Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix-api-doc-20190220

AUTHORS.md

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

-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

@@ -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

@@ -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

@@ -31,5 +31,3 @@ else()
 endif()
 
 add_dependencies(cub extern_cub)
-
-LIST(APPEND external_project_dependencies cub)

cmake/external/dlpack.cmake

@@ -27,5 +27,3 @@ else()
 endif()
 
 add_dependencies(dlpack extern_dlpack)
-
-LIST(APPEND external_project_dependencies dlpack)

cmake/external/eigen.cmake

@@ -52,5 +52,3 @@ else()
 endif()
 
 add_dependencies(eigen3 extern_eigen3)
-
-LIST(APPEND external_project_dependencies eigen3)

cmake/external/gflags.cmake

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -26,5 +26,3 @@ else()
 endif()
 
 add_dependencies(simple_threadpool extern_threadpool)
-
-LIST(APPEND external_project_dependencies simple_threadpool)

cmake/external/warpctc.cmake

@@ -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

@@ -55,4 +55,3 @@ else()
 endif()
 
 add_dependencies(xbyak ${XBYAK_PROJECT})
-list(APPEND external_project_dependencies xbyak)

cmake/external/xxhash.cmake

@@ -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

@@ -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

@@ -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

-# 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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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_));
+    result->Get<GraphOps>(kGraphOps).emplace_back(new AllReduceOpHandle(
+        result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation),
+        scopes, places, nccl_ctxs_));
 #else
-  result->Get<GraphOps>(kGraphOps).emplace_back(new AllReduceOpHandle(
-      result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation),
-      local_scopes_, places_));
+    result->Get<GraphOps>(kGraphOps).emplace_back(new AllReduceOpHandle(
+        result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation),
+        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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

+// 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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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
@@ -257,60 +258,44 @@ 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();
-        var_infos.back().name_ = node->Var()->Name();
-        var_infos.back().type_ = node->Var()->GetType();
-        var_infos.back().persistable_ = node->Var()->Persistable();
-      }
+  for (auto &node : graph->Nodes()) {
+    if (node->IsVar() && !node->IsCtrlVar() && node->Var()) {
+      var_infos.emplace_back();
+      var_infos.back().name_ = node->Var()->Name();
+      var_infos.back().type_ = node->Var()->GetType();
+      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)));
     }
   }
 
@@ -482,11 +474,10 @@ 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)
-    enable_parallel_graph = false;
+    if (build_strategy.enable_sequential_execution_ ||
+        exec_strategy.type_ == ExecutionStrategy::ExecutorType::kExperimental)
+      enable_parallel_graph = false;
   return enable_parallel_graph;
 }
 

paddle/fluid/inference/api/analysis_config.cc

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

+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()
 
 set(WORD2VEC_INSTALL_DIR "${INFERENCE_DEMO_INSTALL_DIR}/word2vec")

paddle/fluid/inference/tests/test_helper.h

@@ -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

@@ -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

@@ -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

@@ -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)