_conv3d() const { return false; }
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"conv_bias_mkldnn_fuse"};
};
/*
......
paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc 0 → 100644
浏览文件 @ 23560d08
// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// 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/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.h"
#include "paddle/fluid/framework/naive_executor.h"
#include "paddle/fluid/platform/place.h"
#include <gtest/gtest.h>
#include "paddle/fluid/framework/op_proto_maker.h"
namespace paddle {
namespace framework {
namespace ir {
void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
const std::vector<std::string>& inputs,
const std::vector<std::string>& outputs) {
auto* op = prog->MutableBlock(0)->AppendOp();
op->SetType(type);
if (type == "conv2d") {
op->SetAttr("use_mkldnn", true);
op->SetAttr("name", name);
op->SetInput("Input", {inputs[0]});
op->SetInput("Filter", {inputs[1]});
if (inputs.size() > 2)
op->SetInput("Bias", {inputs[2]});
else
op->SetInput("Bias", {});
} else if (type == "elementwise_add") {
op->SetAttr("use_mkldnn", true);
op->SetInput("X", {inputs[0]});
op->SetInput("Y", {inputs[1]});
}
op->SetOutput("Out", outputs);
op->SetAttr(OpProtoAndCheckerMaker::OpRoleAttrName(),
static_cast<int>(OpRole::kForward));
}
// (c, weights)->conv->f
// (f)->elementwise_add->g
ProgramDesc BuildProgramDesc(bool convWithExistingBias) {
ProgramDesc prog;
std::vector<std::string> nodes{"c", "weights", "f", "eltwise_bias", "g"};
if (convWithExistingBias) nodes.push_back("conv_bias");
for (auto& v : nodes) {
auto* var = prog.MutableBlock(0)->Var(v);
var->SetType(proto::VarType::LOD_TENSOR);
if (v == "weights" || v == "conv_bias" || v == "eltwise_bias") {
var->SetPersistable(true);
}
}
// conv+bias, both with MKL-DNN
if (convWithExistingBias) {
SetOp(&prog, "conv2d", "conv",
std::vector<std::string>({"c", "weights", "conv_bias"}),
std::vector<std::string>({"f"}));
} else {
SetOp(&prog, "conv2d", "conv", std::vector<std::string>({"c", "weights"}),
std::vector<std::string>({"f"}));
}
SetOp(&prog, "elementwise_add", "eltwise",
std::vector<std::string>({"f", "eltwise_bias"}),
std::vector<std::string>({"g"}));
return prog;
}
void InitTensorHolder(Scope* scope, const paddle::platform::Place& place,
const char* var_name) {
auto x = scope->Var(var_name);
auto tensor = x->GetMutable<LoDTensor>();
tensor->mutable_data(place, proto::VarType::FP32,
::paddle::memory::Allocator::kDefault, 1);
}
void MainTest(bool convWithExistingBias) {
auto prog = BuildProgramDesc(convWithExistingBias);
std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
auto place = paddle::platform::CPUPlace();
NaiveExecutor exe{place};
Scope scope;
// Init scope, as it is used in pass
exe.CreateVariables(prog, 0, true, &scope);
if (convWithExistingBias) {
InitTensorHolder(&scope, place, "conv_bias");
InitTensorHolder(&scope, place, "eltwise_bias");
}
graph->Set(kParamScopeAttr, new framework::Scope*(&scope));
auto pass = PassRegistry::Instance().Get("conv_bias_mkldnn_fuse_pass");
int original_nodes_num = graph->Nodes().size();
graph = pass->Apply(std::move(graph));
int current_nodes_num = graph->Nodes().size();
// Remove 3 Nodes: Conv, Bias, conv_out
// Add 1 Node: ConvBias
EXPECT_EQ(original_nodes_num - 2, current_nodes_num);
// Assert conv_bias op in newly generated graph
int conv_bias_count = 0;
for (auto* node : graph->Nodes()) {
if (node->IsOp() && node->Op()->Type() == "conv2d") {
auto* op = node->Op();
ASSERT_TRUE(op->HasAttr("use_mkldnn"));
EXPECT_TRUE(boost::get<bool>(op->GetAttr("use_mkldnn")));
// check if "conv" convolution is fused
auto op_name = boost::get<std::string>(op->GetAttr("name"));
if (op_name == "conv") {
auto input_names = op->InputNames();
ASSERT_TRUE(std::find(input_names.begin(), input_names.end(), "Bias") !=
input_names.end());
auto bias = boost::get<std::vector<std::string>>(op->Input("Bias"));
if (bias.size()) {
++conv_bias_count;
}
}
}
}
EXPECT_EQ(conv_bias_count, 1);
}
TEST(ConvBiasFusePass, bias_free_conv) { MainTest(false); }
TEST(ConvBiasFusePass, conv_with_existing_bias) { MainTest(true); }
TEST(ConvBiasFusePass, conv3d) {
Conv3DBiasFusePass pass;
ASSERT_TRUE(pass.is_conv3d());
}
} // namespace ir
} // namespace framework
} // namespace paddle
USE_PASS(conv_bias_mkldnn_fuse_pass);
paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.h
浏览文件 @ 23560d08
......@@ -31,7 +31,8 @@ class RepeatedFCReluFusePass : public FusePassBase {
virtual ~RepeatedFCReluFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"repeated_fc_relu_fuse"};
};
......
paddle/fluid/framework/ir/seq_concat_fc_fuse_pass.h
浏览文件 @ 23560d08
......@@ -12,6 +12,8 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "paddle/fluid/framework/ir/fuse_pass_base.h"
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/ir/pass.h"
......@@ -25,7 +27,8 @@ class SeqConcatFcFusePass : public FusePassBase {
virtual ~SeqConcatFcFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/ir/seqconv_eltadd_relu_fuse_pass.h
浏览文件 @ 23560d08
......@@ -28,7 +28,8 @@ class SeqConvEltAddReluFusePass : public FusePassBase {
virtual ~SeqConvEltAddReluFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"seqconv_eltadd_relu_fuse"};
};
......
paddle/fluid/framework/ir/seqpool_concat_fuse_pass.h
浏览文件 @ 23560d08
......@@ -42,7 +42,8 @@ class SeqPoolConcatFusePass : public FusePassBase {
virtual ~SeqPoolConcatFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"seqpool_concat_fuse"};
};
......
paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h
浏览文件 @ 23560d08
......@@ -31,7 +31,8 @@ class SquaredMatSubFusePass : public FusePassBase {
virtual ~SquaredMatSubFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
const std::string name_scope_{"squared_mat_sub_fuse"};
};
......
paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.h
浏览文件 @ 23560d08
......@@ -30,7 +30,8 @@ class TransposeFlattenConcatFusePass : public FusePassBase {
virtual ~TransposeFlattenConcatFusePass() {}
protected:
std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
std::unique_ptr<ir::Graph> ApplyImpl(
std::unique_ptr<ir::Graph> graph) const override;
};
} // namespace ir
......
paddle/fluid/framework/op_proto_maker.h
浏览文件 @ 23560d08
......@@ -27,7 +27,7 @@ enum class OpRole {
kForward = 0x0000,
kBackward = 0x0001,
kOptimize = 0x0002,
// RPC role is for send/recv releated op
// RPC role is for send/recv related op
kRPC = 0x0004,
// Dist role is for split_byref/split_selected_rows/concat
// used for distributed training.
......
paddle/fluid/framework/operator.cc
浏览文件 @ 23560d08
......@@ -177,9 +177,7 @@ void OperatorBase::Run(const Scope& scope, const platform::Place& place) {
// in concurrency scenerio. Here use an `if` to fix this issue.
// Please not remove the `if`, ask @Superjomn if there are any concern.
if (platform::IsProfileEnabled()) {
platform::DeviceContextPool& pool =
platform::DeviceContextPool::Instance();
platform::RecordEvent record_event(Type(), pool.Get(place));
platform::RecordEvent record_event(Type());
RunImpl(scope, place);
} else {
RunImpl(scope, place);
......
paddle/fluid/framework/parallel_executor.cc
浏览文件 @ 23560d08
......@@ -21,6 +21,7 @@ limitations under the License. */
#include "paddle/fluid/framework/ir/graph.h"
#include "paddle/fluid/framework/details/all_reduce_deps_pass.h"
#include "paddle/fluid/framework/details/fast_threaded_ssa_graph_executor.h"
#include "paddle/fluid/framework/details/multi_devices_helper.h"
#include "paddle/fluid/framework/details/parallel_ssa_graph_executor.h"
......@@ -193,7 +194,6 @@ ParallelExecutor::ParallelExecutor(
member_->use_all_reduce_ =
build_strategy.reduce_ == BuildStrategy::ReduceStrategy::kAllReduce;
member_->nranks_ = build_strategy.num_trainers_ * places.size();
if (!member_->use_all_reduce_) {
PADDLE_ENFORCE(places.size() > 1,
"If you set build_strategy.reduce with 'Reduce',"
......@@ -221,9 +221,10 @@ ParallelExecutor::ParallelExecutor(
// choice the execution strategy.
build_strategy.enable_parallel_graph_ =
EnableParallelGraphExecution(main_program, exec_strategy, build_strategy);
VLOG(1) << "Enable ParallelGraph Execution: "
<< build_strategy.enable_parallel_graph_;
if (build_strategy.enable_parallel_graph_)
VLOG(0) << "The Executor would execute the graph by ParallelGraph "
"Execution which can get better performance,"
<< "you can force it off by env FLAGS_enable_parallel_graph=0";
if (member_->use_cuda_) {
// Bcast Parameters to all GPUs
......@@ -257,42 +258,27 @@ ParallelExecutor::ParallelExecutor(
// Step 2. Convert main_program to SSA form and dependency graph. Also, insert
// ncclOp
std::vector<std::unique_ptr<ir::Graph>> graphs;
std::unique_ptr<ir::Graph> graph;
#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
if (build_strategy.enable_parallel_graph_) {
for (size_t i = 0; i < member_->places_.size(); ++i) {
std::unique_ptr<ir::Graph> graph = build_strategy.Apply(
main_program, {member_->places_[i]}, loss_var_name,
{member_->local_scopes_[i]}, member_->nranks_, member_->use_cuda_,
member_->nccl_ctxs_.get());
graphs.push_back(std::move(graph));
}
} else {
std::unique_ptr<ir::Graph> graph = build_strategy.Apply(
main_program, member_->places_, loss_var_name, member_->local_scopes_,
member_->nranks_, member_->use_cuda_, member_->nccl_ctxs_.get());
graphs.push_back(std::move(graph));
}
graph = build_strategy.Apply(main_program, member_->places_, loss_var_name,
member_->local_scopes_, member_->nranks_,
member_->use_cuda_, member_->nccl_ctxs_.get());
#else
std::unique_ptr<ir::Graph> graph = build_strategy.Apply(
main_program, member_->places_, loss_var_name, member_->local_scopes_,
member_->nranks_, member_->use_cuda_);
graphs.push_back(std::move(graph));
graph = build_strategy.Apply(main_program, member_->places_, loss_var_name,
member_->local_scopes_, member_->nranks_,
member_->use_cuda_);
#endif
auto max_memory_size = GetEagerDeletionThreshold();
VLOG(10) << "Eager Deletion Threshold "
<< static_cast<float>(max_memory_size) / (1 << 30);
if (max_memory_size >= 0) {
for (size_t i = 0; i < graphs.size(); ++i) {
graphs[i] = member_->PrepareGCAndRefCnts(
std::move(graphs[i]), static_cast<size_t>(max_memory_size));
}
graph = member_->PrepareGCAndRefCnts(std::move(graph),
static_cast<size_t>(max_memory_size));
}
// Step 3. Create vars in each scope. Passes may also create new vars.
// skip control vars and empty vars
std::vector<details::VariableInfo> var_infos;
for (auto &graph : graphs) {
for (auto &node : graph->Nodes()) {
if (node->IsVar() && !node->IsCtrlVar() && node->Var()) {
var_infos.emplace_back();
......@@ -301,16 +287,15 @@ ParallelExecutor::ParallelExecutor(
var_infos.back().persistable_ = node->Var()->Persistable();
}
}
}
// If the loss_var_name is given, the number of graph should be only one.
if (loss_var_name.size()) {
size_t graph_num = ir::GraphNum(*graphs[0]);
size_t graph_num = ir::GraphNum(*graph);
if (graph_num > 1) {
LOG(WARNING)
<< "The number of graph should be only one, "
"but the current graph has "
<< ir::GraphNum(*graphs[0])
<< ir::GraphNum(*graph)
<< " sub_graphs. If you want to see the nodes of the "
"sub_graphs, you should use 'FLAGS_print_sub_graph_dir' "
"to specify the output dir. NOTES: if you not do training, "
......@@ -319,18 +304,25 @@ ParallelExecutor::ParallelExecutor(
}
if (build_strategy.enable_parallel_graph_) {
#ifdef PADDLE_WITH_CUDA
// TODO(Yancey1989): Remove passing in the main_program when
// allreduce_seq_pass doesn't need it as the attr.
member_->executor_.reset(new details::ParallelSSAGraphExecutor(
exec_strategy, member_->local_scopes_, member_->places_,
std::move(graphs)));
exec_strategy, member_->local_scopes_, member_->places_, main_program,
std::move(graph)));
#else
PADDLE_THROW(
"Paddle should be compiled with CUDA for ParallelGraph Execution.");
#endif
} else {
if (exec_strategy.type_ == ExecutionStrategy::kDefault) {
member_->executor_.reset(new details::ThreadedSSAGraphExecutor(
exec_strategy, member_->local_scopes_, member_->places_,
std::move(graphs[0])));
std::move(graph)));
} else {
member_->executor_.reset(new details::FastThreadedSSAGraphExecutor(
exec_strategy, member_->local_scopes_, member_->places_,
std::move(graphs[0])));
std::move(graph)));
}
}
......@@ -482,7 +474,6 @@ bool ParallelExecutor::EnableParallelGraphExecution(
}
if (!member_->use_all_reduce_ || !member_->use_cuda_)
enable_parallel_graph = false;
if (build_strategy.enable_sequential_execution_ ||
exec_strategy.type_ == ExecutionStrategy::ExecutorType::kExperimental)
......
paddle/fluid/inference/api/analysis_config.cc
浏览文件 @ 23560d08
......@@ -89,7 +89,7 @@ AnalysisConfig::AnalysisConfig(const AnalysisConfig &other) {
CP_MEMBER(params_file_);
CP_MEMBER(model_from_memory_); // the memory model reuses prog_file_ and
// params_file_ fields.
// Gpu releated.
// Gpu related.
CP_MEMBER(use_gpu_);
CP_MEMBER(device_id_);
CP_MEMBER(memory_pool_init_size_mb_);
......@@ -97,13 +97,13 @@ AnalysisConfig::AnalysisConfig(const AnalysisConfig &other) {
CP_MEMBER(enable_memory_optim_);
CP_MEMBER(static_memory_optim_);
CP_MEMBER(static_memory_optim_force_update_);
// TensorRT releated.
// TensorRT related.
CP_MEMBER(use_tensorrt_);
CP_MEMBER(tensorrt_workspace_size_);
CP_MEMBER(tensorrt_max_batchsize_);
CP_MEMBER(tensorrt_min_subgraph_size_);
CP_MEMBER(tensorrt_precision_mode_);
// MKLDNN releated.
// MKLDNN related.
CP_MEMBER(use_mkldnn_);
CP_MEMBER(mkldnn_enabled_op_types_);
......
paddle/fluid/inference/api/analysis_predictor.cc
浏览文件 @ 23560d08
......@@ -392,7 +392,7 @@ std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
AnalysisConfig, PaddleEngineKind::kAnalysis>(const AnalysisConfig &config) {
VLOG(3) << "create AnalysisConfig";
if (config.use_gpu()) {
// 1. GPU memeroy
// 1. GPU memory
PADDLE_ENFORCE_GT(config.memory_pool_init_size_mb(), 0.f);
PADDLE_ENFORCE_GE(config.gpu_device_id(), 0, "Invalid device id %d",
config.gpu_device_id());
......@@ -726,7 +726,7 @@ bool AnalysisPredictor::need_collect_var_shapes_for_memory_optim() {
return need;
}
std::string AnalysisPredictor::GetSeriazlizedProgram() const {
std::string AnalysisPredictor::GetSerializedProgram() const {
return inference_program_->Proto()->SerializeAsString();
}
......
paddle/fluid/inference/api/analysis_predictor.h
浏览文件 @ 23560d08
......@@ -74,7 +74,7 @@ class AnalysisPredictor : public PaddlePredictor {
void SetMkldnnThreadID(int tid);
std::string GetSeriazlizedProgram() const override;
std::string GetSerializedProgram() const override;
protected:
// For memory optimization.
......
paddle/fluid/inference/api/analysis_predictor_tester.cc
浏览文件 @ 23560d08
......@@ -214,8 +214,8 @@ TEST(AnalysisPredictor, memory_optim) {
{
// The first predictor help to cache the memory optimize strategy.
auto predictor = CreatePaddlePredictor<AnalysisConfig>(config);
LOG(INFO) << "serialized program: " << predictor->GetSeriazlizedProgram();
ASSERT_FALSE(predictor->GetSeriazlizedProgram().empty());
LOG(INFO) << "serialized program: " << predictor->GetSerializedProgram();
ASSERT_FALSE(predictor->GetSerializedProgram().empty());
// Run several times to check the parameters are not reused by mistake.
for (int i = 0; i < 5; i++) {
......
paddle/fluid/inference/api/api.cc
浏览文件 @ 23560d08
......@@ -92,7 +92,7 @@ void PaddleBuf::Reset(void *data, size_t length) {
void PaddleBuf::Free() {
if (memory_owned_ && data_) {
PADDLE_ENFORCE_GT(length_, 0);
PADDLE_ENFORCE_GT(length_, 0UL);
free(static_cast<char *>(data_));
data_ = nullptr;
length_ = 0;
......
paddle/fluid/inference/api/api_impl.cc
浏览文件 @ 23560d08
......@@ -290,7 +290,7 @@ std::unique_ptr<PaddlePredictor> CreatePaddlePredictor<
NativeConfig, PaddleEngineKind::kNative>(const NativeConfig &config) {
VLOG(3) << "create NativePaddlePredictor";
if (config.use_gpu) {
// 1. GPU memeroy
// 1. GPU memory
PADDLE_ENFORCE_GE(
config.fraction_of_gpu_memory, 0.f,
"fraction_of_gpu_memory in the config should be set to range (0., 1.]");
......
paddle/fluid/inference/api/paddle_analysis_config.h
浏览文件 @ 23560d08
......@@ -212,12 +212,12 @@ struct AnalysisConfig {
std::string prog_file_;
std::string params_file_;
// GPU releated.
// GPU related.
bool use_gpu_{false};
int device_id_{0};
uint64_t memory_pool_init_size_mb_{100}; // initial size is 100MB.
// TensorRT releated.
// TensorRT related.
bool use_tensorrt_{false};
// For workspace_size, refer it from here:
// https://docs.nvidia.com/deeplearning/sdk/tensorrt-developer-guide/index.html#troubleshooting
......
paddle/fluid/inference/api/paddle_api.h
浏览文件 @ 23560d08
......@@ -248,7 +248,7 @@ class PaddlePredictor {
/** \brief Get the serialized model program that executes in inference phase.
* Its data type is ProgramDesc, which is a protobuf message.
*/
virtual std::string GetSeriazlizedProgram() const {
virtual std::string GetSerializedProgram() const {
assert(false); // Force raise error.
return "NotImplemented";
}
......
paddle/fluid/inference/tests/api/CMakeLists.txt
浏览文件 @ 23560d08
......@@ -60,10 +60,13 @@ set(RNN2_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/rnn2")
download_model_and_data(${RNN2_INSTALL_DIR} "rnn2_model.tar.gz" "rnn2_data.txt.tar.gz")
inference_analysis_api_test(test_analyzer_rnn2 ${RNN2_INSTALL_DIR} analyzer_rnn2_tester.cc)
# TODO(luotao, Superjom) Disable DAM test, temporarily fix
# https://github.com/PaddlePaddle/Paddle/issues/15032#issuecomment-455990914.
# After inference framework refactor, will reopen it.
# normal DAM
set(DAM_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/dam")
download_model_and_data(${DAM_INSTALL_DIR} "DAM_model.tar.gz" "DAM_data.txt.tar.gz")
inference_analysis_api_test(test_analyzer_dam ${DAM_INSTALL_DIR} analyzer_dam_tester.cc EXTRA_DEPS legacy_allocator SERIAL)
#inference_analysis_api_test(test_analyzer_dam ${DAM_INSTALL_DIR} analyzer_dam_tester.cc EXTRA_DEPS legacy_allocator SERIAL)
# small DAM
set(DAM_SMALL_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/small_dam")
......
paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc
浏览文件 @ 23560d08
......@@ -56,14 +56,14 @@ struct DataRecord {
std::vector<float> slot_data;
split_to_float(data[1], ' ', &slot_data);
std::string name = data[0];
PADDLE_ENFORCE_EQ(slot_data.size() % 11, 0,
PADDLE_ENFORCE_EQ(slot_data.size() % 11, 0UL,
"line %d, %s should be divisible", num_lines, name);
datasets[name].emplace_back(std::move(slot_data));
}
num_samples = num_lines / num_slots;
PADDLE_ENFORCE_EQ(num_samples * num_slots, static_cast<size_t>(num_lines),
"num samples should be divisible");
PADDLE_ENFORCE_GT(num_samples, 0);
PADDLE_ENFORCE_GT(num_samples, 0UL);
}
void Prepare(int bs) {
......
paddle/fluid/inference/tests/test.cmake
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include(ExternalProject)
set(INFERENCE_URL "http://paddle-inference-dist.cdn.bcebos.com" CACHE STRING "inference download url")
set(INFERENCE_DEMO_INSTALL_DIR "${THIRD_PARTY_PATH}/inference_demo" CACHE STRING
"A path setting inference demo download directories.")
function (inference_download install_dir url filename)
message(STATUS "Download inference test stuff from ${url}/${filename}")
file(DOWNLOAD "${url}/${filename}" "${install_dir}/${filename}")
message(STATUS "finish downloading ${filename}")
function(inference_download INSTALL_DIR URL FILENAME)
message(STATUS "Download inference test stuff from ${URL}/${FILENAME}")
string(REGEX REPLACE "[-%.]" "_" FILENAME_EX ${FILENAME})
ExternalProject_Add(
extern_inference_download_${FILENAME_EX}
${EXTERNAL_PROJECT_LOG_ARGS}
PREFIX ${INSTALL_DIR}
URL ${URL}/${FILENAME}
DOWNLOAD_COMMAND wget -q -O ${INSTALL_DIR}/${FILENAME} ${URL}/${FILENAME}
DOWNLOAD_DIR ${INSTALL_DIR}
DOWNLOAD_NO_PROGRESS 1
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
UPDATE_COMMAND ""
INSTALL_COMMAND ""
)
endfunction()
function (inference_download_and_uncompress install_dir url filename)
inference_download(${install_dir} ${url} ${filename})
execute_process(
COMMAND ${CMAKE_COMMAND} -E tar xzf ${install_dir}/${filename}
WORKING_DIRECTORY ${install_dir}
function(inference_download_and_uncompress INSTALL_DIR URL FILENAME)
message(STATUS "Download inference test stuff from ${URL}/${FILENAME}")
string(REGEX REPLACE "[-%.]" "_" FILENAME_EX ${FILENAME})
set(EXTERNAL_PROJECT_NAME "extern_inference_download_${FILENAME_EX}")
set(UNPACK_DIR "${INSTALL_DIR}/src/${EXTERNAL_PROJECT_NAME}")
ExternalProject_Add(
${EXTERNAL_PROJECT_NAME}
${EXTERNAL_PROJECT_LOG_ARGS}
PREFIX ${INSTALL_DIR}
URL ${URL}/${FILENAME}
DOWNLOAD_DIR ${INSTALL_DIR}
DOWNLOAD_NO_PROGRESS 1
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
UPDATE_COMMAND ""
INSTALL_COMMAND ${CMAKE_COMMAND} -E copy_directory ${UNPACK_DIR} ${INSTALL_DIR}
)
endfunction()
......
paddle/fluid/inference/tests/test_helper.h
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......@@ -171,9 +171,7 @@ void TestInference(const std::string& dirname,
// Enable the profiler
paddle::platform::EnableProfiler(state);
{
paddle::platform::RecordEvent record_event(
"init_program",
paddle::platform::DeviceContextPool::Instance().Get(place));
paddle::platform::RecordEvent record_event("init_program");
inference_program = InitProgram(&executor, scope, dirname, is_combined);
}
......@@ -230,9 +228,7 @@ void TestInference(const std::string& dirname,
// Run repeat times to profile the performance
for (int i = 0; i < repeat; ++i) {
paddle::platform::RecordEvent record_event(
"run_inference",
paddle::platform::DeviceContextPool::Instance().Get(place));
paddle::platform::RecordEvent record_event("run_inference");
if (PrepareContext) {
// Note: if you change the inference_program, you need to call
......
paddle/fluid/memory/allocation/legacy_allocator.cc
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......@@ -356,7 +356,7 @@ void MemInfo::Minus(const size_t &size) {
usage_ -= size;
}
uint64_t MemInfo::GetPeakUsage() { return peak_usage_; }
uint64_t MemInfo::GetPeakUsage() const { return peak_usage_; }
LegacyMemMonitor::~LegacyMemMonitor() {
for (auto &item : gpu_mem_info_) delete item.second;
......@@ -380,10 +380,10 @@ void LegacyMemMonitor::Minus(const int &device, const size_t &size) {
gpu_mem_info_[device]->Minus(size);
}
uint64_t LegacyMemMonitor::GetMemUsage(const int &device) {
uint64_t LegacyMemMonitor::GetMemUsage(const int &device) const {
return gpu_mem_info_.find(device) == gpu_mem_info_.end()
? 0
: gpu_mem_info_[device]->GetPeakUsage();
: gpu_mem_info_.at(device)->GetPeakUsage();
}
void LegacyMemMonitor::PrintMemUsage() {
......
paddle/fluid/memory/allocation/legacy_allocator.h
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......@@ -27,20 +27,20 @@ namespace allocation {
class MemInfo {
public:
MemInfo() : usage_(0), peak_usage_(0) {}
MemInfo(const MemInfo &) = delete;
MemInfo &operator=(const MemInfo &) = delete;
// return a flag to indicate current operation will create a peak point or not
bool Add(const size_t &);
void Minus(const size_t &);
uint64_t GetPeakUsage();
uint64_t GetPeakUsage() const;
private:
/* current memory usage*/
uint64_t usage_;
uint64_t peak_usage_;
std::mutex mutex_;
DISABLE_COPY_AND_ASSIGN(MemInfo);
};
class LegacyMemMonitor {
......@@ -56,11 +56,11 @@ class LegacyMemMonitor {
void Add(const int &, const size_t &);
void Minus(const int &, const size_t &);
uint64_t GetMemUsage(const int &);
uint64_t GetMemUsage(const int &) const;
void PrintMemUsage();
protected:
private:
MemUsage gpu_mem_info_;
};
......
paddle/fluid/operators/CMakeLists.txt
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......@@ -66,7 +66,7 @@ set(COMMON_OP_DEPS ${OP_HEADER_DEPS})
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} selected_rows_functor selected_rows lod_tensor maxouting unpooling pooling lod_rank_table context_project sequence_pooling executor)
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} dynload_warpctc)
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} sequence_padding sequence_scale cos_sim_functor memory jit_kernel_helper concat_and_split cross_entropy softmax vol2col im2col sampler tree2col)
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} sequence_padding sequence_scale cos_sim_functor memory jit_kernel_helper concat_and_split cross_entropy softmax vol2col im2col sampler sample_prob tree2col)
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} sequence2batch lstm_compute matrix_bit_code gru_compute activation_functions beam_search)
if (WITH_GPU)
set(COMMON_OP_DEPS ${COMMON_OP_DEPS} depthwise_conv prelu)
......@@ -97,3 +97,4 @@ if (WITH_PYTHON)
endif()
set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library")
add_subdirectory(benchmark)
paddle/fluid/operators/benchmark/CMakeLists.txt 0 → 100644
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