diff --git a/AUTHORS.md b/AUTHORS.md index deafa641203ed9d9bd794fe92e4a91e3aaa03f63..da91933f4697f3b7c08feab20d703e22397b3757 100644 --- a/AUTHORS.md +++ b/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 | diff --git a/CMakeLists.txt b/CMakeLists.txt index 61f5e63098c40f140774ba6bfd9a2de8d2d67bfb..8e7ffe72b5fb846fb55ab8dc4809d87a40cfe06c 100644 --- a/CMakeLists.txt +++ b/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") diff --git a/cmake/configure.cmake b/cmake/configure.cmake index b0f54bf49aafb65f1a92fa95877de2cc61fc67d3..93d74bb0a8f726ad31685cbfc7831b5441cd5108 100644 --- a/cmake/configure.cmake +++ b/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 ${CMAKE_BINARY_DIR}/glide go_path) - endif() - -endif(WITH_GOLANG) - if(WITH_GRPC) add_definitions(-DPADDLE_WITH_GRPC) endif(WITH_GRPC) diff --git a/cmake/cuda.cmake b/cmake/cuda.cmake index ef4192ecc98ea6de0c81c1f33320528d547b818a..735846db1db04e3884d72ec62d911d9a0efec147 100644 --- a/cmake/cuda.cmake +++ b/cmake/cuda.cmake @@ -168,10 +168,7 @@ elseif (${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) diff --git a/cmake/external/anakin.cmake b/cmake/external/anakin.cmake index 06fc6061bc98eec8c4c71860333f7d3456952aeb..77f4b34537577c7c5782675e7af19c73bc9f8e32 100644 --- a/cmake/external/anakin.cmake +++ b/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) diff --git a/cmake/external/any.cmake b/cmake/external/any.cmake deleted file mode 100644 index 85cce80b70a1fcf57015ac7a264e4950616b2717..0000000000000000000000000000000000000000 --- a/cmake/external/any.cmake +++ /dev/null @@ -1,31 +0,0 @@ -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) diff --git a/cmake/external/boost.cmake b/cmake/external/boost.cmake index 12412a51a0fd1aaa9702bd4547fb935d94012ada..fc204dc9193bb28b654936048dd61a9b461abb2f 100644 --- a/cmake/external/boost.cmake +++ b/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}) diff --git a/cmake/external/brpc.cmake b/cmake/external/brpc.cmake index 6b50cff7a66a33d9413627bfbc663cca06ba86f3..989d1dbd4cf593e779b94f7bb5eda613f000859c 100644 --- a/cmake/external/brpc.cmake +++ b/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) diff --git a/cmake/external/cub.cmake b/cmake/external/cub.cmake index f06728de91e4509be661e56baef641d591928b66..41ad8207743201fbddd1d678fc5122afe68207ae 100644 --- a/cmake/external/cub.cmake +++ b/cmake/external/cub.cmake @@ -31,5 +31,3 @@ else() endif() add_dependencies(cub extern_cub) - -LIST(APPEND external_project_dependencies cub) diff --git a/cmake/external/dlpack.cmake b/cmake/external/dlpack.cmake index 4587475d7902a134eecd54bf8241fb96d175d0ba..63dd16b28e40a0c2d5310bec011c721285049952 100644 --- a/cmake/external/dlpack.cmake +++ b/cmake/external/dlpack.cmake @@ -27,5 +27,3 @@ else() endif() add_dependencies(dlpack extern_dlpack) - -LIST(APPEND external_project_dependencies dlpack) diff --git a/cmake/external/eigen.cmake b/cmake/external/eigen.cmake index 6aef97f21244efd09e22781f703553a19a9e1860..72441160f89d2c188d35fc6b08b5f0b6d746a1ad 100644 --- a/cmake/external/eigen.cmake +++ b/cmake/external/eigen.cmake @@ -52,5 +52,3 @@ else() endif() add_dependencies(eigen3 extern_eigen3) - -LIST(APPEND external_project_dependencies eigen3) diff --git a/cmake/external/gflags.cmake b/cmake/external/gflags.cmake index f3ca74faea3629ddce053c49ef1e629f230fdc49..911920ed6212b87aa25ba9a1faf7696fbcb22587 100644 --- a/cmake/external/gflags.cmake +++ b/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) diff --git a/cmake/external/glog.cmake b/cmake/external/glog.cmake index d3a4d69d3a05515fdf72074083470e19b4ec255c..7fa17ce6b7b106c47c486729d0136748c73176a7 100644 --- a/cmake/external/glog.cmake +++ b/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) diff --git a/cmake/external/gtest.cmake b/cmake/external/gtest.cmake index 9be625b620287cd4c644ae6908000fd5eec5d5c7..e459526583bd5ee3c89807657f3c30376e57d971 100644 --- a/cmake/external/gtest.cmake +++ b/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)) diff --git a/cmake/external/leveldb.cmake b/cmake/external/leveldb.cmake index 0df61b01ab64c8b751bdc3893dd5294ad39ab928..ac0febd076e659927a6a882ff487c61ac130437a 100644 --- a/cmake/external/leveldb.cmake +++ b/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) - diff --git a/cmake/external/libmct.cmake b/cmake/external/libmct.cmake index 27cff8cfb6315c9b4fa5677ad9062bee73a0e5d8..b944f2945b7874ca76bf1a19e0a363f564851a62 100644 --- a/cmake/external/libmct.cmake +++ b/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) - diff --git a/cmake/external/libxsmm.cmake b/cmake/external/libxsmm.cmake index 39f49d210a20d49a06c120361ecf0a5d07d1af28..69cdba7c5921f14a87172d95791332e364045b26 100644 --- a/cmake/external/libxsmm.cmake +++ b/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) - diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake index 92fe76d05c7507c295b784bc37870abfc31a0a29..94a266c50114a94d125467d55a6367a6999e3298 100644 --- a/cmake/external/mkldnn.cmake +++ b/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) diff --git a/cmake/external/mklml.cmake b/cmake/external/mklml.cmake index 2caff27357687018f29c1efc55b7b82c9dc3ccf6..32a9368a9f639468a2144548118677aaddecbdf2 100644 --- a/cmake/external/mklml.cmake +++ b/cmake/external/mklml.cmake @@ -39,8 +39,10 @@ IF(WIN32) SET(MKLML_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5md.lib) SET(MKLML_SHARED_LIB ${MKLML_LIB_DIR}/mklml.dll) SET(MKLML_SHARED_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5md.dll) -ELSE() - SET(MKLML_VER "mklml_lnx_${TIME_VERSION}" CACHE STRING "" FORCE) +ELSE() + #TODO(intel-huying): + # Now enable Erf function in mklml library temporarily, it will be updated as offical version later. + SET(MKLML_VER "VsErf_mklml_lnx_${TIME_VERSION}" CACHE STRING "" FORCE) SET(MKLML_URL "http://paddlepaddledeps.cdn.bcebos.com/${MKLML_VER}.tgz" CACHE STRING "" FORCE) SET(MKLML_LIB ${MKLML_LIB_DIR}/libmklml_intel.so) SET(MKLML_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5.so) @@ -73,4 +75,3 @@ INCLUDE_DIRECTORIES(${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) diff --git a/cmake/external/ngraph.cmake b/cmake/external/ngraph.cmake index 14af98b2d74d4aa955aac27727e05567788a84c9..5812a61f0ddc3a3233ff212710fc1b16aa140724 100644 --- a/cmake/external/ngraph.cmake +++ b/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) diff --git a/cmake/external/openblas.cmake b/cmake/external/openblas.cmake index b347a592929836a473ac764c0af1153b07d54258..d8a4a0be6f5aaa3a1a4977bbc68348743f2fa742 100644 --- a/cmake/external/openblas.cmake +++ b/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) diff --git a/cmake/external/protobuf.cmake b/cmake/external/protobuf.cmake index 3da3f10d7c91094ff8ae7daeadfb55e4e44eb731..bc7fe5454f5883108e43b4ca47920995dc13a1ff 100644 --- a/cmake/external/protobuf.cmake +++ b/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) diff --git a/cmake/external/pslib.cmake b/cmake/external/pslib.cmake index b4ea268e5a48e29d00b0ec8b957b61a42553ec7e..0287e5cf2a835ed65c5fc26ff69d2653d5db217e 100644 --- a/cmake/external/pslib.cmake +++ b/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) diff --git a/cmake/external/pslib_brpc.cmake b/cmake/external/pslib_brpc.cmake index 8b43f2ef5c999fc351543ba958c7cc4b0856625d..22c8c1b463764b6e107c5f3da25d51b36c2ce59f 100644 --- a/cmake/external/pslib_brpc.cmake +++ b/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 ${PSLIB_BRPC_PROJECT}) -LIST(APPEND external_project_dependencies pslib_brpc) diff --git a/cmake/external/python.cmake b/cmake/external/python.cmake index 351e7fa3ce227ee3a92f527fc49c873e52342594..623c53f4f75bbd217c157bcdda0cb12c510269ee 100644 --- a/cmake/external/python.cmake +++ b/cmake/external/python.cmake @@ -74,8 +74,8 @@ IF(PYTHONINTERP_FOUND) find_python_module(wheel REQUIRED) find_python_module(google.protobuf REQUIRED) FIND_PACKAGE(NumPy REQUIRED) - IF(${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 ${PY_GOOGLE.PROTOBUF_VERSION} < 3.0.0, " "please use pip to upgrade protobuf. pip install -U protobuf") ENDIF() ENDIF(PYTHONINTERP_FOUND) diff --git a/cmake/external/threadpool.cmake b/cmake/external/threadpool.cmake index 0159815fed81bdff6de3e561af569e9edc75f947..1f56bc7ab056ef0dd95d603ebe3461ef044b2a79 100644 --- a/cmake/external/threadpool.cmake +++ b/cmake/external/threadpool.cmake @@ -26,5 +26,3 @@ else() endif() add_dependencies(simple_threadpool extern_threadpool) - -LIST(APPEND external_project_dependencies simple_threadpool) diff --git a/cmake/external/warpctc.cmake b/cmake/external/warpctc.cmake index 7a25aaf15f2c7f46d99394d82d69bc24e4f5cb2c..6f2af8670f25c00ac0970fe4ae2b0c5b03aa0d9e 100644 --- a/cmake/external/warpctc.cmake +++ b/cmake/external/warpctc.cmake @@ -83,5 +83,3 @@ INCLUDE_DIRECTORIES(${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) diff --git a/cmake/external/xbyak.cmake b/cmake/external/xbyak.cmake index 384c2f9328296ce6a8a6293be6cc47e5063dd3c4..1d61154c0d45dea795902d6544deb796693db263 100644 --- a/cmake/external/xbyak.cmake +++ b/cmake/external/xbyak.cmake @@ -55,4 +55,3 @@ else() endif() add_dependencies(xbyak ${XBYAK_PROJECT}) -list(APPEND external_project_dependencies xbyak) diff --git a/cmake/external/xxhash.cmake b/cmake/external/xxhash.cmake index a0f300c2e8bab9e7402f869eed1b4c2d1c579aab..23b1e02108642df561948a6faa3152effb7ca932 100644 --- a/cmake/external/xxhash.cmake +++ b/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) diff --git a/cmake/external/zlib.cmake b/cmake/external/zlib.cmake index 6c8d79c25e6a2655711fe4450e65600c9a584015..5569fefe992d10ad4820e51e677f40271d0214e7 100644 --- a/cmake/external/zlib.cmake +++ b/cmake/external/zlib.cmake @@ -57,5 +57,3 @@ ENDIF(WIN32) ADD_LIBRARY(zlib STATIC IMPORTED GLOBAL) SET_PROPERTY(TARGET zlib PROPERTY IMPORTED_LOCATION ${ZLIB_LIBRARIES}) ADD_DEPENDENCIES(zlib extern_zlib) - -LIST(APPEND external_project_dependencies zlib) diff --git a/cmake/hip.cmake b/cmake/hip.cmake index 4276bc5b08cd88a52bb5782bca87fc37deabd830..c3a748db502037f926dc241e4c3bc26a83ad3468 100644 --- a/cmake/hip.cmake +++ b/cmake/hip.cmake @@ -11,8 +11,6 @@ include_directories("/opt/rocm/rocrand/include") include_directories("/opt/rocm/rccl/include") include_directories("/opt/rocm/thrust") -list(APPEND EXTERNAL_LIBS "-L/opt/rocm/lib/ -lhip_hcc") - set(HIP_HCC_FLAGS "${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") diff --git a/cmake/rdma.cmake b/cmake/rdma.cmake deleted file mode 100644 index b698f3bdc3ff586a72badee3e0109e29285b457f..0000000000000000000000000000000000000000 --- a/cmake/rdma.cmake +++ /dev/null @@ -1,82 +0,0 @@ -# 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) diff --git a/cmake/tensorrt.cmake b/cmake/tensorrt.cmake index 3dc7171551bfb7aff8d1e75083c98b00378d247f..891ff222633741f9894c2fdb6c0096a48f8a35e1 100644 --- a/cmake/tensorrt.cmake +++ b/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 ${TENSORRT_LIBRARY}) add_definitions(-DPADDLE_WITH_TENSORRT) endif() diff --git a/paddle/contrib/float16/run_float16_demo.sh b/paddle/contrib/float16/run_float16_demo.sh index 031225a85dabb26e5d9ea06f58909c049e7f0c08..34cb7a12db171915f2bc7df8787dd62cd381de68 100755 --- a/paddle/contrib/float16/run_float16_demo.sh +++ b/paddle/contrib/float16/run_float16_demo.sh @@ -14,9 +14,7 @@ cmake .. -DWITH_AVX=OFF \ -DWITH_MKL=OFF \ -DWITH_GPU=ON \ -DWITH_TESTING=ON \ - -DWITH_TIMER=ON \ -DWITH_PROFILER=ON \ - -DWITH_FLUID_ONLY=ON make -j `nproc` pip install -U "$WHEEL_PATH/$(ls $WHEEL_PATH)" diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index 230c9665300d2f65693e0c45e6b34dd2dcd80867..f24cf96cce30bf4b21e954ab022b2b99aeff37e6 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -427,7 +427,7 @@ 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)) diff --git a/paddle/fluid/framework/details/all_reduce_deps_pass.cc b/paddle/fluid/framework/details/all_reduce_deps_pass.cc index b7d6edd389d8e40835dadf56d7c54d53402f6f4d..2e20c436dfdb61fcda78cd044b86848c750cf22c 100644 --- a/paddle/fluid/framework/details/all_reduce_deps_pass.cc +++ b/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(p); diff --git a/paddle/fluid/framework/details/all_reduce_op_handle.cc b/paddle/fluid/framework/details/all_reduce_op_handle.cc index dd77f7099f581a5b825916c4ea010023f3ad5bcd..c1f9c2b60c915370df7793f26fe83812a7ced96d 100644 --- a/paddle/fluid/framework/details/all_reduce_op_handle.cc +++ b/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(this->Inputs()); diff --git a/paddle/fluid/framework/details/broadcast_op_handle.cc b/paddle/fluid/framework/details/broadcast_op_handle.cc index 89d626edddfee3d2c43a3cf2232ad4fc1611e655..fdff83b92819b39974f3b2ce0848710f1ee02a41 100644 --- a/paddle/fluid/framework/details/broadcast_op_handle.cc +++ b/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(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]; } diff --git a/paddle/fluid/framework/details/build_strategy.cc b/paddle/fluid/framework/details/build_strategy.cc index 0c823b9ca2a135101f7776bf0a8f94f4a93ffb03..8c6c9f35e84f4fd7d2b5486ac0eb60beceb512a2 100644 --- a/paddle/fluid/framework/details/build_strategy.cc +++ b/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 { diff --git a/paddle/fluid/framework/details/data_balance_op_handle.cc b/paddle/fluid/framework/details/data_balance_op_handle.cc index 48dcc52623369f7b0f51cd8c8aeb198b37467d5f..c9b52b68205ade000e21a3d06b80af86cbe01f34 100644 --- a/paddle/fluid/framework/details/data_balance_op_handle.cc +++ b/paddle/fluid/framework/details/data_balance_op_handle.cc @@ -86,7 +86,7 @@ std::vector> 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(this->Inputs()); diff --git a/paddle/fluid/framework/details/fuse_vars_op_handle.cc b/paddle/fluid/framework/details/fuse_vars_op_handle.cc index d65b0920698748e8a2ded728d78fbcd69b7bae0e..14292c0a5d06aa3ff12b46b5768b136fa925752d 100644 --- a/paddle/fluid/framework/details/fuse_vars_op_handle.cc +++ b/paddle/fluid/framework/details/fuse_vars_op_handle.cc @@ -23,7 +23,7 @@ void FuseVarsOpHandle::RunImpl() { auto in_var_handles = DynamicCast(this->Inputs()); auto out_var_handles = DynamicCast(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(); diff --git a/paddle/fluid/framework/details/fused_broadcast_op_handle.cc b/paddle/fluid/framework/details/fused_broadcast_op_handle.cc index 51dfa2d0711f49aaefab0af3549283dbf77eee4a..f48561ea32e6a3bbc7e9f2a8326b080ad21c6d61 100644 --- a/paddle/fluid/framework/details/fused_broadcast_op_handle.cc +++ b/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; diff --git a/paddle/fluid/framework/details/memory_optimize_helper.cc b/paddle/fluid/framework/details/memory_optimize_helper.cc index 6126c168ccf4b52ae75648d2dfe48db770639214..db4e805bb692ee44ac50337fae54f8dbfe389e6f 100644 --- a/paddle/fluid/framework/details/memory_optimize_helper.cc +++ b/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); } diff --git a/paddle/fluid/framework/details/memory_optimize_helper.h b/paddle/fluid/framework/details/memory_optimize_helper.h index dba96309fdf37e6ca73780cb194843659e1bd2d1..377367faf3c529496b00004f23159750cc2e4bc4 100644 --- a/paddle/fluid/framework/details/memory_optimize_helper.h +++ b/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 SortOpLikeDescOrder(const ir::Graph& graph); // NOTE(dzh): A ordered set for node reuse in memory optimize. diff --git a/paddle/fluid/framework/details/memory_optimize_pass.cc b/paddle/fluid/framework/details/memory_optimize_pass.cc index b35b967c72dcec7c427f6921c094f7a87d536f25..fd02bc4697e72cdd1e5af63d71931b8fe8cc29e3 100644 --- a/paddle/fluid/framework/details/memory_optimize_pass.cc +++ b/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(); } } diff --git a/paddle/fluid/framework/details/multi_devices_graph_pass.cc b/paddle/fluid/framework/details/multi_devices_graph_pass.cc index 75f922d2cca6855a67be7284ae407e549a1a1afb..7d1e63f3682bca8965f6c5e695132dff44fa3715 100644 --- a/paddle/fluid/framework/details/multi_devices_graph_pass.cc +++ b/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 &scopes, + const std::vector &places) -> OpHandleBase * { #if defined(PADDLE_WITH_CUDA) && !defined(_WIN32) - result->Get(kGraphOps).emplace_back(new AllReduceOpHandle( - result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation), - local_scopes_, places_, nccl_ctxs_)); + result->Get(kGraphOps).emplace_back(new AllReduceOpHandle( + result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation), + scopes, places, nccl_ctxs_)); #else - result->Get(kGraphOps).emplace_back(new AllReduceOpHandle( - result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation), - local_scopes_, places_)); + result->Get(kGraphOps).emplace_back(new AllReduceOpHandle( + result->CreateEmptyNode("allreduce", ir::Node::Type::kOperation), + scopes, places)); #endif - auto *op_handle = result->Get(kGraphOps).back(); + return result->Get(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(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); } diff --git a/paddle/fluid/framework/details/multi_devices_helper.h b/paddle/fluid/framework/details/multi_devices_helper.h index 1a2b75fbc0c28984ce5cf00e0a2ce0f804349bb1..9afbb91005c9c3a9d2e185f4dfa901ebf812ee19 100644 --- a/paddle/fluid/framework/details/multi_devices_helper.h +++ b/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` is the version of varaibles. -typedef std::vector>> +typedef std::vector>> GraphVars; const char kGraphVars[] = "vars"; // aux variables to represent dependency. Useful to resolve data hazard. -typedef std::unordered_set GraphDepVars; +typedef std::unordered_set GraphDepVars; const char kGraphDepVars[] = "dep_vars"; + } // namespace details } // namespace framework } // namespace paddle diff --git a/paddle/fluid/framework/details/op_handle_base.h b/paddle/fluid/framework/details/op_handle_base.h index b1a82e8771b92f2d0af4a1c7732ff2da54d496a8..e0aa352e95bc3685a1f4879bffa6e86eecd7e7f9 100644 --- a/paddle/fluid/framework/details/op_handle_base.h +++ b/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 &DeviceContext() { + return dev_ctxes_; + } void SetDeviceContext(platform::Place place, platform::DeviceContext *ctx_) { dev_ctxes_[place] = ctx_; diff --git a/paddle/fluid/framework/details/parallel_ssa_graph_executor.cc b/paddle/fluid/framework/details/parallel_ssa_graph_executor.cc index e8deb5bfc6c013addce11e2a04286a828acc1930..4c8f69c68ce17d0143c34e8adbab92cdc90058c8 100644 --- a/paddle/fluid/framework/details/parallel_ssa_graph_executor.cc +++ b/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> +ParallelSSAGraphExecutor::SeparateMultiDevicesGraph( + std::unique_ptr &&graph) { + std::vector> graphs; + graphs.reserve(places_.size()); + for (size_t i = 0; i < places_.size(); ++i) { + ProgramDesc empty; + graphs.emplace_back(std::unique_ptr(new ir::Graph(empty))); + auto &g = graphs.back(); + g->Set(kGraphVars, new GraphVars(1UL)); + g->Set(kGraphDepVars, new GraphDepVars); + } + auto op_handles = ir::FilterByNodeWrapper(*graph); + + for (auto &op : op_handles) { + auto &dev_ctx = op->DeviceContext(); + auto &p = dev_ctx.begin()->first; + int dev_id = boost::get(p).device; + auto &dev_dummys = graphs[dev_id]->Get(kGraphDepVars); + graphs[dev_id]->AddNode(graph->RemoveNode(op->Node()).release()); + + for (auto &var : op->Inputs()) { + auto dummy_ptr = dynamic_cast(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(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(kGraphVars)[0]; + auto &origin_vars = graph->Get(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 &local_scopes, const std::vector &places, - std::vector> &&graphs) + const framework::ProgramDesc &main_prog, std::unique_ptr &&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>( + details::kAllOpDescs, + new std::vector(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)))); } } diff --git a/paddle/fluid/framework/details/parallel_ssa_graph_executor.h b/paddle/fluid/framework/details/parallel_ssa_graph_executor.h index c00c5bc2d1b4b78593f99c819b5a3d642150e773..1c35d45fdd356a867d1ad80b345379395e03172e 100644 --- a/paddle/fluid/framework/details/parallel_ssa_graph_executor.h +++ b/paddle/fluid/framework/details/parallel_ssa_graph_executor.h @@ -18,7 +18,9 @@ #include #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 &local_scopes, const std::vector &places, - std::vector> &&graphs); + const framework::ProgramDesc &main_prog, + std::unique_ptr &&graph); ~ParallelSSAGraphExecutor() final = default; + const ir::Graph &Graph() const override { return *graphs_[0]; } FeedFetchList Run(const std::vector &fetch_tensors) override; private: + std::vector> SeparateMultiDevicesGraph( + std::unique_ptr &&graph); + ExecutionStrategy strategy_; std::vector local_scopes_; std::unique_ptr<::ThreadPool> pool_{nullptr}; std::vector places_; + framework::ProgramDesc main_prog_; std::vector> graphs_; std::vector> executors_; diff --git a/paddle/fluid/framework/details/reduce_op_handle.cc b/paddle/fluid/framework/details/reduce_op_handle.cc index ee4c8a6ecf77e5d0f23f38b763917d926afdb07a..4e2477c205db5966aa0b2d0c7a608be94a69eb82 100644 --- a/paddle/fluid/framework/details/reduce_op_handle.cc +++ b/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(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(); } diff --git a/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc b/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc index 91e4f9adb418978c30f512abe6924c0ace182124..7b13112986f9ad85056a3e8a5a6ed99bd0be95d5 100644 --- a/paddle/fluid/framework/details/scope_buffered_ssa_graph_executor.cc +++ b/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; diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc index 677a2937945b03fa577317cb4f26e09354d06957..72acc337b7cc4803fa010373f8817ff5fd25cb2c 100644 --- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc +++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc @@ -37,7 +37,7 @@ ThreadedSSAGraphExecutor::ThreadedSSAGraphExecutor( FeedFetchList ThreadedSSAGraphExecutor::Run( const std::vector &fetch_tensors) { std::unique_ptr event( - new platform::RecordEvent("ThreadedSSAGraphExecutorPrepare", nullptr)); + new platform::RecordEvent("ThreadedSSAGraphExecutorPrepare")); std::unordered_map pending_ops; std::unordered_set pending_vars; auto ready_vars = std::make_shared>(); @@ -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()); } diff --git a/paddle/fluid/framework/ir/CMakeLists.txt b/paddle/fluid/framework/ir/CMakeLists.txt index 07c2c970d4de3cecf03e4cf80e60e81e7a9595a8..25d9afbcc8b2bc89ec47654f0dba4cb838be55b0 100644 --- a/paddle/fluid/framework/ir/CMakeLists.txt +++ b/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 () diff --git a/paddle/fluid/framework/ir/attention_lstm_fuse_pass.h b/paddle/fluid/framework/ir/attention_lstm_fuse_pass.h index a756dfc1b98e1de55c809c73e2c4df1e628950ae..39b0585d3a6f9b52c9ec4b0a24f8532a3410851a 100644 --- a/paddle/fluid/framework/ir/attention_lstm_fuse_pass.h +++ b/paddle/fluid/framework/ir/attention_lstm_fuse_pass.h @@ -22,7 +22,8 @@ namespace ir { class AttentionLSTMFusePass : public FusePassBase { protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.h b/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.h index ad966e11e6222a4ed4c730089c454b0d1c7bd0b3..8c3c8b56c08cc09e66b20d17bf730edec0499f35 100644 --- a/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.h +++ b/paddle/fluid/framework/ir/conv_affine_channel_fuse_pass.h @@ -31,7 +31,8 @@ class ConvAffineChannelFusePass : public FusePassBase { virtual ~ConvAffineChannelFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr 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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"conv_eltwiseadd_affine_channel_fuse"}; }; diff --git a/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc b/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc index 846a14e365e6bd7f056d409130a3b246371931da..04765dd1440331fb37ed2eb05a9ce762eb2b81bc 100644 --- a/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc +++ b/paddle/fluid/framework/ir/conv_bn_fuse_pass.cc @@ -169,7 +169,7 @@ std::unique_ptr 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(); PADDLE_ENFORCE_EQ(conv_bias_tensor->dims(), diff --git a/paddle/fluid/framework/ir/conv_bn_fuse_pass.h b/paddle/fluid/framework/ir/conv_bn_fuse_pass.h index 2c9eb574fe8e054e0ae221f08f664b91f05d95c9..cf425a2730904d4ab21c33e66b72db0692cb087c 100644 --- a/paddle/fluid/framework/ir/conv_bn_fuse_pass.h +++ b/paddle/fluid/framework/ir/conv_bn_fuse_pass.h @@ -31,7 +31,8 @@ class ConvBNFusePass : public FusePassBase { virtual ~ConvBNFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr 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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"conv_eltwiseadd_bn_fuse"}; }; diff --git a/paddle/fluid/framework/ir/conv_elementwise_add2_act_fuse_pass.h b/paddle/fluid/framework/ir/conv_elementwise_add2_act_fuse_pass.h index 3b40a5a92665c07bc2b66e6a96721f573d40393f..9259a4ac5c89b1a7d1413fb2eaaa5fc6a70348f2 100644 --- a/paddle/fluid/framework/ir/conv_elementwise_add2_act_fuse_pass.h +++ b/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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/ir/conv_elementwise_add_act_fuse_pass.h b/paddle/fluid/framework/ir/conv_elementwise_add_act_fuse_pass.h index ac69aa6458fc8c19b670dea2af1251c44dc353a8..9c0b50f155821cf2bd815a6fb087e3f6cc513641 100644 --- a/paddle/fluid/framework/ir/conv_elementwise_add_act_fuse_pass.h +++ b/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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h b/paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h index f234603f5856a9238164f7fb0e5cc81ea9b7ed60..bf43bd5ce2602a3e240c56f00f66f13b79151002 100644 --- a/paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h +++ b/paddle/fluid/framework/ir/conv_elementwise_add_fuse_pass.h @@ -25,7 +25,8 @@ class ConvElementwiseAddFusePass : public FusePassBase { virtual ~ConvElementwiseAddFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/ir/embedding_fc_lstm_fuse_pass.h b/paddle/fluid/framework/ir/embedding_fc_lstm_fuse_pass.h index e5ad3067ec4060e41f1464395f3fc76183de3e66..fde2a0a4eecdec9ad5ac58ad8e63c26cce482682 100644 --- a/paddle/fluid/framework/ir/embedding_fc_lstm_fuse_pass.h +++ b/paddle/fluid/framework/ir/embedding_fc_lstm_fuse_pass.h @@ -14,6 +14,8 @@ #pragma once +#include + #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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"embedding_fc_lstm_fuse"}; }; diff --git a/paddle/fluid/framework/ir/fc_fuse_pass.h b/paddle/fluid/framework/ir/fc_fuse_pass.h index 6c69539d1e48268afc2435f8f73b3818d13107cd..783a052edcf84c8c437a7b2e25f0d67c0366691e 100644 --- a/paddle/fluid/framework/ir/fc_fuse_pass.h +++ b/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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/ir/fc_gru_fuse_pass.h b/paddle/fluid/framework/ir/fc_gru_fuse_pass.h index 63e1c72bfb2e2641ae5d44858b342d5e427e9045..e359a3289440fffbec622488ecf3a7f49e986574 100644 --- a/paddle/fluid/framework/ir/fc_gru_fuse_pass.h +++ b/paddle/fluid/framework/ir/fc_gru_fuse_pass.h @@ -30,7 +30,8 @@ class FCGRUFusePass : public FusePassBase { virtual ~FCGRUFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr 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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"fc_nobias_gru_fuse"}; }; diff --git a/paddle/fluid/framework/ir/fc_lstm_fuse_pass.h b/paddle/fluid/framework/ir/fc_lstm_fuse_pass.h index 3ee32c63a46fcc34bdccd1e14d4bbaf9668c49e9..21482615a6efef930b7328594477a51f4aaf28e7 100644 --- a/paddle/fluid/framework/ir/fc_lstm_fuse_pass.h +++ b/paddle/fluid/framework/ir/fc_lstm_fuse_pass.h @@ -14,6 +14,8 @@ #pragma once +#include + #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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr 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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"fc_nobias_lstm_fuse"}; }; diff --git a/paddle/fluid/framework/ir/fuse_elewise_add_act_pass.h b/paddle/fluid/framework/ir/fuse_elewise_add_act_pass.h index b2fecc076efca333539fe81e67eee222873aee2a..0fee5274478e8b8db852774077ff5979f0aaba25 100644 --- a/paddle/fluid/framework/ir/fuse_elewise_add_act_pass.h +++ b/paddle/fluid/framework/ir/fuse_elewise_add_act_pass.h @@ -32,7 +32,8 @@ class FuseElewiseAddActPass : public FusePassBase { virtual ~FuseElewiseAddActPass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; std::unique_ptr FuseElewiseAddAct( std::unique_ptr graph, diff --git a/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.cc b/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.cc index 0d94008ea82d0e09732d4b6448fdded94b60733c..fe844caed2e757fb080dcee398c8903b929b06e5 100644 --- a/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.cc +++ b/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.cc @@ -111,7 +111,7 @@ std::unique_ptr 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 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()}); diff --git a/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.h b/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.h index 6bd653775e42c1ee16051e205e9fa9888ea05eaa..efb49b8300e677f17d9e205800d837b88edfd2e9 100644 --- a/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.h +++ b/paddle/fluid/framework/ir/fuse_relu_depthwise_conv_pass.h @@ -32,7 +32,8 @@ class FuseReluDepthwiseConvPass : public FusePassBase { virtual ~FuseReluDepthwiseConvPass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; std::unique_ptr FuseReluDepthwiseConv( std::unique_ptr graph, bool only_forward) const; }; diff --git a/paddle/fluid/framework/ir/graph.h b/paddle/fluid/framework/ir/graph.h index feb3330176490e71c51cce826fe49d5499469ad7..296f3b83961c1379ee2c1237aa15784791b46878 100644 --- a/paddle/fluid/framework/ir/graph.h +++ b/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 RemoveNode(ir::Node *node) { PADDLE_ENFORCE(node_set_.find(node) != node_set_.end()); - node_set_.erase(node); + std::unique_ptr 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> &var_nodes); - - private: - std::map> 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> &var_nodes); + + private: + std::map> InitFromProgram( + const ProgramDesc &program); + // NOTE: program_ shouldn't be exposed to user. const ProgramDesc program_; std::map attrs_; diff --git a/paddle/fluid/framework/ir/graph_pattern_detector.cc b/paddle/fluid/framework/ir/graph_pattern_detector.cc index 9ea0729e1f3339c2f17371ecc8fa51325b9629bb..c0c34d186b00814fe6c6fd42beb78133233a1357 100644 --- a/paddle/fluid/framework/ir/graph_pattern_detector.cc +++ b/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); } diff --git a/paddle/fluid/framework/ir/identity_scale_op_clean_pass.h b/paddle/fluid/framework/ir/identity_scale_op_clean_pass.h index 50a654d82f0e4fb7e8e91c665397716407e6d2a5..6da592561da1e4046acbfd86c04862f69b7a97a8 100644 --- a/paddle/fluid/framework/ir/identity_scale_op_clean_pass.h +++ b/paddle/fluid/framework/ir/identity_scale_op_clean_pass.h @@ -22,7 +22,8 @@ namespace ir { class IdentityScaleOpCleanPass : public FusePassBase { protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; private: virtual ~IdentityScaleOpCleanPass() = default; diff --git a/paddle/fluid/framework/ir/lock_free_optimize_pass.h b/paddle/fluid/framework/ir/lock_free_optimize_pass.h index 7310f596f8a3170e84840be4bab8390b780b6577..f9157b10d9554092a5da6a6f73ecf7ceac1430dd 100644 --- a/paddle/fluid/framework/ir/lock_free_optimize_pass.h +++ b/paddle/fluid/framework/ir/lock_free_optimize_pass.h @@ -60,7 +60,8 @@ class LockFreeOptimizePass : public Pass { virtual ~LockFreeOptimizePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; private: // Create a new sgd node via current optimizer node diff --git a/paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.h b/paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.h index f3ad9f1c2bf14db418629e0c607e2510f01908b8..0ef5c177bf98b354bb18fc1d2ec8e5bef4b58951 100644 --- a/paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass.h +++ b/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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"conv_bias_mkldnn_fuse"}; }; /* diff --git a/paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc b/paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc new file mode 100644 index 0000000000000000000000000000000000000000..38b7fe52037c1a264e4251b7a54ef7569ee6d765 --- /dev/null +++ b/paddle/fluid/framework/ir/mkldnn/conv_bias_mkldnn_fuse_pass_tester.cc @@ -0,0 +1,151 @@ +// 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 +#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& inputs, + const std::vector& 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(OpRole::kForward)); +} + +// (c, weights)->conv->f +// (f)->elementwise_add->g +ProgramDesc BuildProgramDesc(bool convWithExistingBias) { + ProgramDesc prog; + std::vector 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({"c", "weights", "conv_bias"}), + std::vector({"f"})); + } else { + SetOp(&prog, "conv2d", "conv", std::vector({"c", "weights"}), + std::vector({"f"})); + } + SetOp(&prog, "elementwise_add", "eltwise", + std::vector({"f", "eltwise_bias"}), + std::vector({"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(); + tensor->mutable_data(place, proto::VarType::FP32, + ::paddle::memory::Allocator::kDefault, 1); +} + +void MainTest(bool convWithExistingBias) { + auto prog = BuildProgramDesc(convWithExistingBias); + std::unique_ptr 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(op->GetAttr("use_mkldnn"))); + // check if "conv" convolution is fused + auto op_name = boost::get(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>(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); diff --git a/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.h b/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.h index 3f3f0846eba1201e57a653f8e515c28d2bcdd5e3..ede0bea07ff4130a0f6b3d21d6e34222a5013170 100644 --- a/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.h +++ b/paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.h @@ -31,7 +31,8 @@ class RepeatedFCReluFusePass : public FusePassBase { virtual ~RepeatedFCReluFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"repeated_fc_relu_fuse"}; }; diff --git a/paddle/fluid/framework/ir/seq_concat_fc_fuse_pass.h b/paddle/fluid/framework/ir/seq_concat_fc_fuse_pass.h index 9f5fd1a29adf918806d8f30097d8c7f002f48f3e..06e18f9dc327bf2ffaf8d2ab64edcbddea2eb04c 100644 --- a/paddle/fluid/framework/ir/seq_concat_fc_fuse_pass.h +++ b/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 ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/ir/seqconv_eltadd_relu_fuse_pass.h b/paddle/fluid/framework/ir/seqconv_eltadd_relu_fuse_pass.h index dac9de71930c1768bdf416520caae6468449cd3d..c36c6b76a238dd21eb0c9308e780761aa9e4e27a 100644 --- a/paddle/fluid/framework/ir/seqconv_eltadd_relu_fuse_pass.h +++ b/paddle/fluid/framework/ir/seqconv_eltadd_relu_fuse_pass.h @@ -28,7 +28,8 @@ class SeqConvEltAddReluFusePass : public FusePassBase { virtual ~SeqConvEltAddReluFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"seqconv_eltadd_relu_fuse"}; }; diff --git a/paddle/fluid/framework/ir/seqpool_concat_fuse_pass.h b/paddle/fluid/framework/ir/seqpool_concat_fuse_pass.h index ba2154045e62c687173565c5ad30ea4d45d3c8f4..a5db3528da36ad08bb7f4d2765ee78222c569a5c 100644 --- a/paddle/fluid/framework/ir/seqpool_concat_fuse_pass.h +++ b/paddle/fluid/framework/ir/seqpool_concat_fuse_pass.h @@ -42,7 +42,8 @@ class SeqPoolConcatFusePass : public FusePassBase { virtual ~SeqPoolConcatFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"seqpool_concat_fuse"}; }; diff --git a/paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h b/paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h index fb49adc3768ec99cab4321c6b90c93dfed6d32f2..c21ba65c40a8d54c315ab347e5a8a3266a143779 100644 --- a/paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h +++ b/paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h @@ -31,7 +31,8 @@ class SquaredMatSubFusePass : public FusePassBase { virtual ~SquaredMatSubFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; const std::string name_scope_{"squared_mat_sub_fuse"}; }; diff --git a/paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.h b/paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.h index fb0f0ae9efdc5a25a799d6123fa658a99860cd86..a7d18ec86da1c02aef84c25c378691eb8f651015 100644 --- a/paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.h +++ b/paddle/fluid/framework/ir/transpose_flatten_concat_fuse_pass.h @@ -30,7 +30,8 @@ class TransposeFlattenConcatFusePass : public FusePassBase { virtual ~TransposeFlattenConcatFusePass() {} protected: - std::unique_ptr ApplyImpl(std::unique_ptr graph) const; + std::unique_ptr ApplyImpl( + std::unique_ptr graph) const override; }; } // namespace ir diff --git a/paddle/fluid/framework/op_proto_maker.h b/paddle/fluid/framework/op_proto_maker.h index 0a0f8f4655bc34cdb25205ff6eaec9f96c801ebd..5f3ce60e1d94ea4078cf0b709df362bad317f621 100644 --- a/paddle/fluid/framework/op_proto_maker.h +++ b/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. diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc index e15c838f4fbe44fa4f0b543021e97b6b6c70e757..9a0348871b050278da2ad07ac6992188a702da42 100644 --- a/paddle/fluid/framework/operator.cc +++ b/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); diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc index ff7ef0cce2f12fe89dd087c4a5006b2cfdc5a4a9..56da5660095affa0ba49d8bc533d1da01ffd18be 100644 --- a/paddle/fluid/framework/parallel_executor.cc +++ b/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> graphs; + std::unique_ptr 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 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 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 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(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(max_memory_size)); - } + graph = member_->PrepareGCAndRefCnts(std::move(graph), + static_cast(max_memory_size)); } // Step 3. Create vars in each scope. Passes may also create new vars. // skip control vars and empty vars std::vector 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; } diff --git a/paddle/fluid/inference/api/analysis_config.cc b/paddle/fluid/inference/api/analysis_config.cc index e92273b4dd94f11e0e90c91fd82dafe42bf158f3..522ab495227e9b8c52b8d38db696fa9b785ba642 100644 --- a/paddle/fluid/inference/api/analysis_config.cc +++ b/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_); diff --git a/paddle/fluid/inference/api/analysis_predictor.cc b/paddle/fluid/inference/api/analysis_predictor.cc index 712e010db4340bde55945f89c488ba8cc38a1926..e8964c4acea0d220deca048a018eb7de42d7e4e5 100644 --- a/paddle/fluid/inference/api/analysis_predictor.cc +++ b/paddle/fluid/inference/api/analysis_predictor.cc @@ -392,7 +392,7 @@ std::unique_ptr 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(); } diff --git a/paddle/fluid/inference/api/analysis_predictor.h b/paddle/fluid/inference/api/analysis_predictor.h index 014df4ee8b6d86232212736c43a9aff32ffee011..d5445c58e45ae64a8cfab03cb610e3677729338b 100644 --- a/paddle/fluid/inference/api/analysis_predictor.h +++ b/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. diff --git a/paddle/fluid/inference/api/analysis_predictor_tester.cc b/paddle/fluid/inference/api/analysis_predictor_tester.cc index 002ba90e40e69d565f5a54e374a3f0083b84273f..6696839b53fb21c274843afd86b5d8b5c2042c51 100644 --- a/paddle/fluid/inference/api/analysis_predictor_tester.cc +++ b/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(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++) { diff --git a/paddle/fluid/inference/api/api.cc b/paddle/fluid/inference/api/api.cc index 6cd18277d63200f5bccf180a7ae3196b0ce126ff..f83537f064187e67a08c8bbce52707d1c824abeb 100644 --- a/paddle/fluid/inference/api/api.cc +++ b/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(data_)); data_ = nullptr; length_ = 0; diff --git a/paddle/fluid/inference/api/api_impl.cc b/paddle/fluid/inference/api/api_impl.cc index e18bc02d92eb517fa20dc83811694b8ac80ae316..97c164bdef7a4b3e66be78526793f3830ada398b 100644 --- a/paddle/fluid/inference/api/api_impl.cc +++ b/paddle/fluid/inference/api/api_impl.cc @@ -290,7 +290,7 @@ std::unique_ptr 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.]"); diff --git a/paddle/fluid/inference/api/paddle_analysis_config.h b/paddle/fluid/inference/api/paddle_analysis_config.h index 47361b3279e14dd65a0e6e7f864e508ef1183045..c1c6227cdd8b2042f6765c7932327ecae246c260 100644 --- a/paddle/fluid/inference/api/paddle_analysis_config.h +++ b/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 diff --git a/paddle/fluid/inference/api/paddle_api.h b/paddle/fluid/inference/api/paddle_api.h index f90a74b9102ee62d15c2d738b53971c9bde51439..c9a45b4aa3b4037d3725622fc960848bc1ccfb2c 100644 --- a/paddle/fluid/inference/api/paddle_api.h +++ b/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"; } diff --git a/paddle/fluid/inference/tests/api/CMakeLists.txt b/paddle/fluid/inference/tests/api/CMakeLists.txt index 7ecd9e35332843e3a391cdad5ce32220d890abd1..55ab04bfe16ec6a3d97c443f59c72e7b85fb1899 100644 --- a/paddle/fluid/inference/tests/api/CMakeLists.txt +++ b/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") diff --git a/paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc b/paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc index dd953e0dccbb3749bfcc87966453c6976dfefa10..bd0059e18485c046df27d5ddbb39df9bbb249113 100644 --- a/paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc +++ b/paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc @@ -56,14 +56,14 @@ struct DataRecord { std::vector 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(num_lines), "num samples should be divisible"); - PADDLE_ENFORCE_GT(num_samples, 0); + PADDLE_ENFORCE_GT(num_samples, 0UL); } void Prepare(int bs) { diff --git a/paddle/fluid/inference/tests/test.cmake b/paddle/fluid/inference/tests/test.cmake index 29f0f034a2aab50330d4d0127b870a5cb00d56a5..6c5fe043ffa3f3dcafe2dbbebd6244467f859abf 100644 --- a/paddle/fluid/inference/tests/test.cmake +++ b/paddle/fluid/inference/tests/test.cmake @@ -1,18 +1,43 @@ +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") diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h index 75fa611c0d701dd81dfe5b33231655e0959c7dbf..861f69f4d2143b16bdec546d92ce7bd13ca53ed3 100644 --- a/paddle/fluid/inference/tests/test_helper.h +++ b/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 diff --git a/paddle/fluid/memory/allocation/legacy_allocator.cc b/paddle/fluid/memory/allocation/legacy_allocator.cc index e983ae327d69389526ae4cae226b0eb324759700..1936f9d4cd83c53cf7b322ab29a3e0d92e042abc 100644 --- a/paddle/fluid/memory/allocation/legacy_allocator.cc +++ b/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() { diff --git a/paddle/fluid/memory/allocation/legacy_allocator.h b/paddle/fluid/memory/allocation/legacy_allocator.h index ccbc8c70d8e9a16e7edb1be54bf80bec3b368eca..d9bdae153da6439598f76f5cac226897e6e0c596 100644 --- a/paddle/fluid/memory/allocation/legacy_allocator.h +++ b/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_; }; diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt index e099425b94221bf1229e936fc1781615d13dbc26..2166b8b545c23025e029d283b7ca43719e31a259 100644 --- a/paddle/fluid/operators/CMakeLists.txt +++ b/paddle/fluid/operators/CMakeLists.txt @@ -97,3 +97,4 @@ if (WITH_PYTHON) endif() set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library") +add_subdirectory(benchmark) diff --git a/paddle/fluid/operators/activation_op.h b/paddle/fluid/operators/activation_op.h index c7df3ea58a91579e35ff0d486516271a6daf054f..e8f5530b7887c19679dd1071805c5a66602493ba 100644 --- a/paddle/fluid/operators/activation_op.h +++ b/paddle/fluid/operators/activation_op.h @@ -11,6 +11,7 @@ limitations under the License. */ #pragma once #include +#include #include #include #include @@ -24,6 +25,7 @@ limitations under the License. */ #include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/detail/safe_ref.h" +#include "paddle/fluid/operators/math/blas.h" #include "paddle/fluid/platform/float16.h" #ifdef PADDLE_WITH_MKLDNN @@ -301,8 +303,28 @@ template struct GeluFunctor : public BaseActivationFunctor { template void operator()(Device d, X x, Out out) const { +// Because the execute or device context can not be deliver here, it keep the +// marco for NVCC. +#if defined(PADDLE_WITH_MKLML) && !defined(_WIN32) && !defined(__APPLE__) && \ + !defined(__OSX__) && !defined(PADDLE_WITH_CUDA) + auto x_data = x.data(); + auto out_data = out.data(); + int n = std::min(x.size(), out.size()); + + std::memset(out_data, 0, n * sizeof(T)); + math::CBlas::AXPY(n, static_cast(M_SQRT1_2), x_data, 1, out_data, 1); + math::CBlas::VMERF(n, out_data, out_data, VML_LA); + for (int i = 0; i < n; i++) { + out_data[i] += static_cast(1); + } + math::CBlas::VMUL(n, x_data, out_data, out_data); + for (int i = 0; i < n; i++) { + out_data[i] *= static_cast(0.5); + } +#else auto temp = (x * static_cast(M_SQRT1_2)).erf(); out.device(d) = x * static_cast(0.5) * (static_cast(1) + temp); +#endif } }; diff --git a/paddle/fluid/operators/attention_lstm_op.cc b/paddle/fluid/operators/attention_lstm_op.cc index b6996be4b0984bcee3b16da268d79708a68b65b3..912ec79910301b67bc520b1aa78d3fa1fd165d1f 100644 --- a/paddle/fluid/operators/attention_lstm_op.cc +++ b/paddle/fluid/operators/attention_lstm_op.cc @@ -293,7 +293,7 @@ class AttentionLSTMKernel : public framework::OpKernel { int len = x_lod[0][i + 1] - x_lod[0][i]; max_seq_len = max_seq_len < len ? len : max_seq_len; } - PADDLE_ENFORCE_EQ(x_lod.size(), 1, "Input(X)'s lod size must be 1."); + PADDLE_ENFORCE_EQ(x_lod.size(), 1UL, "Input(X)'s lod size must be 1."); PADDLE_ENFORCE_EQ(c0->dims()[0], N, "C0 dims should be %d x %d.", N, D); fc_out->Resize({max_seq_len, 1}); diff --git a/paddle/fluid/operators/benchmark/CMakeLists.txt b/paddle/fluid/operators/benchmark/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..54008336a9f67f0123ba1cfa6fcea35b79b7ac4c --- /dev/null +++ b/paddle/fluid/operators/benchmark/CMakeLists.txt @@ -0,0 +1,3 @@ +cc_test(op_tester SRCS op_tester.cc op_tester_config.cc + DEPS memory timer framework_proto proto_desc lod_tensor op_registry + device_context scope ${GLOB_OP_LIB} ${GLOB_OPERATOR_DEPS}) diff --git a/paddle/fluid/operators/benchmark/op_tester.cc b/paddle/fluid/operators/benchmark/op_tester.cc new file mode 100644 index 0000000000000000000000000000000000000000..e179de56cddc5fada2e5833086d351659a7cf540 --- /dev/null +++ b/paddle/fluid/operators/benchmark/op_tester.cc @@ -0,0 +1,303 @@ +/* Copyright (c) 2016 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/operators/benchmark/op_tester.h" +#include "gflags/gflags.h" +#include "gtest/gtest.h" +#include "paddle/fluid/framework/op_info.h" +#include "paddle/fluid/framework/op_registry.h" +#include "paddle/fluid/framework/variable_helper.h" +#include "paddle/fluid/platform/init.h" +#include "paddle/fluid/platform/profiler.h" +#include "paddle/fluid/platform/timer.h" +#include "paddle/fluid/pybind/pybind.h" + +namespace paddle { +namespace operators { +namespace benchmark { + +DEFINE_string(op_config_list, "", "Path of op config file."); + +void OpTester::Init(const std::string &filename) { + Init(OpTesterConfig(filename)); +} + +void OpTester::Init(const OpTesterConfig &config) { + config_ = config; + + auto &op_desc_info = framework::OpInfoMap::Instance(); + // Initialize the OpDesc + if (op_desc_info.Has(config_.op_type)) { + type_ = config_.op_type; + op_desc_.SetType(config_.op_type); + + CreateInputVarDesc(); + CreateOutputVarDesc(); + } else { + LOG(FATAL) << "Op \"" << config_.op_type << "\" is not registered."; + } + + if (config_.device_id >= 0) { + place_ = paddle::platform::CUDAPlace(config_.device_id); + } else { + place_ = paddle::platform::CPUPlace(); + } + + framework::InitDevices(false); + scope_.reset(new paddle::framework::Scope()); + + op_ = framework::OpRegistry::CreateOp(op_desc_); + CreateVariables(scope_.get()); +} + +void OpTester::Run() { + if (config_.print_debug_string) { + LOG(INFO) << DebugString(); + } + + // Warm up + RunImpl(); + + platform::Timer timer; + if (config_.profile) { + if (platform::is_cpu_place(place_)) { + platform::EnableProfiler(platform::ProfilerState::kCPU); + } else { +#ifdef PADDLE_WITH_CUDA + platform::EnableProfiler(platform::ProfilerState::kAll); + platform::SetDeviceId(config_.device_id); +#else + PADDLE_THROW("'CUDAPlace' is not supported in CPU only device."); +#endif + } + + timer.Start(); + for (int i = config_.repeat; i > 0; --i) { + RunImpl(); + } + timer.Pause(); + platform::DisableProfiler(platform::EventSortingKey::kDefault, + "op_tester_profiler"); + } else { + timer.Start(); + for (int i = config_.repeat; i > 0; --i) { + RunImpl(); + } + timer.Pause(); + } + config_.runtime = timer.ElapsedMS() / config_.repeat; + LOG(INFO) << "=== Run " << config_.repeat + << " times, latency: " << config_.runtime << " ms ==="; +} + +void OpTester::RunImpl() { + op_->Run(*scope_, place_); + platform::DeviceContextPool::Instance().Get(place_)->Wait(); + scope_->DropKids(); +} + +std::vector OpTester::GetOpProtoInputNames() { + std::vector input_names; + const framework::proto::OpProto &proto = + framework::OpInfoMap::Instance().Get(type_).Proto(); + for (int i = 0; i != proto.inputs_size(); ++i) { + const auto &input = proto.inputs(i); + input_names.push_back(input.name()); + } + return input_names; +} + +std::vector OpTester::GetOpProtoOutputNames() { + std::vector output_names; + const framework::proto::OpProto &proto = + framework::OpInfoMap::Instance().Get(type_).Proto(); + for (int i = 0; i != proto.outputs_size(); ++i) { + const auto &output = proto.outputs(i); + output_names.push_back(output.name()); + } + return output_names; +} + +void OpTester::CreateInputVarDesc() { + std::vector input_names = GetOpProtoInputNames(); + for (auto &name : input_names) { + const OpInputConfig *input = config_.GetInput(name); + if (input == nullptr) { + LOG(FATAL) << "The input " << name << " of op " << config_.op_type + << " is not correctlly provided."; + } + + std::string var_name = config_.op_type + "." + name; + framework::VarDesc *var = Var(var_name); + // Need to support more type + var->SetType(framework::proto::VarType::LOD_TENSOR); + var->SetPersistable(false); + var->SetDataType(framework::proto::VarType::FP32); + var->SetShape(input->dims); + + op_desc_.SetInput(name, {var_name}); + inputs_.push_back(var_name); + } +} + +void OpTester::CreateOutputVarDesc() { + std::vector output_names = GetOpProtoOutputNames(); + for (auto &name : output_names) { + std::string var_name = config_.op_type + "." + name; + framework::VarDesc *var = Var(var_name); + // Need to support more type + var->SetType(framework::proto::VarType::LOD_TENSOR); + var->SetPersistable(false); + var->SetDataType(framework::proto::VarType::FP32); + + op_desc_.SetOutput(name, {var_name}); + outputs_.push_back(var_name); + } +} + +framework::VarDesc *OpTester::Var(const std::string &name) { + auto it = vars_.find(name); + if (it != vars_.end()) { + return it->second.get(); + } + auto *var = new framework::VarDesc(name); + vars_[name].reset(var); + return var; +} + +template +void OpTester::SetupTensor(framework::LoDTensor *tensor, + const std::vector &shape, T lower, + T upper) { + static unsigned int seed = 100; + std::mt19937 rng(seed++); + std::uniform_real_distribution uniform_dist(0, 1); + + T *ptr = tensor->mutable_data(framework::make_ddim(shape), place_); + if (platform::is_cpu_place(place_)) { + for (int i = 0; i < tensor->numel(); ++i) { + ptr[i] = static_cast(uniform_dist(rng) * (upper - lower) + lower); + } + } else { + framework::LoDTensor cpu_tensor; + T *cpu_ptr = cpu_tensor.mutable_data(framework::make_ddim(shape), + platform::CPUPlace()); + for (int i = 0; i < cpu_tensor.numel(); ++i) { + cpu_ptr[i] = static_cast(uniform_dist(rng) * (upper - lower) + lower); + } + TensorCopySync(cpu_tensor, place_, tensor); + } +} + +void OpTester::CreateVariables(framework::Scope *scope) { + for (auto &item : vars_) { + auto &var = item.second; + if (var->Name() == framework::kEmptyVarName) { + continue; + } + + auto *ptr = scope->Var(var->Name()); + framework::InitializeVariable(ptr, var->GetType()); + if (var->Persistable()) { + VLOG(3) << "Create Variable " << var->Name() + << " global, which pointer is " << ptr; + } else { + VLOG(3) << "Create Variable " << var->Name() + << " locally, which pointer is " << ptr; + } + } + + // Allocate memory for input tensor + for (auto &name : inputs_) { + VLOG(3) << "Allocate memory for tensor " << name; + auto &var_desc = vars_[name]; + std::vector shape = var_desc->GetShape(); + + auto *var = scope->Var(name); + auto *tensor = var->GetMutable(); + SetupTensor(tensor, shape, static_cast(0.0), + static_cast(1.0)); + } +} + +static std::string GenSpaces(int count) { + std::stringstream ss; + for (int i = 0; i < count; ++i) { + ss << " "; + } + return ss.str(); +} + +std::string OpTester::DebugString() { + std::stringstream ss; + int count = 0; + for (auto &item : vars_) { + auto &var = item.second; + ss << GenSpaces(count++) << "vars {\n"; + ss << GenSpaces(count) << "name: \"" << var->Name() << "\"\n"; + ss << GenSpaces(count++) << "type: {\n"; + ss << GenSpaces(count) << "type: LOD_TENSOR\n"; + ss << GenSpaces(count++) << "lod_tensor {\n"; + ss << GenSpaces(count++) << "tensor {\n"; + ss << GenSpaces(count) << "data_type: FP32\n"; + std::vector shape = var->GetShape(); + for (auto d : shape) { + ss << GenSpaces(count) << "dims: " << d << "\n"; + } + ss << GenSpaces(--count) << "}\n"; + ss << GenSpaces(--count) << "}\n"; + ss << GenSpaces(--count) << "}\n"; + ss << GenSpaces(count) << "persistable: " << var->Persistable() << "\n"; + ss << GenSpaces(--count) << "}\n"; + } + ss << GenSpaces(count++) << "ops {\n"; + for (auto &name : op_desc_.InputNames()) { + ss << GenSpaces(count++) << "inputs {\n"; + ss << GenSpaces(count) << "parameters: \"" << name << "\"\n"; + ss << GenSpaces(count) << "arguments: \"" << op_desc_.Input(name)[0] + << "\"\n"; + ss << GenSpaces(--count) << "}\n"; + } + for (auto &name : op_desc_.OutputNames()) { + ss << GenSpaces(count++) << "outputs {\n"; + ss << GenSpaces(count) << "parameters: \"" << name << "\"\n"; + ss << GenSpaces(count) << "arguments: \"" << op_desc_.Output(name)[0] + << "\"\n"; + ss << GenSpaces(--count) << "}\n"; + } + ss << GenSpaces(count) << "type: " << op_desc_.Type() << "\n"; + ss << GenSpaces(--count) << "}\n"; + return ss.str(); +} + +TEST(op_tester, base) { + OpTester tester; + if (!FLAGS_op_config_list.empty()) { + tester.Init(FLAGS_op_config_list); + } else { + OpTesterConfig config; + config.op_type = "elementwise_add"; + config.inputs.resize(2); + config.inputs[0].name = "X"; + config.inputs[0].dims = {64, 64}; + config.inputs[1].name = "Y"; + config.inputs[1].dims = {64, 1}; + tester.Init(config); + } + tester.Run(); +} + +} // namespace benchmark +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/benchmark/op_tester.h b/paddle/fluid/operators/benchmark/op_tester.h new file mode 100644 index 0000000000000000000000000000000000000000..1723d46c47ed67199713e6d726c6245f34f7c224 --- /dev/null +++ b/paddle/fluid/operators/benchmark/op_tester.h @@ -0,0 +1,69 @@ +/* Copyright (c) 2016 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. */ + +#pragma once + +#include +#include +#include "paddle/fluid/framework/ddim.h" +#include "paddle/fluid/framework/op_desc.h" +#include "paddle/fluid/framework/operator.h" +#include "paddle/fluid/operators/benchmark/op_tester_config.h" + +namespace paddle { +namespace operators { +namespace benchmark { + +class OpTester { + public: + OpTester() {} + + void Init(const std::string &filename); + void Init(const OpTesterConfig &config); + + void Run(); + + std::string DebugString(); + + private: + std::vector GetOpProtoInputNames(); + std::vector GetOpProtoOutputNames(); + + void CreateInputVarDesc(); + void CreateOutputVarDesc(); + + framework::VarDesc *Var(const std::string &name); + void CreateVariables(framework::Scope *scope); + + template + void SetupTensor(framework::LoDTensor *input, + const std::vector &shape, T lower, T upper); + + void RunImpl(); + + private: + OpTesterConfig config_; + std::string type_; + framework::OpDesc op_desc_; + std::unordered_map> vars_; + std::vector inputs_; + std::vector outputs_; + std::unique_ptr op_; + platform::Place place_; + std::unique_ptr scope_; +}; + +} // namespace benchmark +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/benchmark/op_tester_config.cc b/paddle/fluid/operators/benchmark/op_tester_config.cc new file mode 100644 index 0000000000000000000000000000000000000000..3db8de7f76801eb814b57859d6b95590761c96f3 --- /dev/null +++ b/paddle/fluid/operators/benchmark/op_tester_config.cc @@ -0,0 +1,114 @@ +/* Copyright (c) 2016 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/operators/benchmark/op_tester_config.h" +#include +#include "glog/logging.h" +#include "paddle/fluid/platform/enforce.h" + +namespace paddle { +namespace operators { +namespace benchmark { + +static const char kStartSeparator[] = "{"; +static const char kEndSeparator[] = "}"; +static const char kSepBetweenItems[] = ";"; + +static bool StartWith(const std::string& str, const std::string& substr) { + return str.find(substr) == 0; +} + +static bool EndWith(const std::string& str, const std::string& substr) { + return str.rfind(substr) == (str.length() - substr.length()); +} + +static void EraseEndSep(std::string* str) { + std::string substr = kSepBetweenItems; + if (EndWith(*str, substr)) { + str->erase(str->length() - substr.length(), str->length()); + } +} + +static std::vector ParseDims(std::string dims_str) { + std::vector dims; + std::string token; + std::istringstream token_stream(dims_str); + while (std::getline(token_stream, token, 'x')) { + dims.push_back(std::stoi(token)); + } + return dims; +} + +OpInputConfig::OpInputConfig(std::istream& is) { + std::string sep; + is >> sep; + if (sep == kStartSeparator) { + while (sep != kEndSeparator) { + is >> sep; + if (sep == "name" || sep == "name:") { + is >> name; + EraseEndSep(&name); + } else if (sep == "dims" || sep == "dims:") { + std::string dims_str; + is >> dims_str; + dims = ParseDims(dims_str); + } + } + } +} + +OpTesterConfig::OpTesterConfig(const std::string& filename) { + std::ifstream fin(filename, std::ios::in | std::ios::binary); + PADDLE_ENFORCE(static_cast(fin), "Cannot open file %s", + filename.c_str()); + + Init(fin); +} + +void OpTesterConfig::Init(std::istream& is) { + std::string sep; + is >> sep; + if (sep == kStartSeparator) { + while (sep != kEndSeparator) { + is >> sep; + if (sep == "op_type" || sep == "op_type:") { + is >> op_type; + } else if (sep == "device_id" || sep == "device_id:") { + is >> device_id; + } else if (sep == "repeat" || sep == "repeat:") { + is >> repeat; + } else if (sep == "profile" || sep == "profile:") { + is >> profile; + } else if (sep == "print_debug_string" || sep == "print_debug_string:") { + is >> print_debug_string; + } else if (sep == "input" || sep == "input:") { + OpInputConfig input_config(is); + inputs.push_back(input_config); + } + } + } +} + +const OpInputConfig* OpTesterConfig::GetInput(const std::string& name) { + for (size_t i = 0; i < inputs.size(); ++i) { + if (inputs[i].name == name) { + return &inputs[i]; + } + } + return nullptr; +} + +} // namespace benchmark +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/benchmark/op_tester_config.h b/paddle/fluid/operators/benchmark/op_tester_config.h new file mode 100644 index 0000000000000000000000000000000000000000..f7b62cb8ad03b410a2ea99fe4c2a8dc8a6bea7a7 --- /dev/null +++ b/paddle/fluid/operators/benchmark/op_tester_config.h @@ -0,0 +1,51 @@ +/* Copyright (c) 2016 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. */ + +#pragma once + +#include +#include +#include + +namespace paddle { +namespace operators { +namespace benchmark { + +struct OpInputConfig { + OpInputConfig() {} + explicit OpInputConfig(std::istream& is); + + std::string name; + std::vector dims; +}; + +struct OpTesterConfig { + OpTesterConfig() {} + explicit OpTesterConfig(const std::string& filename); + void Init(std::istream& is); + + const OpInputConfig* GetInput(const std::string& name); + + std::string op_type; + std::vector inputs; + int device_id{-1}; // CPU: -1 + int repeat{1}; + int profile{0}; + int print_debug_string{0}; + double runtime{0.0}; +}; + +} // namespace benchmark +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/controlflow/get_places_op.cc b/paddle/fluid/operators/controlflow/get_places_op.cc index db6ff7825690176ded0ab957764ed8411d3cd804..1a157688f3d02185d18b66ff5ba3613b6cf438ad 100644 --- a/paddle/fluid/operators/controlflow/get_places_op.cc +++ b/paddle/fluid/operators/controlflow/get_places_op.cc @@ -52,7 +52,7 @@ class GetPlacesOp : public framework::OperatorBase { device_count = is_gpu ? CUDADevCount() : std::thread::hardware_concurrency(); } - PADDLE_ENFORCE_NE(device_count, 0, "Cannot indicate %s device count", + PADDLE_ENFORCE_NE(device_count, 0UL, "Cannot indicate %s device count", is_gpu ? "GPU" : "CPU"); auto out_var_name = Output("Out"); diff --git a/paddle/fluid/operators/crf_decoding_op.cc b/paddle/fluid/operators/crf_decoding_op.cc index 81c9e9e543191d9b2d606217d726cc783be97fea..e053ae57739d3d96209e9ca180cc041f8b55396e 100644 --- a/paddle/fluid/operators/crf_decoding_op.cc +++ b/paddle/fluid/operators/crf_decoding_op.cc @@ -84,12 +84,12 @@ class CRFDecodingOp : public framework::OperatorWithKernel { "Output(ViterbiPath) should be not null."); auto emission_dims = ctx->GetInputDim("Emission"); - PADDLE_ENFORCE_EQ(emission_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(emission_dims.size(), 2, "The Input(Emission) should be a 2-D tensor."); PADDLE_ENFORCE(emission_dims[0], "An empty mini-batch is not allowed."); auto transition_dims = ctx->GetInputDim("Transition"); - PADDLE_ENFORCE_EQ(transition_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(transition_dims.size(), 2, "The Input(Transition) should be a 2-D tensor."); PADDLE_ENFORCE_EQ( transition_dims[0] - 2, transition_dims[1], diff --git a/paddle/fluid/operators/detection/anchor_generator_op.cc b/paddle/fluid/operators/detection/anchor_generator_op.cc index f2984d1af2f26d901bc30ecfd519d5268a60278a..4a333b559f82e6d39d2d4345c8ad58bc8d430c69 100644 --- a/paddle/fluid/operators/detection/anchor_generator_op.cc +++ b/paddle/fluid/operators/detection/anchor_generator_op.cc @@ -85,7 +85,7 @@ class AnchorGeneratorOpMaker : public framework::OpProtoAndCheckerMaker { " For instance, the anchor size of 64 means the area of this anchor " "equals to 64**2.") .AddCustomChecker([](const std::vector& anchor_sizes) { - PADDLE_ENFORCE_GT(anchor_sizes.size(), 0, + PADDLE_ENFORCE_GT(anchor_sizes.size(), 0UL, "Size of anchor_sizes must be at least 1."); for (size_t i = 0; i < anchor_sizes.size(); ++i) { PADDLE_ENFORCE_GT(anchor_sizes[i], 0.0, @@ -103,7 +103,7 @@ class AnchorGeneratorOpMaker : public framework::OpProtoAndCheckerMaker { "(vector) List of variances to be used " "in box regression deltas") .AddCustomChecker([](const std::vector& variances) { - PADDLE_ENFORCE_EQ(variances.size(), 4, + PADDLE_ENFORCE_EQ(variances.size(), 4UL, "Must and only provide 4 variance."); for (size_t i = 0; i < variances.size(); ++i) { PADDLE_ENFORCE_GT(variances[i], 0.0, @@ -117,7 +117,7 @@ class AnchorGeneratorOpMaker : public framework::OpProtoAndCheckerMaker { .SetDefault(std::vector(2, 16.0)) .AddCustomChecker([](const std::vector& stride) { PADDLE_ENFORCE_EQ( - stride.size(), 2, + stride.size(), 2UL, "Must and only provide 2 stride for width and height."); for (size_t i = 0; i < stride.size(); ++i) { PADDLE_ENFORCE_GT(stride[i], 0.0, diff --git a/paddle/fluid/operators/distributed/brpc/brpc_client.cc b/paddle/fluid/operators/distributed/brpc/brpc_client.cc index b8e63f42e2040730ac79c57651d86d9e3176fa01..a1a3443348129b5cdf057592fced8fdff238ac09 100644 --- a/paddle/fluid/operators/distributed/brpc/brpc_client.cc +++ b/paddle/fluid/operators/distributed/brpc/brpc_client.cc @@ -80,7 +80,7 @@ VarHandlePtr BRPCClient::AsyncSendVar(const std::string& ep, google::protobuf::Closure* done = brpc::NewCallback( &HandleSendResponse, cntl, response, var_h, ch_ptr, ch_ctx, this); - platform::RecordRPCEvent record_event(method, p_ctx); + platform::RecordRPCEvent record_event(method); ch_ctx->stub->SendVariable(cntl, &request, response, done); @@ -184,7 +184,7 @@ VarHandlePtr BRPCClient::_AsyncGetVar(const std::string& ep, google::protobuf::Closure* done = brpc::NewCallback( &HandleGetResponse, cntl, response, var_h, ch_ptr, ch_ctx, this); - platform::RecordRPCEvent record_event(method, p_ctx); + platform::RecordRPCEvent record_event(method); if (method_name == kGetMonomerRPC) { ch_ctx->stub->GetMonomerVariable(cntl, &req, response, done); @@ -272,7 +272,7 @@ VarHandlePtr BRPCClient::AsyncPrefetchVar(const std::string& ep, &cntl->request_attachment(), out_var_name_val, false, 0, table_name_val); - platform::RecordRPCEvent record_event(method, p_ctx); + platform::RecordRPCEvent record_event(method); google::protobuf::Closure* done = brpc::NewCallback( &HandleGetResponse, cntl, response, var_h, ch_ptr, ch_ctx, this); @@ -311,7 +311,7 @@ VarHandlePtr BRPCClient::AsyncSendFetchBarrier(const std::string& ep, VarHandlePtr var_h( new VarHandle(ep, method, FETCH_BARRIER_MESSAGE, nullptr, nullptr)); - platform::RecordRPCEvent record_event(method, nullptr); + platform::RecordRPCEvent record_event(method); google::protobuf::Closure* done = brpc::NewCallback( &HandleFetchBarrierResponse, cntl, response, var_h, ch_ptr, ch_ctx, this); @@ -406,7 +406,7 @@ VarHandlePtr BRPCClient::AsyncSendVarMessage( sendrecv::VoidMessage* response = new sendrecv::VoidMessage(); cntl->set_timeout_ms(time_out); - platform::RecordRPCEvent record_event(method_name, nullptr); + platform::RecordRPCEvent record_event(method_name); VarHandlePtr var_h( new VarHandle(ep, method_name, req.varname(), nullptr, nullptr)); diff --git a/paddle/fluid/operators/distributed/grpc/grpc_client.cc b/paddle/fluid/operators/distributed/grpc/grpc_client.cc index 52310f8d04db6a5df9967c0a5ec9a5e95a24cdab..61e94dae3c7a107e10fa5e5518651014cec078bc 100644 --- a/paddle/fluid/operators/distributed/grpc/grpc_client.cc +++ b/paddle/fluid/operators/distributed/grpc/grpc_client.cc @@ -89,7 +89,7 @@ VarHandlePtr GRPCClient::AsyncSendVar(const std::string& ep, // stub context s->response_call_back_ = nullptr; - platform::RecordRPCEvent record_event(method, p_ctx); + platform::RecordRPCEvent record_event(method); auto call = s->stub_g_.PrepareUnaryCall( s->context_.get(), "/sendrecv.SendRecvService/SendVariable", req, &cq_); @@ -184,7 +184,7 @@ VarHandlePtr GRPCClient::_AsyncGetVar( // stub context s->response_call_back_ = ProcGetResponse; - platform::RecordRPCEvent record_event(method, p_ctx); + platform::RecordRPCEvent record_event(method); auto call = s->stub_g_.PrepareUnaryCall(s->context_.get(), rpc_path, buf, &cq_); @@ -235,7 +235,7 @@ VarHandlePtr GRPCClient::AsyncPrefetchVar(const std::string& ep, // stub context s->response_call_back_ = ProcGetResponse; - platform::RecordRPCEvent record_event(method, p_ctx); + platform::RecordRPCEvent record_event(method); auto call = s->stub_g_.PrepareUnaryCall( s->context_.get(), "/sendrecv.SendRecvService/PrefetchVariable", req, @@ -265,7 +265,7 @@ VarHandlePtr GRPCClient::AsyncSendBatchBarrier(const std::string& ep, sendrecv::VariableMessage req; req.set_varname(BATCH_BARRIER_MESSAGE); - platform::RecordRPCEvent record_event(method, nullptr); + platform::RecordRPCEvent record_event(method); auto rpc = s->stub_->AsyncSendVariable(s->context_.get(), req, &cq_); rpc->Finish(&s->reply_, &s->status_, reinterpret_cast(s)); @@ -290,7 +290,7 @@ VarHandlePtr GRPCClient::AsyncSendFetchBarrier(const std::string& ep, sendrecv::VariableMessage req; req.set_varname(FETCH_BARRIER_MESSAGE); - platform::RecordRPCEvent record_event(method, nullptr); + platform::RecordRPCEvent record_event(method); auto rpc = s->stub_->AsyncGetVariable(s->context_.get(), req, &cq_); rpc->Finish(&s->reply_, &s->status_, reinterpret_cast(s)); @@ -317,7 +317,7 @@ VarHandlePtr GRPCClient::AsyncGetMonomerBarrier(const std::string& ep, sendrecv::VariableMessage req; req.set_varname(var_name); - platform::RecordRPCEvent record_event(method, nullptr); + platform::RecordRPCEvent record_event(method); auto rpc = s->stub_->AsyncGetMonomerBarrier(s->context_.get(), req, &cq_); rpc->Finish(&s->reply_, &s->status_, reinterpret_cast(s)); @@ -342,7 +342,7 @@ VarHandlePtr GRPCClient::AsyncSendComplete(const std::string& ep, sendrecv::VariableMessage req; req.set_varname(COMPLETE_MESSAGE); - platform::RecordRPCEvent record_event(method, nullptr); + platform::RecordRPCEvent record_event(method); auto rpc = s->stub_->AsyncSendVariable(s->context_.get(), req, &cq_); rpc->Finish(&s->reply_, &s->status_, reinterpret_cast(s)); @@ -372,7 +372,7 @@ VarHandlePtr GRPCClient::AsyncCheckpointNotify(const std::string& ep, req.set_varname(CHECKPOINT_SAVE_MESSAGE); req.set_out_varname(dir); - platform::RecordRPCEvent record_event(method, nullptr); + platform::RecordRPCEvent record_event(method); auto rpc = s->stub_->AsyncCheckpointNotify(s->context_.get(), req, &cq_); rpc->Finish(&s->reply_, &s->status_, reinterpret_cast(s)); diff --git a/paddle/fluid/operators/distributed/grpc/grpc_serde.cc b/paddle/fluid/operators/distributed/grpc/grpc_serde.cc index 6df4fd36f95b127a0bbc0725b83c4494b160785f..6e65aa5fae83536d229be63fbaf7874bd45f967d 100644 --- a/paddle/fluid/operators/distributed/grpc/grpc_serde.cc +++ b/paddle/fluid/operators/distributed/grpc/grpc_serde.cc @@ -38,7 +38,7 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var, ::grpc::ByteBuffer* msg, const std::string& out_name, const int trainer_id, const std::string& table_name) { - platform::RecordRPCEvent record_event("serial", &ctx); + platform::RecordRPCEvent record_event("serial"); VarMsg request; TensorPayload* payload = nullptr; @@ -147,7 +147,7 @@ void DeserializeFromByteBuffer(const ::grpc::ByteBuffer& msg, const platform::DeviceContext& ctx, const framework::Scope* scope, framework::Variable** var, int* trainer_id) { - platform::RecordRPCEvent record_event("deserial", &ctx); + platform::RecordRPCEvent record_event("deserial"); operators::distributed::GRPCVariableResponse resp(scope, &ctx); PADDLE_ENFORCE(resp.Parse(msg) == 0, "parse bytebuffer to tensor error!"); *var = resp.GetVar(); diff --git a/paddle/fluid/operators/fc_op.cc b/paddle/fluid/operators/fc_op.cc index 38e57a41ed253eab4d0713af8bb14bac19041f6d..eb4617a9359353820fc41b9ad1c8db5327fdacde 100644 --- a/paddle/fluid/operators/fc_op.cc +++ b/paddle/fluid/operators/fc_op.cc @@ -47,7 +47,7 @@ void FCOp::InferShape(framework::InferShapeContext* ctx) const { PADDLE_ENFORCE(in_dims.size() == 2 || in_dims.size() == 4, "Fully Connected input should be 2-D or 4-D tensor."); } - PADDLE_ENFORCE_EQ(w_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(w_dims.size(), 2, "Fully Connected input should be 2-D tensor."); int in_num_col_dims = ctx->Attrs().Get("in_num_col_dims"); PADDLE_ENFORCE_GT( diff --git a/paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h b/paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h index 92345b3c0eda42f03bd48c5f64880c56ddbe351b..33a1b47d150f653b84a377a61b251491aa719bee 100644 --- a/paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h +++ b/paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h @@ -47,10 +47,11 @@ struct EmbeddingVSumFunctor { auto *output = output_t->mutable_data(context.GetPlace()); PADDLE_ENFORCE_LE(table_width * idx_width, out_width); + PADDLE_ENFORCE_GT(ids_lod.size(), 1UL); jit::emb_seq_pool_attr_t attr(table_height, table_width, 0, idx_width, out_width, jit::SeqPoolType::kSum); - for (int64_t i = 0; i != ids_lod.size() - 1; ++i) { + for (size_t i = 0; i != ids_lod.size() - 1; ++i) { attr.index_height = ids_lod[i + 1] - ids_lod[i]; auto emb_seqpool = jit::Get, platform::CPUPlace>(attr); diff --git a/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc b/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc index e9e2a3b1f5c1c00bb2e95b6171ecd09bfe7a0d21..8ecdf2ed9d40e7f5dc9226c635a8c8e6406a76ba 100644 --- a/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc +++ b/paddle/fluid/operators/fused/fusion_repeated_fc_relu_op.cc @@ -37,7 +37,7 @@ void FusionRepeatedFCReluOp::InferShape( "Output(Out) of FusionRepeatedFCReluOp should not be null."); auto i_dims = ctx->GetInputDim("X"); - PADDLE_ENFORCE_EQ(i_dims.size(), 2UL, "Input shape size should be 2"); + PADDLE_ENFORCE_EQ(i_dims.size(), 2, "Input shape size should be 2"); auto w_dims = ctx->GetInputsDim("W"); auto b_dims = ctx->GetInputsDim("Bias"); @@ -49,7 +49,7 @@ void FusionRepeatedFCReluOp::InferShape( "inpute width should be equal with weight height"); for (size_t i = 1; i < sz; ++i) { - PADDLE_ENFORCE_EQ(w_dims[i].size(), 2UL, + PADDLE_ENFORCE_EQ(w_dims[i].size(), 2, "Every weight shape size should be 2."); PADDLE_ENFORCE_EQ(framework::product(b_dims[i]), w_dims[i][1], "The length of Bias must be equal with w_dims[1]."); diff --git a/paddle/fluid/operators/fused/fusion_seqexpand_concat_fc_op.cc b/paddle/fluid/operators/fused/fusion_seqexpand_concat_fc_op.cc index aaef46de0d3b88720a762abb000e42d560fbd8cf..d091da5aa8a7e7ec30798d68021bfd2b9b87b32f 100644 --- a/paddle/fluid/operators/fused/fusion_seqexpand_concat_fc_op.cc +++ b/paddle/fluid/operators/fused/fusion_seqexpand_concat_fc_op.cc @@ -39,7 +39,7 @@ void FusionSeqExpandConcatFCOp::InferShape( auto ins_dims = ctx->GetInputsDim("X"); auto w_dims = ctx->GetInputDim("FCWeight"); // (M0+M1+M2+..) x D - PADDLE_ENFORCE_EQ(w_dims.size(), 2UL, "Input(FCWeight)'s rank must be 2."); + PADDLE_ENFORCE_EQ(w_dims.size(), 2, "Input(FCWeight)'s rank must be 2."); const int D = w_dims[1]; int sum = ins_dims[0][1]; for (size_t i = 1; i < ins_dims.size(); ++i) { diff --git a/paddle/fluid/operators/fused/fusion_seqpool_concat_op.cc b/paddle/fluid/operators/fused/fusion_seqpool_concat_op.cc index b181140db750a8d1b74c0b6cc93259a208fe5b06..d48bdafe0aa38cb860b54b2e41ebad3421b93bce 100644 --- a/paddle/fluid/operators/fused/fusion_seqpool_concat_op.cc +++ b/paddle/fluid/operators/fused/fusion_seqpool_concat_op.cc @@ -39,7 +39,7 @@ void FusionSeqPoolConcatOp::InferShape( // The output height should be confirmed in Compute, // since input lod is not accessible here. - PADDLE_ENFORCE_EQ(ins_dims[0].size(), 2UL, + PADDLE_ENFORCE_EQ(ins_dims[0].size(), 2, "The dims size of first input should be 2."); ctx->SetOutputDim("Out", {-1, ins_dims[0][axis] * static_cast(n)}); } diff --git a/paddle/fluid/operators/fused/fusion_squared_mat_sub_op.cc b/paddle/fluid/operators/fused/fusion_squared_mat_sub_op.cc index 8c8b079633aacb711aa304ec7016c37c6bec61ce..8493f4468fc994964116d99dc85dd34fb19a44cc 100644 --- a/paddle/fluid/operators/fused/fusion_squared_mat_sub_op.cc +++ b/paddle/fluid/operators/fused/fusion_squared_mat_sub_op.cc @@ -42,7 +42,7 @@ void FusionSquaredMatSubOp::InferShape( auto y_dims = ctx->GetInputDim("Y"); PADDLE_ENFORCE_EQ(x_dims.size(), y_dims.size(), "Input tensors dims size should be equal."); - PADDLE_ENFORCE_EQ(x_dims.size(), 2UL, "Input tensors should be a Matrix."); + PADDLE_ENFORCE_EQ(x_dims.size(), 2, "Input tensors should be a Matrix."); PADDLE_ENFORCE_EQ(x_dims[1], y_dims[0], "Inputs Matrix should be multiply."); ctx->SetOutputDim("SquaredX", x_dims); diff --git a/paddle/fluid/operators/jit/test.cc b/paddle/fluid/operators/jit/test.cc index 2632bfb6de1751982c5c836fc96bf57d5b2844d6..356eba6f86ad180c7d23bf7fa91eb5d455ff5f08 100644 --- a/paddle/fluid/operators/jit/test.cc +++ b/paddle/fluid/operators/jit/test.cc @@ -1,16 +1,16 @@ /* Copyright (c) 2018 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. */ + +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 #include @@ -259,7 +259,7 @@ struct TestFuncWithRefer, std::vector, std::vector, const std::vector& x, const std::vector& yref, const typename jit::SeqPoolTuples::attr_type& attr) { EXPECT_TRUE(tgt != nullptr); - EXPECT_EQ(x.size() % yref.size(), 0); + EXPECT_EQ(x.size() % yref.size(), static_cast(0)); int w = yref.size(); std::vector y(w); const T* x_data = x.data(); diff --git a/paddle/fluid/operators/layer_norm_op.cc b/paddle/fluid/operators/layer_norm_op.cc index f83fe355b85566d229a2673d8f27cfb5ca4831d5..b9db6daf0825b573bfc7f684266212f998c91627 100644 --- a/paddle/fluid/operators/layer_norm_op.cc +++ b/paddle/fluid/operators/layer_norm_op.cc @@ -44,11 +44,11 @@ class LayerNormOp : public framework::OperatorWithKernel { int left = static_cast(matrix_dim[0]); int right = static_cast(matrix_dim[1]); if (ctx->HasInput("Scale")) { - PADDLE_ENFORCE_EQ(ctx->GetInputDim("Scale").size(), 1UL); + PADDLE_ENFORCE_EQ(ctx->GetInputDim("Scale").size(), 1); PADDLE_ENFORCE_EQ(ctx->GetInputDim("Scale")[0], right); } if (ctx->HasInput("Bias")) { - PADDLE_ENFORCE_EQ(ctx->GetInputDim("Bias").size(), 1UL); + PADDLE_ENFORCE_EQ(ctx->GetInputDim("Bias").size(), 1); PADDLE_ENFORCE_EQ(ctx->GetInputDim("Bias")[0], right); } diff --git a/paddle/fluid/operators/linear_chain_crf_op.cc b/paddle/fluid/operators/linear_chain_crf_op.cc index 1da14631e35608d479e1b861228d52d6d57def79..e17b6cb59898524d793f3cc78a09232f5b664617 100644 --- a/paddle/fluid/operators/linear_chain_crf_op.cc +++ b/paddle/fluid/operators/linear_chain_crf_op.cc @@ -144,12 +144,12 @@ class LinearChainCRFOp : public framework::OperatorWithKernel { "Output(LogLikelihood) should be not null."); auto emission_dims = ctx->GetInputDim("Emission"); - PADDLE_ENFORCE_EQ(emission_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(emission_dims.size(), 2, "The Input(Emission) should be a 2-D tensor."); PADDLE_ENFORCE(emission_dims[0], "An empty mini-batch is not allowed."); auto transition_dims = ctx->GetInputDim("Transition"); - PADDLE_ENFORCE_EQ(transition_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(transition_dims.size(), 2, "The Input(Transition) should be a 2-D tensor."); PADDLE_ENFORCE_EQ( transition_dims[0] - 2, transition_dims[1], @@ -202,13 +202,13 @@ class LinearChainCRFGradOp : public framework::OperatorWithKernel { "Input(LogLikelihood@GRAD) shoudl be not null."); auto emission_exps_dims = ctx->GetInputDim("EmissionExps"); - PADDLE_ENFORCE_EQ(emission_exps_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(emission_exps_dims.size(), 2, "The Input(EmissionExps) should be a 2-D tensor."); PADDLE_ENFORCE(emission_exps_dims[0], "An empty mini-batch is not allowed."); auto transition_exps_dims = ctx->GetInputDim("TransitionExps"); - PADDLE_ENFORCE_EQ(transition_exps_dims.size(), 2UL, + PADDLE_ENFORCE_EQ(transition_exps_dims.size(), 2, "The Input(TransitionExps) should be a 2-D tensor."); PADDLE_ENFORCE_EQ( transition_exps_dims[0] - 2, transition_exps_dims[1], diff --git a/paddle/fluid/operators/math/blas.h b/paddle/fluid/operators/math/blas.h index f67f57827bc03e134bf87edd5bf033adb5098916..ce8109f64d62b0d412419107881952f1b4ffc75e 100644 --- a/paddle/fluid/operators/math/blas.h +++ b/paddle/fluid/operators/math/blas.h @@ -184,6 +184,9 @@ class Blas { template void VINV(int n, const T* a, T* y) const; + template + void VMERF(int n, const T* a, T* y, int64_t mode) const; + private: const DeviceContext& context_; }; @@ -290,6 +293,11 @@ class BlasT : private Blas { Base()->template VINV(args...); } + template + void VMERF(ARGS... args) const { + Base()->template VMERF(args...); + } + private: const Blas* Base() const { return static_cast*>(this); diff --git a/paddle/fluid/operators/math/blas_impl.h b/paddle/fluid/operators/math/blas_impl.h index 972366bc093f4b7f0a090cf31213f75ccd89fd82..ba995dabecbfab8c4952bb7efeaa381f8078821a 100644 --- a/paddle/fluid/operators/math/blas_impl.h +++ b/paddle/fluid/operators/math/blas_impl.h @@ -123,6 +123,11 @@ struct CBlas { static void VINV(ARGS... args) { platform::dynload::vsInv(args...); } + + template + static void VMERF(ARGS... args) { + platform::dynload::vmsErf(args...); + } }; template <> @@ -223,6 +228,11 @@ struct CBlas { static void VINV(ARGS... args) { platform::dynload::vdInv(args...); } + + template + static void VMERF(ARGS... args) { + platform::dynload::vmdErf(args...); + } }; #else @@ -625,6 +635,19 @@ void Blas::VINV(int n, const T *a, T *y) const { #endif } +template <> +template +void Blas::VMERF(int n, const T *a, T *y, + int64_t mode) const { +#ifdef PADDLE_WITH_MKLML + CBlas::VMERF(n, a, y, mode); +#else + for (int i = 0; i < n; ++i) { + y[i] = std::erf(a[i]); + } +#endif +} + } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc b/paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc index e16b6f78d16ce29cc493c4c795c7fe97a4bf2550..223adcaa6b36e85ea54004c850ba6cfd142eac37 100644 --- a/paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc +++ b/paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc @@ -52,11 +52,6 @@ class MKLDNNActivationKernel "Wrong layout/format set for Input x tensor"); Functor functor; - - auto attrs = functor.GetAttrs(); - for (auto &attr : attrs) { - *attr.second = ctx.Attr(attr.first); - } functor(ctx); } }; @@ -76,11 +71,6 @@ class MKLDNNActivationGradKernel "is_test attribute should be set to False in training phase."); Functor functor; - - auto attrs = functor.GetAttrs(); - for (auto &attr : attrs) { - *attr.second = ctx.Attr(attr.first); - } functor(ctx); } }; diff --git a/paddle/fluid/operators/ngraph/CMakeLists.txt b/paddle/fluid/operators/ngraph/CMakeLists.txt index 6b256ef02666c21ec1db3f6922b56bb23363b4a0..7559d29ce233dfcebf8b3118b4c700c35fe15d32 100644 --- a/paddle/fluid/operators/ngraph/CMakeLists.txt +++ b/paddle/fluid/operators/ngraph/CMakeLists.txt @@ -2,4 +2,5 @@ if(WITH_NGRAPH) cc_library(ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto ngraph) cc_library(ngraph_engine SRCS ngraph_engine.cc DEPS ngraph_bridge framework_proto) op_library(ngraph_engine_op DEPS ngraph_engine op_registry op_info device_context) + add_subdirectory(ops) endif() diff --git a/paddle/fluid/operators/ngraph/ngraph_bridge.cc b/paddle/fluid/operators/ngraph/ngraph_bridge.cc index 36a2efc0ce113e7ca47243d7a1dee1ca998edd03..996376c53f07b5c26eccad382e734f187f75f5a1 100644 --- a/paddle/fluid/operators/ngraph/ngraph_bridge.cc +++ b/paddle/fluid/operators/ngraph/ngraph_bridge.cc @@ -19,49 +19,21 @@ limitations under the License. */ #include "ngraph/ngraph.hpp" #include "paddle/fluid/operators/ngraph/ngraph_bridge.h" #include "paddle/fluid/operators/ngraph/ngraph_ops.h" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/enforce.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { namespace operators { -namespace NG_OPS = paddle::operators::ngraphs; -std::map&, - std::shared_ptr>>)>> - NgraphBridge::NG_NODE_MAP = { - {"accuracy", NG_OPS::BuildAccuracyNode}, - {"conv2d", NG_OPS::BuildConv2dNode}, - {"conv2d_grad", NG_OPS::BuildConv2dGradNode}, - {"batch_norm", NG_OPS::BuildBatchNormNode}, - {"batch_norm_grad", NG_OPS::BuildBatchNormGradNode}, - {"cross_entropy", NG_OPS::BuildCrossEntropyNode}, - {"cross_entropy_grad", NG_OPS::BuildCrossEntropyGradNode}, - {"elementwise_add", NG_OPS::BuildElementwiseAddNode}, - {"elementwise_add_grad", NG_OPS::BuildElementwiseAddGradNode}, - {"fill_constant", NG_OPS::BuildFillConstantNode}, - {"mean", NG_OPS::BuildMeanNode}, - {"mean_grad", NG_OPS::BuildMeanGradNode}, - {"mul", NG_OPS::BuildMulNode}, - {"mul_grad", NG_OPS::BuildMulGradNode}, - {"pool2d", NG_OPS::BuildPool2dNode}, - {"pool2d_grad", NG_OPS::BuildPool2dGradNode}, - {"softmax", NG_OPS::BuildSoftmaxNode}, - {"softmax_grad", NG_OPS::BuildSoftmaxGradNode}, - {"scale", NG_OPS::BuildScaleNode}, - {"sigmoid", NG_OPS::BuildUnaryNode}, - {"sum", NG_OPS::BuildSumNode}, - {"relu", NG_OPS::BuildUnaryNode}, - {"relu_grad", NG_OPS::BuildReluGradNode}, - {"tanh", NG_OPS::BuildUnaryNode}, - {"tanh_grad", NG_OPS::BuildTanhGradNode}, - {"top_k", NG_OPS::BuildTopKNode}}; +bool NgraphBridge::isRegister(const std::string& str) { + return ops::NgraphSingleton::Lookup(str); +} void NgraphBridge::BuildNgNode( const std::shared_ptr& op) { auto& op_type = op->Type(); - NG_NODE_MAP[op_type](op, ngb_node_map_); + ops::NgraphSingleton::BuildNode(ngb_node_map_, op, op_type); } } // namespace operators diff --git a/paddle/fluid/operators/ngraph/ngraph_bridge.h b/paddle/fluid/operators/ngraph/ngraph_bridge.h index c57988f8f6322e76678c572aa21ff5b17b9e3c22..952d5b0b4362aa1c1112782885ab5d30698f5cff 100644 --- a/paddle/fluid/operators/ngraph/ngraph_bridge.h +++ b/paddle/fluid/operators/ngraph/ngraph_bridge.h @@ -28,13 +28,6 @@ namespace operators { class NgraphBridge { public: - static std::map< - std::string, - std::function&, - std::shared_ptr>>)>> - NG_NODE_MAP; - explicit NgraphBridge( std::shared_ptr< std::unordered_map>> @@ -43,6 +36,8 @@ class NgraphBridge { void BuildNgNode(const std::shared_ptr& op); + static bool isRegister(const std::string& str); + private: std::shared_ptr< std::unordered_map>> diff --git a/paddle/fluid/operators/ngraph/ngraph_engine.cc b/paddle/fluid/operators/ngraph/ngraph_engine.cc index bec4b514a218715134d2366dd7efd7cf5b377b68..660a3298cbe4bf5d83851a916bb3ea8d260214a3 100644 --- a/paddle/fluid/operators/ngraph/ngraph_engine.cc +++ b/paddle/fluid/operators/ngraph/ngraph_engine.cc @@ -88,14 +88,12 @@ static std::vector> NgraphOpIntervals( int pivot = left; while (pivot < right) { auto op_type = ops.at(pivot)->Type(); - if (NgraphBridge::NG_NODE_MAP.find(op_type) == - NgraphBridge::NG_NODE_MAP.end()) { + if (NgraphBridge::isRegister(op_type)) { ++pivot; } else { int start = pivot, end = start; while (pivot < right && - (NgraphBridge::NG_NODE_MAP.find(ops.at(pivot)->Type()) != - NgraphBridge::NG_NODE_MAP.end())) { + (!NgraphBridge::isRegister(ops.at(pivot)->Type()))) { ++pivot; ++end; } diff --git a/paddle/fluid/operators/ngraph/ngraph_ops.h b/paddle/fluid/operators/ngraph/ngraph_ops.h deleted file mode 100644 index c2fdbc670072648ac05840eec636de8ca383406b..0000000000000000000000000000000000000000 --- a/paddle/fluid/operators/ngraph/ngraph_ops.h +++ /dev/null @@ -1,38 +0,0 @@ -/* Copyright (c) 2018 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. */ - -/* - * This file contains the list of the ngraph operators for Paddle. - * - * ATTENTION: It requires some C++11 features, for lower version C++ or C, we - * might release another API. - */ - -#pragma once - -#include "ops/accuracy_op.h" -#include "ops/activation_op.h" -#include "ops/batch_norm_op.h" -#include "ops/binary_unary_op.h" -#include "ops/conv2d_op.h" -#include "ops/cross_entropy_op.h" -#include "ops/elementwise_add_op.h" -#include "ops/fill_constant_op.h" -#include "ops/mean_op.h" -#include "ops/mul_op.h" -#include "ops/pool2d_op.h" -#include "ops/scale_op.h" -#include "ops/softmax_op.h" -#include "ops/sum_op.h" -#include "ops/top_k_op.h" diff --git a/paddle/fluid/operators/ngraph/ops/CMakeLists.txt b/paddle/fluid/operators/ngraph/ops/CMakeLists.txt new file mode 100644 index 0000000000000000000000000000000000000000..7dee3308b74a70a2daf35055d3ac80a14de99ac1 --- /dev/null +++ b/paddle/fluid/operators/ngraph/ops/CMakeLists.txt @@ -0,0 +1,8 @@ +file(GLOB LIST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.h") +set(pass_file ${PADDLE_BINARY_DIR}/paddle/fluid/operators/ngraph/ngraph_ops.h) +file(APPEND ${pass_file} "\#pragma once\n") +file(WRITE ${pass_file} "// Generated by the /paddle/fluid/operators/ngraph/ops/CMakeLists.txt. DO NOT EDIT!\n\n") + +foreach(OPS_NAME ${LIST_OPS}) + file(APPEND ${pass_file} "\#include \"paddle/fluid/operators/ngraph/ops/${OPS_NAME}\"\n") +endforeach(OPS_NAME) diff --git a/paddle/fluid/operators/ngraph/ops/accuracy_op.h b/paddle/fluid/operators/ngraph/ops/accuracy_op.h index bf37ce48d8c2ce3b97fac154be9d1dfb08421f97..d90ec97298b0f6fb8480e97ca57cb427784261e4 100644 --- a/paddle/fluid/operators/ngraph/ops/accuracy_op.h +++ b/paddle/fluid/operators/ngraph/ops/accuracy_op.h @@ -17,6 +17,7 @@ limitations under the License. */ #include #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -63,3 +64,5 @@ void BuildAccuracyNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(accuracy, BuildAccuracyNode); diff --git a/paddle/fluid/operators/ngraph/ops/activation_op.h b/paddle/fluid/operators/ngraph/ops/activation_op.h index f66080e3aabc05d3ce5ecaa3791de4410e34fa37..d1b0b80d227a5042219a17e35255617726aa8042 100644 --- a/paddle/fluid/operators/ngraph/ops/activation_op.h +++ b/paddle/fluid/operators/ngraph/ops/activation_op.h @@ -17,6 +17,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -50,3 +51,6 @@ void BuildTanhGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(relu_grad, BuildReluGradNode); +REGISTER_NG_OP(than_grad, BuildTanhGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/batch_norm_op.h b/paddle/fluid/operators/ngraph/ops/batch_norm_op.h index f0d2d5f27f81c1cc5b0774478ea00e5350049ac2..2d638bb53f084ee75014d64302ec3d86b3bcf26f 100644 --- a/paddle/fluid/operators/ngraph/ops/batch_norm_op.h +++ b/paddle/fluid/operators/ngraph/ops/batch_norm_op.h @@ -20,6 +20,7 @@ limitations under the License. */ #include "ngraph/ngraph.hpp" #include "paddle/fluid/operators/ngraph/ops/elementwise_node.h" #include "paddle/fluid/operators/ngraph/ops/elementwise_scalar_op.h" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -155,3 +156,6 @@ void BuildBatchNormGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(batch_norm, BuildBatchNormNode); +REGISTER_NG_OP(batch_norm_grad, BuildBatchNormGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/binary_unary_op.h b/paddle/fluid/operators/ngraph/ops/binary_unary_op.h index 0c0d25d0cd1ae536618057ce80388b8eeb81c68a..375f188286c123b1d652f8780989404760c8e1a4 100644 --- a/paddle/fluid/operators/ngraph/ops/binary_unary_op.h +++ b/paddle/fluid/operators/ngraph/ops/binary_unary_op.h @@ -16,6 +16,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -47,3 +48,7 @@ static void BuildUnaryNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(relu, BuildUnaryNode); +REGISTER_NG_OP(tanh, BuildUnaryNode); +REGISTER_NG_OP(sigmoid, BuildUnaryNode); diff --git a/paddle/fluid/operators/ngraph/ops/conv2d_op.h b/paddle/fluid/operators/ngraph/ops/conv2d_op.h index 46fb2703f51482afa0546f08b8fc7b2c98e281bc..d664825c53ebf17435a0ec532969978abe6d30ca 100644 --- a/paddle/fluid/operators/ngraph/ops/conv2d_op.h +++ b/paddle/fluid/operators/ngraph/ops/conv2d_op.h @@ -17,6 +17,7 @@ limitations under the License. */ #include #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -233,3 +234,6 @@ void BuildConv2dGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(conv2d, BuildConv2dNode); +REGISTER_NG_OP(conv2d_grad, BuildConv2dGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/cross_entropy_op.h b/paddle/fluid/operators/ngraph/ops/cross_entropy_op.h index f88a2cb94103b2305875655cefaec16263b4bf4f..3ab158f3e13a33bdb7e423919c7592831fa9831a 100644 --- a/paddle/fluid/operators/ngraph/ops/cross_entropy_op.h +++ b/paddle/fluid/operators/ngraph/ops/cross_entropy_op.h @@ -18,6 +18,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -143,3 +144,6 @@ void BuildCrossEntropyGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(cross_entropy, BuildCrossEntropyNode); +REGISTER_NG_OP(cross_entropy_grad, BuildCrossEntropyGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/elementwise_add_op.h b/paddle/fluid/operators/ngraph/ops/elementwise_add_op.h index 868df51e16a9714a750bac64dadc3441de79165e..fb796c336a9b45966a0ff703286faa8b61752483 100644 --- a/paddle/fluid/operators/ngraph/ops/elementwise_add_op.h +++ b/paddle/fluid/operators/ngraph/ops/elementwise_add_op.h @@ -19,6 +19,7 @@ limitations under the License. */ #include "ngraph/ngraph.hpp" #include "paddle/fluid/operators/ngraph/ops/elementwise_node.h" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -85,3 +86,6 @@ void BuildElementwiseAddGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(elementwise_add, BuildElementwiseAddNode); +REGISTER_NG_OP(elementwise_add_grad, BuildElementwiseAddGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/fill_constant_op.h b/paddle/fluid/operators/ngraph/ops/fill_constant_op.h index 58783bc220fa02879aaebacc5ac55a07b13184f1..bc958f2ba27cf929408d56d41bf22976caf7d6ae 100644 --- a/paddle/fluid/operators/ngraph/ops/fill_constant_op.h +++ b/paddle/fluid/operators/ngraph/ops/fill_constant_op.h @@ -17,6 +17,7 @@ limitations under the License. */ #include #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -55,3 +56,5 @@ void BuildFillConstantNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(fill_constant, BuildFillConstantNode); diff --git a/paddle/fluid/operators/ngraph/ops/mean_op.h b/paddle/fluid/operators/ngraph/ops/mean_op.h index 4c44bc4c112f401c2707f7babd49a33f238a768f..f839d9978d71c2967a7f2c2f22622dc615907831 100644 --- a/paddle/fluid/operators/ngraph/ops/mean_op.h +++ b/paddle/fluid/operators/ngraph/ops/mean_op.h @@ -19,6 +19,7 @@ limitations under the License. */ #include "ngraph/ngraph.hpp" #include "paddle/fluid/operators/ngraph/ops/elementwise_scalar_op.h" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -64,3 +65,6 @@ void BuildMeanGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(mean, BuildMeanNode); +REGISTER_NG_OP(mean_grad, BuildMeanGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/momentum_op.h b/paddle/fluid/operators/ngraph/ops/momentum_op.h new file mode 100644 index 0000000000000000000000000000000000000000..b8291a08a28b585a7ceb67642ba28c3314195790 --- /dev/null +++ b/paddle/fluid/operators/ngraph/ops/momentum_op.h @@ -0,0 +1,104 @@ +/*Copyright (c) 2018 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. */ + +#pragma once + +#include +#include +#include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" +#include "paddle/fluid/platform/ngraph_helper.h" + +namespace paddle { +namespace operators { +namespace ngraphs { + +void BuildMomentumNode( + const std::shared_ptr& op, + std::shared_ptr< + std::unordered_map>> + ngb_node_map) { + auto op_attrs = paddle::framework::AttrReader(op->Attrs()); + auto param = paddle::platform::GetInputNode(op, "Param", ngb_node_map); + auto grad = paddle::platform::GetInputNode(op, "Grad", ngb_node_map); + auto velocity = paddle::platform::GetInputNode(op, "Velocity", ngb_node_map); + auto learning_rate = + paddle::platform::GetInputNode(op, "LearningRate", ngb_node_map); + + auto mu = op_attrs.Get("mu"); + bool use_nesterov = op_attrs.Get("use_nesterov"); + + auto param_shape = param->get_shape(); + auto velocity_shape = velocity->get_shape(); + auto grad_shape = grad->get_shape(); + auto lr_shape = learning_rate->get_shape(); + + auto shape_velocity = ngraph::Shape{velocity_shape}; + auto mu_create = + ngraph::op::Constant::create(ngraph::element::f32, shape_velocity, {mu}); + + auto vel_mul = std::make_shared(velocity, mu_create); + auto vel_out = std::make_shared(vel_mul, grad); + + ngraph::NodeVector result; + if (use_nesterov) { + auto mul_res = std::make_shared(vel_out, mu_create); + auto add_res = std::make_shared(grad, mul_res); + + auto add_2d = paddle::platform::FlattenTo2d(add_res->get_shape(), 0); + auto vel_reshape = paddle::platform::NgReshaper(vel_out, add_2d); + + auto lr_bcast = std::make_shared( + learning_rate, vel_reshape->get_shape(), + ngraph::AxisSet{vel_reshape->get_shape().size() - 1}); + + auto lr_1d = paddle::platform::FlattenTo1d(lr_bcast->get_shape(), 0); + auto lr_reshape = std::make_shared( + lr_bcast, ngraph::AxisVector{0, 1}, lr_1d); + + lr_reshape = std::make_shared( + lr_reshape, ngraph::AxisVector{0}, param->get_shape()); + + auto mul_res1 = std::make_shared(add_res, lr_reshape); + auto res = std::make_shared(param, mul_res1); + paddle::platform::SetOutputNode(op, "ParamOut", res, ngb_node_map); + } else { + auto vel_2d = paddle::platform::FlattenTo2d(vel_out->get_shape(), 0); + auto vel_reshape = paddle::platform::NgReshaper(vel_out, vel_2d); + + auto lr_bcast = std::make_shared( + learning_rate, vel_reshape->get_shape(), + ngraph::AxisSet{vel_reshape->get_shape().size() - 1}); + + auto lr_1d = paddle::platform::FlattenTo1d(lr_bcast->get_shape(), 0); + auto lr_reshape = std::make_shared( + lr_bcast, ngraph::AxisVector{0, 1}, lr_1d); + + lr_reshape = std::make_shared( + lr_reshape, ngraph::AxisVector{0}, param->get_shape()); + + auto mul_result = + std::make_shared(lr_reshape, vel_out); + + auto res = std::make_shared(param, mul_result); + paddle::platform::SetOutputNode(op, "ParamOut", res, ngb_node_map); + } + paddle::platform::SetOutputNode(op, "VelocityOut", vel_out, ngb_node_map); +} + +} // namespace ngraphs +} // namespace operators +} // namespace paddle + +REGISTER_NG_OP(momentum, BuildMomentumNode); diff --git a/paddle/fluid/operators/ngraph/ops/mul_op.h b/paddle/fluid/operators/ngraph/ops/mul_op.h index 4a6cbebe245f891c6c33b2116330a41d89d50e25..98c70a1a99aa899ed8fdd3c4674668cefd14c4ae 100644 --- a/paddle/fluid/operators/ngraph/ops/mul_op.h +++ b/paddle/fluid/operators/ngraph/ops/mul_op.h @@ -16,6 +16,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -130,3 +131,6 @@ static void BuildMulGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(mul, BuildMulNode); +REGISTER_NG_OP(mul_grad, BuildMulGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/op_bridge.h b/paddle/fluid/operators/ngraph/ops/op_bridge.h new file mode 100644 index 0000000000000000000000000000000000000000..93df0ad8062745380d9cd4ca5027bef1425083bf --- /dev/null +++ b/paddle/fluid/operators/ngraph/ops/op_bridge.h @@ -0,0 +1,84 @@ +/* Copyright (c) 2018 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. */ + +#pragma once +#include +#include +#include +#include + +#include "ngraph/node.hpp" +#include "paddle/fluid/framework/operator.h" +#include "paddle/fluid/operators/ngraph/ngraph_bridge.h" +#include "paddle/fluid/platform/enforce.h" + +namespace paddle { +namespace operators { +namespace ops { + +class NgraphSingleton { + NgraphSingleton() = default; + NgraphSingleton(NgraphSingleton const&) = delete; + void operator=(NgraphSingleton const) = delete; + + ~NgraphSingleton() = default; + + static std::map< + std::string, + std::function&, + std::shared_ptr>>)>> + ng_node_maps_; + + public: + template + static void Register(TF&& tf, const std::string& name) { + ng_node_maps_[name] = tf; + } + + static bool Lookup(const std::string& name) { + auto it = ng_node_maps_.find(name); + if (it == ng_node_maps_.end()) { + return true; + } + return false; + } + + static void BuildNode( + const std::shared_ptr>>& ng_maps, + const std::shared_ptr& op, + const std::string& name) { + ng_node_maps_[name](op, ng_maps); + } +}; + +std::map&, + std::shared_ptr>>)>> + NgraphSingleton::ng_node_maps_; + +} // namespace ops +} // namespace operators +} // namespace paddle + +#define REGISTER_NG_OP(op_type__, Converter__) \ + struct ng_##op_type__##_converter { \ + ng_##op_type__##_converter() { \ + paddle::operators::ops::NgraphSingleton::Register( \ + paddle::operators::ngraphs::Converter__, #op_type__); \ + } \ + }; \ + ng_##op_type__##_converter ng_##op_type__##_converter__; diff --git a/paddle/fluid/operators/ngraph/ops/pool2d_op.h b/paddle/fluid/operators/ngraph/ops/pool2d_op.h index 836c9d6c185b305d3dd4c9e9d30e23abb0c1431c..a6371372ef10c093c41153cb0dc73f4f9e95687f 100644 --- a/paddle/fluid/operators/ngraph/ops/pool2d_op.h +++ b/paddle/fluid/operators/ngraph/ops/pool2d_op.h @@ -18,6 +18,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -172,3 +173,6 @@ void BuildPool2dGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(pool2d, BuildPool2dNode); +REGISTER_NG_OP(pool2d_grad, BuildPool2dGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/scale_op.h b/paddle/fluid/operators/ngraph/ops/scale_op.h index 91a57d0be606373e985a30b7ac9c73648062d8e4..a334192419f572c429f5842cd9e418d8945eb0ef 100644 --- a/paddle/fluid/operators/ngraph/ops/scale_op.h +++ b/paddle/fluid/operators/ngraph/ops/scale_op.h @@ -17,6 +17,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" #include "paddle/fluid/operators/ngraph/ops/elementwise_scalar_op.h" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -37,3 +38,5 @@ void BuildScaleNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(scale, BuildScaleNode); diff --git a/paddle/fluid/operators/ngraph/ops/softmax_op.h b/paddle/fluid/operators/ngraph/ops/softmax_op.h index fc6395c08bc6b00990679c5327c3152a980be821..1df6418de06d000892d2802596df61320fcdc759 100644 --- a/paddle/fluid/operators/ngraph/ops/softmax_op.h +++ b/paddle/fluid/operators/ngraph/ops/softmax_op.h @@ -18,6 +18,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" #include "paddle/fluid/operators/ngraph/ops/elementwise_scalar_op.h" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -72,3 +73,6 @@ void BuildSoftmaxGradNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(softmax, BuildSoftmaxNode); +REGISTER_NG_OP(softmax_grad, BuildSoftmaxGradNode); diff --git a/paddle/fluid/operators/ngraph/ops/top_k_op.h b/paddle/fluid/operators/ngraph/ops/top_k_op.h index 852ecd7139a3c7046e78265ca021b2ce286c63c0..6d10faa7c2efb9cbd87fa8ef1c6ecb4fa350d8f6 100644 --- a/paddle/fluid/operators/ngraph/ops/top_k_op.h +++ b/paddle/fluid/operators/ngraph/ops/top_k_op.h @@ -16,6 +16,7 @@ limitations under the License. */ #include #include "ngraph/ngraph.hpp" +#include "paddle/fluid/operators/ngraph/ops/op_bridge.h" #include "paddle/fluid/platform/ngraph_helper.h" namespace paddle { @@ -42,3 +43,5 @@ void BuildTopKNode( } // namespace ngraphs } // namespace operators } // namespace paddle + +REGISTER_NG_OP(top_k, BuildTopKNode); diff --git a/paddle/fluid/operators/reader/read_op.cc b/paddle/fluid/operators/reader/read_op.cc index 8fe638ac2fdc6e0baed7d6cd3c57b72f23164129..846b2ed77e46d82fbeda8faaeed99cddf23c8824 100644 --- a/paddle/fluid/operators/reader/read_op.cc +++ b/paddle/fluid/operators/reader/read_op.cc @@ -85,9 +85,7 @@ class ReadOp : public framework::OperatorBase { std::vector ins; // For profiling - platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance(); - auto& ctx = *pool.Get(dev_place); - platform::RecordEvent record_event(Type(), &ctx); + platform::RecordEvent record_event(Type()); reader->ReadNext(&ins); if (ins.empty()) { diff --git a/paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc b/paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc index 1eebadc2c980ddf1cbaaefef1568dd401d0c77ed..0932211cadf30d0c464d43ca652a5c52df15747e 100644 --- a/paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc +++ b/paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc @@ -31,10 +31,10 @@ class SequenceEnumerateOp : public framework::OperatorWithKernel { const auto x_dims = ctx->GetInputDim("X"); PADDLE_ENFORCE_EQ( - x_dims.size(), 2UL, + x_dims.size(), 2, "Input(X) of SequenceEnumerate operator's rank should be 2."); PADDLE_ENFORCE_EQ( - x_dims[1], 1UL, + x_dims[1], 1, "Input(X) of SequenceEnumerate operator's 2nd dimension should be 1."); const auto win_size = ctx->Attrs().Get("win_size"); diff --git a/paddle/fluid/operators/sequence_ops/sequence_expand_op.cc b/paddle/fluid/operators/sequence_ops/sequence_expand_op.cc index 27e0201bd70df59c58eaa7567d5bb69eb1b721b4..f6c42415301bc8d6f3509bfba2ff356265643bad 100644 --- a/paddle/fluid/operators/sequence_ops/sequence_expand_op.cc +++ b/paddle/fluid/operators/sequence_ops/sequence_expand_op.cc @@ -48,10 +48,10 @@ class SequenceExpandOp : public framework::OperatorWithKernel { auto& x_lod = x_var->Get().lod(); auto& y_lod = y_var->Get().lod(); - PADDLE_ENFORCE_LE(x_lod.size(), 1, + PADDLE_ENFORCE_LE(x_lod.size(), 1UL, "Level number of Input(X)'s lod should not be " "greater than 1."); - PADDLE_ENFORCE_GT(y_lod.size(), 0, + PADDLE_ENFORCE_GT(y_lod.size(), 0UL, "Level number of Input(Y)'s lod should be " "greater than 0."); PADDLE_ENFORCE( @@ -69,7 +69,8 @@ class SequenceExpandOp : public framework::OperatorWithKernel { "size of Input(X)'s first level lod should be equal to " "size of Input(Y)'s referred level lod."); } else { - PADDLE_ENFORCE_EQ(x_dims[0], y_lod[ref_level].size() - 1, + PADDLE_ENFORCE_EQ(x_dims[0], + static_cast(y_lod[ref_level].size()) - 1, "When Input(X)'s lod is null, the dims[0] of " "Input(X) should match the " "size of Input(Y)'s referred level lod."); diff --git a/paddle/fluid/operators/shape_op.cc b/paddle/fluid/operators/shape_op.cc index 1be9fe47af71d31ce2e0eba807ea4a43601f8aca..efc497fa47d1d954bbd1e214b43f5de4c76b0714 100644 --- a/paddle/fluid/operators/shape_op.cc +++ b/paddle/fluid/operators/shape_op.cc @@ -35,14 +35,15 @@ class ShapeOp : public framework::OperatorWithKernel { class ShapeOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { - AddInput("Input", "(Tensor), The input tensor."); - AddOutput("Out", - "(Tensor), The shape of input tensor, the data type of the shape" - " is int32_t, will be on the same device with the input Tensor."); + AddInput("Input", "(LoDTensor), The input tensor."); + AddOutput( + "Out", + "(LoDTensor), The shape of input tensor, the data type of the shape" + " is int32_t, will be on the same device with the input Tensor."); AddComment(R"DOC( -Shape Operator +Shape Operator. -Get the shape of input tensor. Only support CPU input Tensor now. +Return the shape of the input. )DOC"); } }; diff --git a/paddle/fluid/platform/CMakeLists.txt b/paddle/fluid/platform/CMakeLists.txt index fbb2ac3fe8c5de9b0be593df225677c6a7a89e9c..b7e84031e7b7e821d51caf405978d07995ea0e91 100644 --- a/paddle/fluid/platform/CMakeLists.txt +++ b/paddle/fluid/platform/CMakeLists.txt @@ -36,7 +36,7 @@ cc_test(cpu_info_test SRCS cpu_info_test.cc DEPS cpu_info) nv_library(gpu_info SRCS gpu_info.cc DEPS gflags glog enforce) -cc_library(place SRCS place.cc DEPS enforce boost lib_any) +cc_library(place SRCS place.cc DEPS enforce boost) cc_test(place_test SRCS place_test.cc DEPS place glog gflags) add_subdirectory(dynload) @@ -87,8 +87,12 @@ nv_test(transform_test SRCS transform_test.cu DEPS memory place device_context) cc_library(timer SRCS timer.cc) cc_test(timer_test SRCS timer_test.cc DEPS timer) -cc_library(device_tracer SRCS device_tracer.cc DEPS boost profiler_proto framework_proto ${GPU_CTX_DEPS}) -cc_library(profiler SRCS profiler.cc DEPS device_context device_tracer) +cc_library(device_tracer SRCS device_tracer.cc DEPS boost profiler_proto framework_proto device_context ${GPU_CTX_DEPS}) +if(WITH_GPU) + nv_library(profiler SRCS profiler.cc profiler.cu DEPS device_context device_tracer) +else() + cc_library(profiler SRCS profiler.cc DEPS device_context device_tracer) +endif() cc_test(profiler_test SRCS profiler_test.cc DEPS profiler) nv_test(float16_gpu_test SRCS float16_test.cu DEPS lod_tensor) diff --git a/paddle/fluid/platform/device_context.cc b/paddle/fluid/platform/device_context.cc index 2493fb71c019f9923012afa4a46cb3e95479f860..ed0dbdeb13ce93926c023f9f435776f1a1839933 100644 --- a/paddle/fluid/platform/device_context.cc +++ b/paddle/fluid/platform/device_context.cc @@ -291,7 +291,7 @@ CUDADeviceContext::CUDADeviceContext(CUDAPlace place) if (dynload::HasCUDNN()) { auto local_cudnn_version = cudnn_dso_ver / 100; auto compile_cudnn_version = CUDNN_VERSION / 100; - if (local_cudnn_version < compile_cudnn_version) { + if (local_cudnn_version < static_cast(compile_cudnn_version)) { LOG_FIRST_N(WARNING, 1) << "WARNING: device: " << place_.device << ". The installed Paddle is compiled with CUDNN " diff --git a/paddle/fluid/platform/device_tracer.cc b/paddle/fluid/platform/device_tracer.cc index 0a4563ead65b1e45adca1d1a1fce066a1a55d932..52372c25143be251b69d5f41a211ac090bba2063 100644 --- a/paddle/fluid/platform/device_tracer.cc +++ b/paddle/fluid/platform/device_tracer.cc @@ -14,17 +14,23 @@ limitations under the License. */ #include "paddle/fluid/platform/device_tracer.h" #include +#include #include +#include #include #include // NOLINT #include +#include #include #include // NOLINT +#include +#include #include #include "glog/logging.h" #include "google/protobuf/text_format.h" #include "paddle/fluid/framework/block_desc.h" +#include "paddle/fluid/platform/profiler.h" #include "paddle/fluid/string/printf.h" namespace paddle { @@ -33,17 +39,31 @@ namespace { // Tracking the nested block stacks of each thread. thread_local std::deque block_id_stack; // Tracking the nested event stacks. -thread_local std::deque annotation_stack; +thread_local std::deque annotation_stack; + +std::map system_thread_id_map; std::once_flag tracer_once_flag; DeviceTracer *tracer = nullptr; + +void PrintCuptiHint() { + static bool showed = false; + if (showed) return; + showed = true; + LOG(WARNING) << "Invalid timestamp occured. Please try increasing the " + "FLAGS_multiple_of_cupti_buffer_size."; +} + } // namespace #ifdef PADDLE_WITH_CUPTI namespace { -// TODO(panyx0718): Revisit the buffer size here. -uint64_t kBufSize = 32 * 1024; +// The experimental best performance is +// the same size with CUPTI device buffer size(8M) +uint64_t kBufSize = 1024 * 1024 * 8; uint64_t kAlignSize = 8; +std::unordered_map runtime_cbid_str, + driver_cbid_str; #define ALIGN_BUFFER(buffer, align) \ (((uintptr_t)(buffer) & ((align)-1)) \ @@ -92,15 +112,33 @@ std::string MemcpyKind(CUpti_ActivityMemcpyKind kind) { return "MEMCPY"; } +std::string DriverKind(CUpti_CallbackId cbid) { + auto iter = driver_cbid_str.find(cbid); + if (iter == driver_cbid_str.end()) + return "Driver API " + std::to_string(cbid); + return iter->second; +} + +std::string RuntimeKind(CUpti_CallbackId cbid) { + auto iter = runtime_cbid_str.find(cbid); + if (iter == runtime_cbid_str.end()) + return "Runtime API " + std::to_string(cbid); + return iter->second; +} + void EnableActivity() { // Device activity record is created when CUDA initializes, so we // want to enable it before cuInit() or any CUDA runtime call. CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_MEMCPY)); - CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_KERNEL)); - CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_DEVICE)); - CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_MEMSET)); - CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_OVERHEAD)); + CUPTI_CALL( + dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_CONCURRENT_KERNEL)); + // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_KERNEL)); + CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_DRIVER)); + CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_RUNTIME)); // We don't track these activities for now. + // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_MEMSET)); + // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_OVERHEAD)); + // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_DEVICE)); // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_CONTEXT)); // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_DRIVER)); // CUPTI_CALL(dynload::cuptiActivityEnable(CUPTI_ACTIVITY_KIND_RUNTIME)); @@ -110,16 +148,17 @@ void EnableActivity() { void DisableActivity() { CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_MEMCPY)); - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_KERNEL)); - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_DEVICE)); + CUPTI_CALL( + dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_CONCURRENT_KERNEL)); + // CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_DEVICE)); // Disable all other activity record kinds. - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_CONTEXT)); + // CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_CONTEXT)); CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_DRIVER)); CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_RUNTIME)); - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_MEMSET)); - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_NAME)); - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_MARKER)); - CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_OVERHEAD)); + // CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_MEMSET)); + // CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_NAME)); + // CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_MARKER)); + // CUPTI_CALL(dynload::cuptiActivityDisable(CUPTI_ACTIVITY_KIND_OVERHEAD)); } void CUPTIAPI bufferRequested(uint8_t **buffer, size_t *size, @@ -132,6 +171,11 @@ void CUPTIAPI bufferRequested(uint8_t **buffer, size_t *size, void CUPTIAPI bufferCompleted(CUcontext ctx, uint32_t streamId, uint8_t *buffer, size_t size, size_t validSize) { + static std::thread::id cupti_thread_id(0); + if (cupti_thread_id == std::thread::id(0)) + cupti_thread_id = std::this_thread::get_id(); + PADDLE_ENFORCE_EQ(std::this_thread::get_id(), cupti_thread_id, + "Only one thread is allowed to call bufferCompleted()"); CUptiResult status; CUpti_Activity *record = NULL; if (validSize > 0) { @@ -168,6 +212,23 @@ void CUPTIAPI bufferCompleted(CUcontext ctx, uint32_t streamId, uint8_t *buffer, memcpy->correlationId, memcpy->bytes); break; } + case CUPTI_ACTIVITY_KIND_DRIVER: { + auto *api = reinterpret_cast(record); + if (api->start != 0 && api->end != 0) + // -1 device id represents CUDA api call + tracer->AddCPURecords( + DriverKind(api->cbid), api->start, api->end, -1, + GetThreadIdFromSystemThreadId(api->threadId)); + break; + } + case CUPTI_ACTIVITY_KIND_RUNTIME: { + auto *api = reinterpret_cast(record); + if (api->start != 0 && api->end != 0) + tracer->AddCPURecords( + RuntimeKind(api->cbid), api->start, api->end, -1, + GetThreadIdFromSystemThreadId(api->threadId)); + break; + } default: { break; } } } else if (status == CUPTI_ERROR_MAX_LIMIT_REACHED) { @@ -183,21 +244,35 @@ void CUPTIAPI bufferCompleted(CUcontext ctx, uint32_t streamId, uint8_t *buffer, dynload::cuptiActivityGetNumDroppedRecords(ctx, streamId, &dropped)); if (dropped != 0) { fprintf(stderr, "Dropped %u activity records\n", (unsigned int)dropped); + PrintCuptiHint(); } } free(buffer); } + +void initCuptiCbidStr(); + } // namespace #endif // PADDLE_WITH_CUPTI class DeviceTracerImpl : public DeviceTracer { public: - DeviceTracerImpl() : enabled_(false) {} + DeviceTracerImpl() : enabled_(false) { +#ifdef PADDLE_WITH_CUPTI + initCuptiCbidStr(); +#endif + } - void AddAnnotation(uint64_t id, const std::string &anno) { - std::lock_guard l(trace_mu_); - correlations_[id] = anno; + void AddAnnotation(uint32_t id, Event *event) { + thread_local std::forward_list> + *local_correlations_pairs = nullptr; + if (local_correlations_pairs == nullptr) { + std::lock_guard l(trace_mu_); + correlations_pairs.emplace_front(); + local_correlations_pairs = &correlations_pairs.front(); + } + local_correlations_pairs->push_front(std::make_pair(id, event)); } void AddCPURecords(const std::string &anno, uint64_t start_ns, @@ -206,8 +281,13 @@ class DeviceTracerImpl : public DeviceTracer { VLOG(1) << "Empty timeline annotation."; return; } - std::lock_guard l(trace_mu_); - cpu_records_.push_back( + thread_local std::forward_list *local_cpu_records_ = nullptr; + if (local_cpu_records_ == nullptr) { + std::lock_guard l(trace_mu_); + cpu_records_.emplace_front(); + local_cpu_records_ = &cpu_records_.front(); + } + local_cpu_records_->push_front( CPURecord{anno, start_ns, end_ns, device_id, thread_id}); } @@ -215,25 +295,27 @@ class DeviceTracerImpl : public DeviceTracer { uint64_t end_ns, int64_t device_id, int64_t stream_id, uint32_t correlation_id, uint64_t bytes) { // 0 means timestamp information could not be collected for the kernel. - if (start_ns == 0 || end_ns == 0) { + if (start_ns == 0 || end_ns == 0 || start_ns == end_ns) { VLOG(3) << name << " cannot be traced"; + PrintCuptiHint(); return; } - std::lock_guard l(trace_mu_); - mem_records_.push_back(MemRecord{name, start_ns, end_ns, device_id, - stream_id, correlation_id, bytes}); + // NOTE(liangdun): lock is not needed, only one thread call this function. + mem_records_.push_front(MemRecord{name, start_ns, end_ns, device_id, + stream_id, correlation_id, bytes}); } void AddKernelRecords(std::string name, uint64_t start, uint64_t end, int64_t device_id, int64_t stream_id, uint32_t correlation_id) { // 0 means timestamp information could not be collected for the kernel. - if (start == 0 || end == 0) { + if (start == 0 || end == 0 || start == end) { VLOG(3) << correlation_id << " cannot be traced"; + PrintCuptiHint(); return; } - std::lock_guard l(trace_mu_); - kernel_records_.push_back( + // NOTE(liangdun): lock is not needed, only one thread call this function. + kernel_records_.push_front( KernelRecord{name, start, end, device_id, stream_id, correlation_id}); } @@ -263,25 +345,80 @@ class DeviceTracerImpl : public DeviceTracer { } else if (ret != CUPTI_SUCCESS) { fprintf(stderr, "Failed to create CUPTI subscriber.\n"); } - CUPTI_CALL( - dynload::cuptiEnableCallback(1, subscriber_, CUPTI_CB_DOMAIN_DRIVER_API, - CUPTI_DRIVER_TRACE_CBID_cuLaunchKernel)); + const std::vector cbids { + CUPTI_RUNTIME_TRACE_CBID_cudaMemcpy_v3020, + CUPTI_RUNTIME_TRACE_CBID_cudaMemcpyAsync_v3020, + CUPTI_RUNTIME_TRACE_CBID_cudaLaunch_v3020, + CUPTI_RUNTIME_TRACE_CBID_cudaLaunchKernel_v7000 +#if CUDA_VERSION >= 9000 + , + CUPTI_RUNTIME_TRACE_CBID_cudaLaunchCooperativeKernel_v9000, + CUPTI_RUNTIME_TRACE_CBID_cudaLaunchCooperativeKernelMultiDevice_v9000 +#endif + }; + for (auto cbid : cbids) + CUPTI_CALL(dynload::cuptiEnableCallback( + 1, subscriber_, CUPTI_CB_DOMAIN_RUNTIME_API, cbid)); CUPTI_CALL(dynload::cuptiGetTimestamp(&start_ns_)); #endif // PADDLE_WITH_CUPTI enabled_ = true; } + void Reset() { +#ifdef PADDLE_WITH_CUPTI + CUPTI_CALL( + dynload::cuptiActivityFlushAll(CUPTI_ACTIVITY_FLAG_FLUSH_FORCED)); +#endif + std::lock_guard l(trace_mu_); + kernel_records_.clear(); + mem_records_.clear(); + correlations_.clear(); + for (auto &tmp : correlations_pairs) tmp.clear(); + for (auto &tmp : cpu_records_) tmp.clear(); + } + + void GenEventKernelCudaElapsedTime() { +#ifdef PADDLE_WITH_CUPTI + if (correlations_.empty()) + for (auto &tmp : correlations_pairs) + for (auto &pair : tmp) correlations_[pair.first] = pair.second; + for (const KernelRecord &r : kernel_records_) { + auto c = correlations_.find(r.correlation_id); + if (c != correlations_.end() && c->second != nullptr) { + Event *e = c->second; + e->AddCudaElapsedTime(r.start_ns, r.end_ns); + } + } + for (const auto &r : mem_records_) { + auto c = correlations_.find(r.correlation_id); + if (c != correlations_.end() && c->second != nullptr) { + Event *e = c->second; + e->AddCudaElapsedTime(r.start_ns, r.end_ns); + } + } +#endif + } + proto::Profile GenProfile(const std::string &profile_path) { + int miss = 0, find = 0; std::lock_guard l(trace_mu_); proto::Profile profile_pb; profile_pb.set_start_ns(start_ns_); profile_pb.set_end_ns(end_ns_); + if (correlations_.empty()) + for (auto &tmp : correlations_pairs) + for (auto &pair : tmp) correlations_[pair.first] = pair.second; for (const KernelRecord &r : kernel_records_) { auto *event = profile_pb.add_events(); event->set_type(proto::Event::GPUKernel); - if (correlations_.find(r.correlation_id) != correlations_.end()) { - event->set_name(correlations_.at(r.correlation_id)); + auto c = correlations_.find(r.correlation_id); + if (c != correlations_.end() && c->second != nullptr) { + event->set_name(c->second->name()); + event->set_detail_info(r.name); + find++; } else { + VLOG(10) << "Missing Kernel Event: " + r.name; + miss++; event->set_name(r.name); } event->set_start_ns(r.start_ns); @@ -289,31 +426,41 @@ class DeviceTracerImpl : public DeviceTracer { event->set_sub_device_id(r.stream_id); event->set_device_id(r.device_id); } - - for (const CPURecord &r : cpu_records_) { - auto *event = profile_pb.add_events(); - event->set_type(proto::Event::CPU); - event->set_name(r.name); - event->set_start_ns(r.start_ns); - event->set_end_ns(r.end_ns); - event->set_sub_device_id(r.thread_id); - event->set_device_id(r.device_id); - } + VLOG(1) << "KernelRecord event miss: " << miss << " find: " << find; + for (auto &tmp : cpu_records_) + for (const CPURecord &r : tmp) { + auto *event = profile_pb.add_events(); + event->set_type(proto::Event::CPU); + event->set_name(r.name); + event->set_start_ns(r.start_ns); + event->set_end_ns(r.end_ns); + event->set_sub_device_id(r.thread_id); + event->set_device_id(r.device_id); + } + miss = find = 0; for (const MemRecord &r : mem_records_) { auto *event = profile_pb.add_events(); event->set_type(proto::Event::GPUKernel); - event->set_name(r.name); + auto c = correlations_.find(r.correlation_id); + if (c != correlations_.end() && c->second != nullptr) { + event->set_name(c->second->name()); + event->set_detail_info(r.name); + find++; + } else { + miss++; + event->set_name(r.name); + } event->set_start_ns(r.start_ns); event->set_end_ns(r.end_ns); event->set_sub_device_id(r.stream_id); event->set_device_id(r.device_id); event->mutable_memcopy()->set_bytes(r.bytes); } + VLOG(1) << "MemRecord event miss: " << miss << " find: " << find; std::ofstream profile_f; - profile_f.open(profile_path, std::ios::out | std::ios::trunc); - std::string profile_str; - profile_pb.SerializeToString(&profile_str); - profile_f << profile_str; + profile_f.open(profile_path, + std::ios::out | std::ios::trunc | std::ios::binary); + profile_pb.SerializeToOstream(&profile_f); profile_f.close(); return profile_pb; } @@ -321,12 +468,13 @@ class DeviceTracerImpl : public DeviceTracer { void Disable() { #ifdef PADDLE_WITH_CUPTI // flush might cause additional calls to DeviceTracker. - dynload::cuptiActivityFlushAll(CUPTI_ACTIVITY_FLAG_FLUSH_FORCED); + CUPTI_CALL( + dynload::cuptiActivityFlushAll(CUPTI_ACTIVITY_FLAG_FLUSH_FORCED)); #endif // PADDLE_WITH_CUPTI std::lock_guard l(trace_mu_); #ifdef PADDLE_WITH_CUPTI DisableActivity(); - dynload::cuptiUnsubscribe(subscriber_); + CUPTI_CALL(dynload::cuptiUnsubscribe(subscriber_)); CUPTI_CALL(dynload::cuptiGetTimestamp(&end_ns_)); #endif // PADDLE_WITH_CUPTI enabled_ = false; @@ -337,18 +485,10 @@ class DeviceTracerImpl : public DeviceTracer { static void CUPTIAPI ApiCallback(void *userdata, CUpti_CallbackDomain domain, CUpti_CallbackId cbid, const void *cbdata) { auto *cbInfo = reinterpret_cast(cbdata); - DeviceTracer *tracer = reinterpret_cast(userdata); - - if ((domain == CUPTI_CB_DOMAIN_DRIVER_API) && - (cbid == CUPTI_DRIVER_TRACE_CBID_cuLaunchKernel)) { - if (cbInfo->callbackSite == CUPTI_API_ENTER) { - const std::string anno = !annotation_stack.empty() - ? annotation_stack.back() - : cbInfo->symbolName; - tracer->AddAnnotation(cbInfo->correlationId, anno); - } - } else { - VLOG(1) << "Unhandled API Callback for " << domain << " " << cbid; + DeviceTracerImpl *tracer = reinterpret_cast(userdata); + if (cbInfo->callbackSite == CUPTI_API_ENTER) { + Event *event = CurAnnotation(); + tracer->AddAnnotation(cbInfo->correlationId, event); } } CUpti_SubscriberHandle subscriber_; @@ -357,10 +497,12 @@ class DeviceTracerImpl : public DeviceTracer { bool enabled_; uint64_t start_ns_; uint64_t end_ns_; - std::vector kernel_records_; - std::vector mem_records_; - std::vector cpu_records_; - std::unordered_map correlations_; + std::forward_list kernel_records_; + std::forward_list mem_records_; + std::forward_list> cpu_records_; + std::forward_list>> + correlations_pairs; + std::unordered_map correlations_; }; void CreateTracer(DeviceTracer **t) { *t = new DeviceTracerImpl(); } @@ -370,21 +512,106 @@ DeviceTracer *GetDeviceTracer() { return tracer; } -void SetCurAnnotation(const std::string &anno) { - annotation_stack.push_back(anno); -} +void SetCurAnnotation(Event *event) { annotation_stack.push_back(event); } void ClearCurAnnotation() { annotation_stack.pop_back(); } -std::string CurAnnotation() { - if (annotation_stack.empty()) return ""; +Event *CurAnnotation() { + if (annotation_stack.empty()) return nullptr; return annotation_stack.back(); } +std::string CurAnnotationName() { + if (annotation_stack.empty()) return ""; + return annotation_stack.back()->name(); +} void SetCurBlock(int block_id) { block_id_stack.push_back(block_id); } void ClearCurBlock() { block_id_stack.pop_back(); } int BlockDepth() { return block_id_stack.size(); } + +uint32_t GetCurSystemThreadId() { + std::stringstream ss; + ss << std::this_thread::get_id(); + uint32_t id = static_cast(std::stoull(ss.str())); + return id; +} + +void RecoreCurThreadId(int32_t id) { + auto gid = GetCurSystemThreadId(); + VLOG(1) << "RecoreCurThreadId: " << gid << " -> " << id; + system_thread_id_map[gid] = id; +} + +int32_t GetThreadIdFromSystemThreadId(uint32_t id) { + auto it = system_thread_id_map.find(id); + if (it != system_thread_id_map.end()) return it->second; + // return origin id if no event is recorded in this thread. + return static_cast(id); +} + +#ifdef PADDLE_WITH_CUPTI +namespace { + +void initCuptiCbidStr() { + static bool called = false; + if (called) return; + called = true; +#define REGISTER_RUNTIME_CBID_STR(cbid) \ + runtime_cbid_str[CUPTI_RUNTIME_TRACE_CBID_##cbid] = #cbid + + REGISTER_RUNTIME_CBID_STR(cudaBindTexture_v3020); + REGISTER_RUNTIME_CBID_STR(cudaConfigureCall_v3020); + REGISTER_RUNTIME_CBID_STR(cudaDeviceGetAttribute_v5000); + REGISTER_RUNTIME_CBID_STR(cudaDeviceGetStreamPriorityRange_v5050); + REGISTER_RUNTIME_CBID_STR(cudaDeviceSynchronize_v3020); + REGISTER_RUNTIME_CBID_STR(cudaDriverGetVersion_v3020); + REGISTER_RUNTIME_CBID_STR(cudaEventCreateWithFlags_v3020); + REGISTER_RUNTIME_CBID_STR(cudaEventDestroy_v3020); + REGISTER_RUNTIME_CBID_STR(cudaEventDestroy_v3020); + REGISTER_RUNTIME_CBID_STR(cudaEventQuery_v3020); + REGISTER_RUNTIME_CBID_STR(cudaEventRecord_v3020); + REGISTER_RUNTIME_CBID_STR(cudaFreeHost_v3020); + REGISTER_RUNTIME_CBID_STR(cudaFree_v3020); + REGISTER_RUNTIME_CBID_STR(cudaFuncGetAttributes_v3020); + REGISTER_RUNTIME_CBID_STR(cudaGetDeviceCount_v3020); + REGISTER_RUNTIME_CBID_STR(cudaGetDeviceProperties_v3020); + REGISTER_RUNTIME_CBID_STR(cudaGetDevice_v3020); + REGISTER_RUNTIME_CBID_STR(cudaGetErrorString_v3020); + REGISTER_RUNTIME_CBID_STR(cudaGetLastError_v3020); + REGISTER_RUNTIME_CBID_STR(cudaHostAlloc_v3020); + REGISTER_RUNTIME_CBID_STR(cudaHostGetDevicePointer_v3020); + REGISTER_RUNTIME_CBID_STR(cudaLaunchKernel_v7000); + REGISTER_RUNTIME_CBID_STR(cudaMallocHost_v3020); + REGISTER_RUNTIME_CBID_STR(cudaMalloc_v3020); + REGISTER_RUNTIME_CBID_STR(cudaMemcpyAsync_v3020); + REGISTER_RUNTIME_CBID_STR(cudaMemcpy_v3020); + REGISTER_RUNTIME_CBID_STR(cudaMemsetAsync_v3020); + REGISTER_RUNTIME_CBID_STR(cudaMemset_v3020); + REGISTER_RUNTIME_CBID_STR( + cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags_v7000); + REGISTER_RUNTIME_CBID_STR(cudaPeekAtLastError_v3020); + REGISTER_RUNTIME_CBID_STR(cudaRuntimeGetVersion_v3020); + REGISTER_RUNTIME_CBID_STR(cudaSetDevice_v3020); + REGISTER_RUNTIME_CBID_STR(cudaStreamCreate_v3020); + REGISTER_RUNTIME_CBID_STR(cudaStreamCreateWithFlags_v5000); + REGISTER_RUNTIME_CBID_STR(cudaStreamCreateWithPriority_v5050); + REGISTER_RUNTIME_CBID_STR(cudaStreamDestroy_v5050); + REGISTER_RUNTIME_CBID_STR(cudaStreamSynchronize_v3020); + REGISTER_RUNTIME_CBID_STR(cudaStreamWaitEvent_v3020); + REGISTER_RUNTIME_CBID_STR(cudaUnbindTexture_v3020); + REGISTER_RUNTIME_CBID_STR(cudaSetupArgument_v3020); + REGISTER_RUNTIME_CBID_STR(cudaLaunch_v3020); +#if CUDA_VERSION >= 9000 + REGISTER_RUNTIME_CBID_STR(cudaLaunchCooperativeKernel_v9000); + REGISTER_RUNTIME_CBID_STR(cudaLaunchCooperativeKernelMultiDevice_v9000); +#endif + +#undef REGISTER_RUNTIME_CBID_STR +} +} // namespace +#endif // PADDLE_WITH_CUPTI + } // namespace platform } // namespace paddle diff --git a/paddle/fluid/platform/device_tracer.h b/paddle/fluid/platform/device_tracer.h index bf0786be2d0fafbf4b610d16ef587ac219399203..6ee2c36146215e278c87d22dd7b8fd5cb7e33865 100644 --- a/paddle/fluid/platform/device_tracer.h +++ b/paddle/fluid/platform/device_tracer.h @@ -32,6 +32,8 @@ inline uint64_t PosixInNsec() { return 1000 * (static_cast(tv.tv_sec) * 1000000 + tv.tv_usec); } +class Event; + // DeviceTracer performs the following tasks: // 1. Register cuda callbacks for various events: kernel, memcpy, etc. // 2. Collect cuda statistics: start/end ts, memory, etc. @@ -68,11 +70,13 @@ class DeviceTracer { virtual void Enable() = 0; // Needs to be called once after use. virtual void Disable() = 0; + // Needs to be called once before reuse. + virtual void Reset() = 0; // Add a pair to correlate internal cuda id with high level - // annotation (string). So cuda statistics can be represented by + // annotation event(with string). So cuda statistics can be represented by // human-readable annotations. - virtual void AddAnnotation(uint64_t id, const std::string& anno) = 0; + virtual void AddAnnotation(uint32_t id, Event* event) = 0; virtual void AddMemRecords(const std::string& name, uint64_t start_ns, uint64_t end_ns, int64_t device_id, @@ -92,6 +96,9 @@ class DeviceTracer { // Generate a proto after done (Disabled). virtual proto::Profile GenProfile(const std::string& profile_path) = 0; + // generate kernel elapsed time into Event + virtual void GenEventKernelCudaElapsedTime() = 0; + virtual bool IsEnabled() = 0; }; @@ -99,14 +106,19 @@ class DeviceTracer { DeviceTracer* GetDeviceTracer(); // Set a name for the cuda kernel operation being launched by the thread. -void SetCurAnnotation(const std::string& anno); +void SetCurAnnotation(Event* event); // Clear the name after the operation is done. void ClearCurAnnotation(); // Current name of the operation being run in the thread. -std::string CurAnnotation(); +std::string CurAnnotationName(); +Event* CurAnnotation(); void SetCurBlock(int block_id); void ClearCurBlock(); int BlockDepth(); + +// Set current thread id, so we can map the system thread id to thread id. +void RecoreCurThreadId(int32_t id); +int32_t GetThreadIdFromSystemThreadId(uint32_t id); } // namespace platform } // namespace paddle diff --git a/paddle/fluid/platform/dynload/mklml.h b/paddle/fluid/platform/dynload/mklml.h index a260cda49138580b209e647af459e9392d9f18f1..a5b846f500f3677188b170dda76c65047d628064 100644 --- a/paddle/fluid/platform/dynload/mklml.h +++ b/paddle/fluid/platform/dynload/mklml.h @@ -86,6 +86,8 @@ extern void* mklml_dso_handle; __macro(vdPowx); \ __macro(vsInv); \ __macro(vdInv); \ + __macro(vmsErf); \ + __macro(vmdErf); \ __macro(MKL_Set_Num_Threads) MKLML_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_MKLML_WRAP); diff --git a/paddle/fluid/platform/enforce.h b/paddle/fluid/platform/enforce.h index d32f9c8667d34246e55b039165bec05b7bec0376..54ad18a8e4abbddc0414ed32a719d46002e99188 100644 --- a/paddle/fluid/platform/enforce.h +++ b/paddle/fluid/platform/enforce.h @@ -31,6 +31,8 @@ limitations under the License. */ #include #include #include +#include +#include #include "glog/logging.h" #include "paddle/fluid/platform/macros.h" @@ -280,16 +282,62 @@ inline void throw_on_error(ncclResult_t stat, const std::string& msg) { } \ } while (0) -#define __PADDLE_BINARY_COMPARE(__VAL0, __VAL1, __CMP, __INV_CMP, ...) \ +namespace details { +template +inline constexpr bool IsArithmetic() { + return std::is_arithmetic::value; +} + +template +struct TypeConverterImpl { + using Type1 = typename std::common_type::type; + using Type2 = Type1; +}; + +template +struct TypeConverterImpl { + using Type1 = T1; + using Type2 = T2; +}; + +template +struct TypeConverter { + private: + static constexpr bool kIsArithmetic = + IsArithmetic() && IsArithmetic(); + + public: + using Type1 = typename TypeConverterImpl::Type1; + using Type2 = typename TypeConverterImpl::Type2; +}; + +template +using CommonType1 = typename std::add_lvalue_reference< + typename std::add_const::Type1>::type>::type; + +template +using CommonType2 = typename std::add_lvalue_reference< + typename std::add_const::Type2>::type>::type; +} // namespace details + +#define __PADDLE_BINARY_COMPARE(__VAL1, __VAL2, __CMP, __INV_CMP, ...) \ do { \ - auto __cond1__ = (__VAL0); \ - auto __cond2__ = (__VAL1); \ - if (UNLIKELY(!((__cond1__)__CMP(__cond2__)))) { \ + auto __val1 = (__VAL1); \ + auto __val2 = (__VAL2); \ + using __TYPE1__ = decltype(__val1); \ + using __TYPE2__ = decltype(__val2); \ + using __COMMON_TYPE1__ = \ + ::paddle::platform::details::CommonType1<__TYPE1__, __TYPE2__>; \ + using __COMMON_TYPE2__ = \ + ::paddle::platform::details::CommonType2<__TYPE1__, __TYPE2__>; \ + bool __is_not_error = (static_cast<__COMMON_TYPE1__>(__val1))__CMP( \ + static_cast<__COMMON_TYPE2__>(__val2)); \ + if (UNLIKELY(!__is_not_error)) { \ PADDLE_THROW("Enforce failed. Expected %s " #__CMP \ " %s, but received %s:%s " #__INV_CMP " %s:%s.\n%s", \ - #__VAL0, #__VAL1, #__VAL0, \ - ::paddle::string::to_string(__cond1__), #__VAL1, \ - ::paddle::string::to_string(__cond2__), \ + #__VAL1, #__VAL2, #__VAL1, \ + ::paddle::string::to_string(__val1), #__VAL2, \ + ::paddle::string::to_string(__val2), \ ::paddle::string::Sprintf(__VA_ARGS__)); \ } \ } while (0) diff --git a/paddle/fluid/platform/enforce_test.cc b/paddle/fluid/platform/enforce_test.cc index 1091badae54a809c4a9da6d0398bcbb538420af0..adcc95367f11dfa2722226e5a0386bedfa6e746e 100644 --- a/paddle/fluid/platform/enforce_test.cc +++ b/paddle/fluid/platform/enforce_test.cc @@ -118,59 +118,58 @@ TEST(ENFORCE_GT, OK) { PADDLE_ENFORCE_GT(2, 1); } TEST(ENFORCE_GT, FAIL) { bool caught_exception = false; try { - PADDLE_ENFORCE_GT(1, 2UL); + PADDLE_ENFORCE_GT(1, 2); } catch (paddle::platform::EnforceNotMet error) { caught_exception = true; - EXPECT_TRUE(HasPrefix( - StringPiece(error.what()), - "Enforce failed. Expected 1 > 2UL, but received 1:1 <= 2UL:2.")); + EXPECT_TRUE( + HasPrefix(StringPiece(error.what()), + "Enforce failed. Expected 1 > 2, but received 1:1 <= 2:2.")); } EXPECT_TRUE(caught_exception); } TEST(ENFORCE_GE, OK) { - PADDLE_ENFORCE_GE(2, 2UL); - PADDLE_ENFORCE_GE(3, 2UL); + PADDLE_ENFORCE_GE(2, 2); PADDLE_ENFORCE_GE(3, 2); - PADDLE_ENFORCE_GE(3.21, 2UL); + PADDLE_ENFORCE_GE(3.21, 2.0); } TEST(ENFORCE_GE, FAIL) { bool caught_exception = false; try { - PADDLE_ENFORCE_GE(1, 2UL); + PADDLE_ENFORCE_GE(1, 2); } catch (paddle::platform::EnforceNotMet error) { caught_exception = true; - EXPECT_TRUE(HasPrefix( - StringPiece(error.what()), - "Enforce failed. Expected 1 >= 2UL, but received 1:1 < 2UL:2.")); + EXPECT_TRUE( + HasPrefix(StringPiece(error.what()), + "Enforce failed. Expected 1 >= 2, but received 1:1 < 2:2.")); } EXPECT_TRUE(caught_exception); } TEST(ENFORCE_LE, OK) { PADDLE_ENFORCE_LE(1, 1); - PADDLE_ENFORCE_LE(1, 1UL); - PADDLE_ENFORCE_LE(2, 3UL); - PADDLE_ENFORCE_LE(2UL, 3); - PADDLE_ENFORCE_LE(2UL, 3.2); + PADDLE_ENFORCE_LE(1UL, 1UL); + PADDLE_ENFORCE_LE(2, 3); + PADDLE_ENFORCE_LE(2UL, 3UL); + PADDLE_ENFORCE_LE(2.0, 3.2); } TEST(ENFORCE_LE, FAIL) { bool caught_exception = false; try { - PADDLE_ENFORCE_GT(1, 2UL); + PADDLE_ENFORCE_GT(1, 2); } catch (paddle::platform::EnforceNotMet error) { caught_exception = true; - EXPECT_TRUE(HasPrefix( - StringPiece(error.what()), - "Enforce failed. Expected 1 > 2UL, but received 1:1 <= 2UL:2.")); + EXPECT_TRUE( + HasPrefix(StringPiece(error.what()), + "Enforce failed. Expected 1 > 2, but received 1:1 <= 2:2.")); } EXPECT_TRUE(caught_exception); } TEST(ENFORCE_LT, OK) { PADDLE_ENFORCE_LT(3, 10); - PADDLE_ENFORCE_LT(2, 3UL); - PADDLE_ENFORCE_LT(2UL, 3); + PADDLE_ENFORCE_LT(2UL, 3UL); + PADDLE_ENFORCE_LT(2, 3); } TEST(ENFORCE_LT, FAIL) { bool caught_exception = false; @@ -235,7 +234,13 @@ TEST(ENFORCE_USER_DEFINED_CLASS, EQ) { TEST(ENFORCE_USER_DEFINED_CLASS, NE) { Dims a{{1, 2, 3, 4}}, b{{5, 6, 7, 8}}; - ASSERT_THROW(PADDLE_ENFORCE_EQ(a, b), paddle::platform::EnforceNotMet); + bool caught_exception = false; + try { + PADDLE_ENFORCE_EQ(a, b); + } catch (paddle::platform::EnforceNotMet&) { + caught_exception = true; + } + EXPECT_TRUE(caught_exception); } TEST(EOF_EXCEPTION, THROW_EOF) { diff --git a/paddle/fluid/platform/init.cc b/paddle/fluid/platform/init.cc index ac86b38a61c9d8e3e946d9fb3f46d8feba7c034d..4dcf7e79043af008cb2067d90d12d629c5c2d0d9 100644 --- a/paddle/fluid/platform/init.cc +++ b/paddle/fluid/platform/init.cc @@ -22,6 +22,7 @@ limitations under the License. */ #include "paddle/fluid/string/split.h" #ifdef PADDLE_WITH_CUDA #include "paddle/fluid/platform/cuda_device_guard.h" +#include "paddle/fluid/platform/dynload/cupti.h" #endif #include "paddle/fluid/platform/device_context.h" #include "paddle/fluid/platform/init.h" @@ -30,6 +31,9 @@ limitations under the License. */ DEFINE_int32(paddle_num_threads, 1, "Number of threads for each paddle instance."); +DEFINE_int32(multiple_of_cupti_buffer_size, 1, + "Multiple of the CUPTI device buffer size. If the timestamps have " + "been dropped when you are profiling, try increasing this value."); namespace paddle { namespace framework { @@ -78,7 +82,32 @@ void InitP2P(std::vector devices) { #endif } +void InitCupti() { +#ifdef PADDLE_WITH_CUPTI + if (FLAGS_multiple_of_cupti_buffer_size == 1) return; + size_t attrValue = 0, attrValueSize = sizeof(size_t); +#define MULTIPLY_ATTR_VALUE(attr) \ + { \ + PADDLE_ENFORCE(!platform::dynload::cuptiActivityGetAttribute( \ + attr, &attrValueSize, &attrValue)); \ + attrValue *= FLAGS_multiple_of_cupti_buffer_size; \ + LOG(WARNING) << "Set " #attr " " << attrValue << " byte"; \ + PADDLE_ENFORCE(!platform::dynload::cuptiActivitySetAttribute( \ + attr, &attrValueSize, &attrValue)); \ + } + MULTIPLY_ATTR_VALUE(CUPTI_ACTIVITY_ATTR_DEVICE_BUFFER_SIZE); + MULTIPLY_ATTR_VALUE(CUPTI_ACTIVITY_ATTR_DEVICE_BUFFER_SIZE_CDP); +#if CUDA_VERSION >= 9000 + MULTIPLY_ATTR_VALUE(CUPTI_ACTIVITY_ATTR_PROFILING_SEMAPHORE_POOL_SIZE); +#endif +#undef MULTIPLY_ATTR_VALUE +#endif +} + void InitDevices(bool init_p2p) { + // CUPTI attribute should be set before any CUDA context is created (see CUPTI + // documentation about CUpti_ActivityAttribute). + InitCupti(); /*Init all available devices by default */ std::vector devices; #ifdef PADDLE_WITH_CUDA diff --git a/paddle/fluid/platform/ngraph_helper.h b/paddle/fluid/platform/ngraph_helper.h index 5ee985ea719f8cb28bf8be23823eb6c96f4af1a3..e74f57a79a66ea8fe8c9b972a9a2ec9d722731eb 100644 --- a/paddle/fluid/platform/ngraph_helper.h +++ b/paddle/fluid/platform/ngraph_helper.h @@ -43,6 +43,13 @@ std::shared_ptr Nchw2Nhwc(std::shared_ptr in) { return std::make_shared(in, axis_vec, in_shape); } +ngraph::Shape FlattenTo1d(ngraph::Shape sh, int num) { + auto x1 = std::accumulate(std::begin(sh), std::end(sh) + num, 1, + std::multiplies()); + size_t x1_l = (size_t)x1; + return ngraph::Shape{x1_l}; +} + ngraph::Shape FlattenTo2d(ngraph::Shape sh, int num) { auto x1 = std::accumulate(std::begin(sh), std::begin(sh) + num, 1, std::multiplies()); diff --git a/paddle/fluid/platform/profiler.cc b/paddle/fluid/platform/profiler.cc index 85977366e61c676fc5d2d3c5d22dd2f606543684..9a285a6b533dcb48013e3b3e4d34dc27186173ac 100644 --- a/paddle/fluid/platform/profiler.cc +++ b/paddle/fluid/platform/profiler.cc @@ -12,6 +12,8 @@ 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/platform/profiler.h" + #include #include #include @@ -27,7 +29,6 @@ limitations under the License. */ #include "paddle/fluid/framework/block_desc.h" #include "paddle/fluid/platform/device_tracer.h" #include "paddle/fluid/platform/port.h" -#include "paddle/fluid/platform/profiler.h" #include "paddle/fluid/string/printf.h" DEFINE_bool(enable_rpc_profiler, false, "Enable rpc profiler or not."); @@ -66,12 +67,13 @@ struct EventList { ((kEventSize + kEventAlign - 1) / kEventAlign * kEventAlign); template - void Record(Args&&... args) { + Event* Record(Args&&... args) { if (event_blocks.empty() || event_blocks.front().size() == kNumBlock) { event_blocks.emplace_front(); event_blocks.front().reserve(kNumBlock); } event_blocks.front().emplace_back(std::forward(args)...); + return &event_blocks.front().back(); } std::vector Reduce() { @@ -98,21 +100,8 @@ inline uint64_t GetTimeInNsec() { .count(); } -Event::Event(EventType type, std::string name, uint32_t thread_id, - const DeviceContext* dev_ctx) - : type_(type), name_(name), thread_id_(thread_id), has_cuda_(false) { -#ifdef PADDLE_WITH_CUDA - has_cuda_ = dev_ctx ? platform::is_gpu_place(dev_ctx->GetPlace()) : false; - if (has_cuda_) { - auto* cuda_dev_ctx = static_cast(dev_ctx); - PADDLE_ENFORCE(cudaSetDevice( - boost::get(cuda_dev_ctx->GetPlace()).device)); - PADDLE_ENFORCE(cudaGetDevice(&device_)); - PADDLE_ENFORCE(cudaEventCreate(&event_)); - auto stream = cuda_dev_ctx->stream(); - PADDLE_ENFORCE(cudaEventRecord(event_, stream)); - } -#endif +Event::Event(EventType type, std::string name, uint32_t thread_id) + : type_(type), name_(name), thread_id_(thread_id) { cpu_ns_ = GetTimeInNsec(); } @@ -123,89 +112,70 @@ double Event::CpuElapsedMs(const Event& e) const { } double Event::CudaElapsedMs(const Event& e) const { -#ifdef PADDLE_WITH_CUDA - if (!has_cuda_) return 0.0; - PADDLE_ENFORCE(e.has_cuda() && has_cuda()); - PADDLE_ENFORCE(e.device() == device()); - PADDLE_ENFORCE(cudaEventSynchronize(event_)); - PADDLE_ENFORCE(cudaEventSynchronize(e.event())); - float ms; - PADDLE_ENFORCE(cudaEventElapsedTime(&ms, event_, e.event())); - return ms; +#ifdef PADDLE_WITH_CUPTI + return gpu_ns_ / 1000000.0; #else - PADDLE_THROW("CUDA is not enabled"); + LOG_FIRST_N(WARNING, 1) << "CUDA CUPTI is not enabled"; + return 0; #endif } -#ifdef PADDLE_WITH_CUDA -static void ForEachDevice(std::function func) { - auto original_device = GetCurrentDeviceId(); - int count = GetCUDADeviceCount(); - for (int i = 0; i < count; i++) { - SetDeviceId(i); - func(i); - } - SetDeviceId(original_device); -} -#endif - inline EventList& GetEventList() { if (!g_event_list) { std::lock_guard guard(g_all_event_lists_mutex); g_event_list = std::make_shared(); g_thread_id = g_next_thread_id++; g_all_event_lists.emplace_front(g_event_list); + RecoreCurThreadId(g_thread_id); } return *g_event_list; } -void Mark(const std::string& name, const DeviceContext* dev_ctx) { - GetEventList().Record(EventType::kMark, name, g_thread_id, dev_ctx); +void Mark(const std::string& name) { + GetEventList().Record(EventType::kMark, name, g_thread_id); } -void PushEvent(const std::string& name, const DeviceContext* dev_ctx) { - GetEventList().Record(EventType::kPushRange, name, g_thread_id, dev_ctx); +Event* PushEvent(const std::string& name) { + return GetEventList().Record(EventType::kPushRange, name, g_thread_id); } -void PopEvent(const std::string& name, const DeviceContext* dev_ctx) { - GetEventList().Record(EventType::kPopRange, name, g_thread_id, dev_ctx); +void PopEvent(const std::string& name) { + GetEventList().Record(EventType::kPopRange, name, g_thread_id); } -RecordEvent::RecordEvent(const std::string& name, const DeviceContext* dev_ctx) +RecordEvent::RecordEvent(const std::string& name) : is_enabled_(false), start_ns_(PosixInNsec()) { if (g_state == ProfilerState::kDisabled) return; - std::lock_guard l(profiler_mu); + // lock is not needed, the code below is thread-safe is_enabled_ = true; - dev_ctx_ = dev_ctx; name_ = name; - PushEvent(name_, dev_ctx_); + Event* e = PushEvent(name_); // Maybe need the same push/pop behavior. - SetCurAnnotation(name_); + SetCurAnnotation(e); } RecordEvent::~RecordEvent() { if (g_state == ProfilerState::kDisabled || !is_enabled_) return; - std::lock_guard l(profiler_mu); + // lock is not needed, the code below is thread-safe DeviceTracer* tracer = GetDeviceTracer(); if (tracer) { - tracer->AddCPURecords(CurAnnotation(), start_ns_, PosixInNsec(), + tracer->AddCPURecords(CurAnnotationName(), start_ns_, PosixInNsec(), BlockDepth(), g_thread_id); } ClearCurAnnotation(); - PopEvent(name_, dev_ctx_); + PopEvent(name_); } -RecordRPCEvent::RecordRPCEvent(const std::string& name, - const DeviceContext* dev_ctx) { +RecordRPCEvent::RecordRPCEvent(const std::string& name) { if (FLAGS_enable_rpc_profiler) { - event_.reset(new platform::RecordEvent(name, dev_ctx)); + event_.reset(new platform::RecordEvent(name)); } } RecordBlock::RecordBlock(int block_id) : is_enabled_(false), start_ns_(PosixInNsec()) { - std::lock_guard l(profiler_mu); + // lock is not needed, the code below is thread-safe if (g_state == ProfilerState::kDisabled) return; is_enabled_ = true; SetCurBlock(block_id); @@ -213,7 +183,7 @@ RecordBlock::RecordBlock(int block_id) } RecordBlock::~RecordBlock() { - std::lock_guard l(profiler_mu); + // lock is not needed, the code below is thread-safe if (g_state == ProfilerState::kDisabled || !is_enabled_) return; DeviceTracer* tracer = GetDeviceTracer(); if (tracer) { @@ -225,11 +195,21 @@ RecordBlock::~RecordBlock() { ClearCurBlock(); } +void SynchronizeAllDevice() { +#ifdef PADDLE_WITH_CUDA + int count = GetCUDADeviceCount(); + for (int i = 0; i < count; i++) { + SetDeviceId(i); + PADDLE_ENFORCE(cudaDeviceSynchronize()); + } +#endif +} + void EnableProfiler(ProfilerState state) { PADDLE_ENFORCE(state != ProfilerState::kDisabled, "Can't enable profiling, since the input state is ", "ProfilerState::kDisabled"); - + SynchronizeAllDevice(); std::lock_guard l(profiler_mu); if (state == g_state) { return; @@ -238,23 +218,20 @@ void EnableProfiler(ProfilerState state) { should_send_profile_state = true; GetDeviceTracer()->Enable(); #ifdef PADDLE_WITH_CUDA - if (g_state == ProfilerState::kCUDA) { + if (g_state == ProfilerState::kCUDA || g_state == ProfilerState::kAll || + g_state == ProfilerState::kCPU) { // Generate some dummy events first to reduce the startup overhead. - for (int i = 0; i < 5; i++) { - ForEachDevice([](int d) { - DeviceContext* dev_ctx = new CUDADeviceContext(CUDAPlace(d)); - Mark("_cuda_startup_", dev_ctx); - dev_ctx->Wait(); - delete dev_ctx; - }); - } + DummyKernelAndEvent(); + GetDeviceTracer()->Reset(); } #endif // Mark the profiling start. - Mark("_start_profiler_", nullptr); + Mark("_start_profiler_"); } void ResetProfiler() { + SynchronizeAllDevice(); + GetDeviceTracer()->Reset(); std::lock_guard guard(g_all_event_lists_mutex); for (auto it = g_all_event_lists.begin(); it != g_all_event_lists.end(); ++it) { @@ -277,9 +254,11 @@ struct EventItem { std::string name; int calls; double total_time; - double min_time; double max_time; double ave_time; + double min_time; + double cpu_time; + double gpu_time; float ratio; }; @@ -313,8 +292,12 @@ void PrintProfiler(const std::vector>& events_table, // Output events table std::cout.setf(std::ios::left); std::cout << std::setw(name_width) << "Event" << std::setw(data_width) - << "Calls" << std::setw(data_width) << "Total" - << std::setw(data_width) << "Min." << std::setw(data_width) + << "Calls" << std::setw(data_width) << "Total"; + if (g_state == ProfilerState::kAll) { + std::cout << std::setw(data_width * 2) << "CPU Time (Ratio)" + << std::setw(data_width * 2) << "GPU Time (Ratio)"; + } + std::cout << std::setw(data_width) << "Min." << std::setw(data_width) << "Max." << std::setw(data_width) << "Ave." << std::setw(data_width) << "Ratio." << std::endl; for (size_t i = 0; i < events_table.size(); ++i) { @@ -322,8 +305,18 @@ void PrintProfiler(const std::vector>& events_table, const EventItem& event_item = events_table[i][j]; std::cout << std::setw(name_width) << event_item.name << std::setw(data_width) << event_item.calls - << std::setw(data_width) << event_item.total_time - << std::setw(data_width) << event_item.min_time + << std::setw(data_width) << event_item.total_time; + if (g_state == ProfilerState::kAll) { + std::cout << std::setw(data_width * 2) + << string::Sprintf( + "%f (%f)", event_item.cpu_time, + (event_item.cpu_time / event_item.total_time)) + << std::setw(data_width * 2) + << string::Sprintf( + "%f (%f)", event_item.gpu_time, + (event_item.gpu_time / event_item.total_time)); + } + std::cout << std::setw(data_width) << event_item.min_time << std::setw(data_width) << event_item.max_time << std::setw(data_width) << event_item.ave_time << std::setw(data_width) << event_item.ratio << std::endl; @@ -372,6 +365,18 @@ void ParseEvents(const std::vector>& events, return a.ave_time > b.ave_time; }; break; + case EventSortingKey::kGPUTime: + sorted_domain = "average time"; + sorted_func = [](const EventItem& a, const EventItem& b) { + return a.gpu_time > b.gpu_time; + }; + break; + case EventSortingKey::kCPUTime: + sorted_domain = "average time"; + sorted_func = [](const EventItem& a, const EventItem& b) { + return a.cpu_time > b.cpu_time; + }; + break; default: sorted_domain = "event first end time"; } @@ -410,10 +415,17 @@ void ParseEvents(const std::vector>& events, } if (rit != pushed_events.rend()) { - double event_time = (g_state == ProfilerState::kCUDA || - g_state == ProfilerState::kAll) - ? rit->CudaElapsedMs((*analyze_events)[i][j]) - : rit->CpuElapsedMs((*analyze_events)[i][j]); + double event_time = 0; + double gpu_time = rit->CudaElapsedMs((*analyze_events)[i][j]); + double cpu_time = rit->CpuElapsedMs((*analyze_events)[i][j]); + if (g_state == ProfilerState::kCUDA) { + event_time = gpu_time; + } else if (g_state == ProfilerState::kCPU) { + event_time = cpu_time; + } else { + event_time = gpu_time + cpu_time; + } + total += event_time; std::string event_name; @@ -430,7 +442,7 @@ void ParseEvents(const std::vector>& events, event_idx[event_name] = event_items.size(); EventItem event_item = {event_name, 1, event_time, event_time, event_time, event_time, - 0.}; + gpu_time, cpu_time, 0.}; event_items.push_back(event_item); } else { int index = event_idx[event_name]; @@ -443,6 +455,8 @@ void ParseEvents(const std::vector>& events, // max time event_items[index].max_time = std::max(event_time, event_items[index].max_time); + event_items[index].gpu_time += gpu_time; + event_items[index].cpu_time += cpu_time; } // remove the push marker from the list @@ -481,20 +495,23 @@ void ParseEvents(const std::vector>& events, void DisableProfiler(EventSortingKey sorted_key, const std::string& profile_path) { + SynchronizeAllDevice(); std::lock_guard l(profiler_mu); if (g_state == ProfilerState::kDisabled) return; // Mark the profiling stop. - Mark("_stop_profiler_", nullptr); + Mark("_stop_profiler_"); - std::vector> all_events = GetAllEvents(); - ParseEvents(all_events, true, sorted_key); - ParseEvents(all_events, false, sorted_key); - ResetProfiler(); DeviceTracer* tracer = GetDeviceTracer(); if (tracer->IsEnabled()) { tracer->Disable(); tracer->GenProfile(profile_path); + tracer->GenEventKernelCudaElapsedTime(); } + + std::vector> all_events = GetAllEvents(); + ParseEvents(all_events, true, sorted_key); + ParseEvents(all_events, false, sorted_key); + ResetProfiler(); g_state = ProfilerState::kDisabled; should_send_profile_state = true; } diff --git a/paddle/fluid/platform/profiler.cu b/paddle/fluid/platform/profiler.cu new file mode 100644 index 0000000000000000000000000000000000000000..e115c554caf383bad29aa5d065ec0126427f8e78 --- /dev/null +++ b/paddle/fluid/platform/profiler.cu @@ -0,0 +1,50 @@ +/* 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/platform/profiler.h" + +#include + +namespace paddle { +namespace platform { + +__global__ void DummyKernel(int *a) { a[0] = 0; } + +static void ForEachDevice(std::function func) { + auto original_device = GetCurrentDeviceId(); + int count = GetCUDADeviceCount(); + for (int i = 0; i < count; i++) { + SetDeviceId(i); + func(i); + } + SetDeviceId(original_device); +} + +void DummyKernelAndEvent() { + for (int i = 0; i < 5; i++) { + ForEachDevice([](int d) { + CUDADeviceContext *dev_ctx = new CUDADeviceContext(CUDAPlace(d)); + Mark("_cuda_startup_"); + int *ptr; + PADDLE_ENFORCE(cudaMalloc(&ptr, sizeof(int))); + DummyKernel<<<1, 1, 0, dev_ctx->stream()>>>(ptr); + dev_ctx->Wait(); + PADDLE_ENFORCE(cudaFree(ptr)); + delete dev_ctx; + }); + } +} + +} // namespace platform +} // namespace paddle diff --git a/paddle/fluid/platform/profiler.h b/paddle/fluid/platform/profiler.h index f5d3490634f3199a23986ec3ae13d9fe3577ac35..4057e5ea0564099667517eb2c54feb2ff13303d1 100644 --- a/paddle/fluid/platform/profiler.h +++ b/paddle/fluid/platform/profiler.h @@ -28,17 +28,17 @@ class Event { public: // The DeviceContext is used to get the cuda stream. // If CPU profiling mode, can pass nullptr. - Event(EventType type, std::string name, uint32_t thread_id, - const DeviceContext* dev_ctx); + Event(EventType type, std::string name, uint32_t thread_id); const EventType& type() const; std::string name() const { return name_; } uint32_t thread_id() const { return thread_id_; } - bool has_cuda() const { return has_cuda_; } #ifdef PADDLE_WITH_CUDA +#ifndef PADDLE_WITH_CUPTI cudaEvent_t event() const { return event_; } int device() const { return device_; } +#endif #endif double CpuElapsedMs(const Event& e) const; @@ -49,11 +49,21 @@ class Event { std::string name_; uint32_t thread_id_; int64_t cpu_ns_; - bool has_cuda_; #ifdef PADDLE_WITH_CUDA +#ifdef PADDLE_WITH_CUPTI + int64_t gpu_ns_ = 0; + + public: + void AddCudaElapsedTime(int64_t start_ns, int64_t end_ns) { + gpu_ns_ += end_ns - start_ns; + } + + private: +#else cudaEvent_t event_ = nullptr; int device_ = -1; #endif +#endif }; enum ProfilerState { @@ -63,22 +73,19 @@ enum ProfilerState { kAll, // Profile both CPU and GPU. (Currently experimental). }; -void Mark(const std::string& name, const DeviceContext* dev_ctx); +void Mark(const std::string& name); -void PushEvent(const std::string& name, const DeviceContext* dev_ctx); +Event* PushEvent(const std::string& name); -void PopEvent(const std::string& name, const DeviceContext* dev_ctx); +void PopEvent(const std::string& name); struct RecordEvent { - // dev_ctx can be set to nullptr if device is cpu. - RecordEvent(const std::string& name, const DeviceContext* dev_ctx); + explicit RecordEvent(const std::string& name); ~RecordEvent(); bool is_enabled_; uint64_t start_ns_; - // The device context is used by Event to get the current cuda stream. - const DeviceContext* dev_ctx_; // Event name std::string name_; // Need to distinguish name by op type, block_id, program_id and perhaps @@ -88,8 +95,7 @@ struct RecordEvent { class RecordRPCEvent { public: - // dev_ctx can be set to nullptr if device is cpu. - RecordRPCEvent(const std::string& name, const DeviceContext* dev_ctx); + explicit RecordRPCEvent(const std::string& name); ~RecordRPCEvent() {} private: @@ -111,7 +117,16 @@ struct RecordBlock { std::vector> GetAllEvents(); // Candidate keys to sort the profiling report -enum EventSortingKey { kDefault, kCalls, kTotal, kMin, kMax, kAve }; +enum EventSortingKey { + kDefault, + kCalls, + kTotal, + kMin, + kMax, + kAve, + kCPUTime, + kGPUTime +}; // Enable the profiling function. void EnableProfiler(ProfilerState state); @@ -132,5 +147,9 @@ bool ShouldSendProfileState(); void SetProfileListener(); int64_t ListenerId(); +#ifdef PADDLE_WITH_CUDA +void DummyKernelAndEvent(); +#endif + } // namespace platform } // namespace paddle diff --git a/paddle/fluid/platform/profiler.proto b/paddle/fluid/platform/profiler.proto index 7b42aa785ec6ad5731e3adee1e9f189127a826a1..e761d7b266e92fd5d47b5b6073ffc8bea1dc877d 100644 --- a/paddle/fluid/platform/profiler.proto +++ b/paddle/fluid/platform/profiler.proto @@ -31,6 +31,7 @@ message Event { optional int64 sub_device_id = 6; optional MemCopy memcopy = 7; + optional string detail_info = 9; } message Profile { diff --git a/paddle/fluid/platform/profiler_test.cc b/paddle/fluid/platform/profiler_test.cc index 61f467814ba4a24c8b73f1bc614cda0ab8c4debd..528fe03c67a282248c551525e899279b561ce5d2 100644 --- a/paddle/fluid/platform/profiler_test.cc +++ b/paddle/fluid/platform/profiler_test.cc @@ -23,76 +23,49 @@ TEST(Event, CpuElapsedTime) { using paddle::platform::Event; using paddle::platform::EventType; - Event start_event(EventType::kPushRange, "test", 0, nullptr); - EXPECT_TRUE(start_event.has_cuda() == false); + Event start_event(EventType::kPushRange, "test", 0); int counter = 0; while (counter != 1000) { counter++; } - Event stop_event(EventType::kPopRange, "test", 0, nullptr); + Event stop_event(EventType::kPopRange, "test", 0); EXPECT_GT(start_event.CpuElapsedMs(stop_event), 0); } -#ifdef PADDLE_WITH_CUDA -TEST(Event, CudaElapsedTime) { - using paddle::platform::DeviceContext; - using paddle::platform::CUDADeviceContext; - using paddle::platform::CUDAPlace; - using paddle::platform::Event; - using paddle::platform::EventType; - - DeviceContext* dev_ctx = new CUDADeviceContext(CUDAPlace(0)); - Event start_event(EventType::kPushRange, "test", 0, dev_ctx); - EXPECT_TRUE(start_event.has_cuda() == true); - int counter = 0; - while (counter != 1000) { - counter++; - } - Event stop_event(EventType::kPopRange, "test", 0, dev_ctx); - EXPECT_GT(start_event.CudaElapsedMs(stop_event), 0); -} -#endif - TEST(RecordEvent, RecordEvent) { using paddle::platform::DeviceContext; using paddle::platform::Event; using paddle::platform::EventType; using paddle::platform::RecordEvent; + using paddle::platform::PushEvent; + using paddle::platform::PopEvent; using paddle::platform::ProfilerState; using paddle::platform::EventSortingKey; ProfilerState state = ProfilerState::kCPU; - DeviceContext* dev_ctx = nullptr; -#ifdef PADDLE_WITH_CUDA - using paddle::platform::CUDADeviceContext; - using paddle::platform::CUDAPlace; - state = ProfilerState::kCUDA; - dev_ctx = - new paddle::platform::CUDADeviceContext(paddle::platform::CUDAPlace(0)); -#endif EnableProfiler(state); /* Usage 1: - * PushEvent(evt_name, dev_ctx); + * PushEvent(evt_name); * ... * code to be analyzed * ... - * PopEvent(evt_name, dev_ctx); + * PopEvent(evt_name); */ LOG(INFO) << "Usage 1: PushEvent & PopEvent"; for (int loop = 0; loop < 3; ++loop) { for (int i = 1; i < 5; ++i) { std::string name = "op_" + std::to_string(i); - PushEvent(name, dev_ctx); + PushEvent(name); int counter = 1; while (counter != i * 1000) counter++; - PopEvent(name, dev_ctx); + PopEvent(name); } } /* Usage 2: * { - * RecordEvent record_event(name, dev_ctx); + * RecordEvent record_event(name); * ... * code to be analyzed * ... @@ -101,7 +74,7 @@ TEST(RecordEvent, RecordEvent) { LOG(INFO) << "Usage 2: RecordEvent"; for (int i = 1; i < 5; ++i) { std::string name = "evs_op_" + std::to_string(i); - RecordEvent record_event(name, dev_ctx); + RecordEvent record_event(name); int counter = 1; while (counter != i * 1000) counter++; } @@ -123,20 +96,20 @@ TEST(RecordEvent, RecordEvent) { LOG(INFO) << "Usage 3: nested RecordEvent"; for (int i = 1; i < 5; ++i) { std::string name = "ano_evs_op_" + std::to_string(i); - RecordEvent record_event(name, dev_ctx); + RecordEvent record_event(name); int counter = 1; while (counter != i * 100) counter++; { std::string nested_name = "nested_ano_evs_op_" + std::to_string(i); - RecordEvent nested_record_event(nested_name, dev_ctx); + RecordEvent nested_record_event(nested_name); int nested_counter = 1; while (nested_counter != i * 100) nested_counter++; } } // Bad Usage: - PushEvent("event_without_pop", dev_ctx); - PopEvent("event_without_push", dev_ctx); + PushEvent("event_without_pop"); + PopEvent("event_without_push"); std::vector> events = paddle::platform::GetAllEvents(); int cuda_startup_count = 0; diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc index c50c38160e0a2daca704a52eceaa2a9a67a9ba9b..d8e57a1ac6ccfc768a7f0604fcd1f32744a126df 100644 --- a/paddle/fluid/pybind/pybind.cc +++ b/paddle/fluid/pybind/pybind.cc @@ -106,6 +106,11 @@ bool IsCompiledWithDIST() { #endif } +template +static inline bool IsSamePlace(const PlaceType1 &p1, const PlaceType2 &p2) { + return paddle::platform::Place(p1) == paddle::platform::Place(p2); +} + PYBIND11_MODULE(core, m) { // Not used, just make sure cpu_info.cc is linked. paddle::platform::CpuTotalPhysicalMemory(); @@ -732,23 +737,45 @@ All parameter, weight, gradient are variables in Paddle. PADDLE_THROW("Cannot use CUDAPlace in CPU only version"); #endif }) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) + .def("_equals", + &IsSamePlace) .def("__str__", string::to_string); py::class_(m, "CPUPlace") .def(py::init<>()) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) + .def("_equals", + &IsSamePlace) .def("__str__", string::to_string); py::class_(m, "CUDAPinnedPlace") .def("__init__", - [](platform::CUDAPinnedPlace &) { + [](platform::CUDAPinnedPlace &self) { #ifndef PADDLE_WITH_CUDA PADDLE_THROW("Cannot use CUDAPinnedPlace in CPU only version"); #endif + new (&self) platform::CUDAPinnedPlace(); }) + .def("_equals", &IsSamePlace) + .def("_equals", + &IsSamePlace) + .def("_equals", + &IsSamePlace) + .def("_equals", + &IsSamePlace) .def("__str__", string::to_string); py::class_(m, "Place") .def(py::init<>()) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) + .def("_equals", &IsSamePlace) .def("is_gpu_place", [](platform::Place &self) { return platform::is_gpu_place(self); }) .def("gpu_device_id", diff --git a/paddle/fluid/train/demo/README.md b/paddle/fluid/train/demo/README.md index 191da20669e185d819ec5eed55427461cc0b10e4..bd53ab4b0c023b2591d792b504ab496a42d2835d 100644 --- a/paddle/fluid/train/demo/README.md +++ b/paddle/fluid/train/demo/README.md @@ -9,7 +9,6 @@ PADDLE_LIB=/paddle/lib/dir cmake .. -DFLUID_INSTALL_DIR=$PADDLE_LIB \ -DCMAKE_BUILD_TYPE=Release \ - -DWITH_FLUID_ONLY=ON \ -DWITH_GPU=OFF \ -DWITH_STYLE_CHECK=OFF \ -DWITH_MKL=OFF \ diff --git a/paddle/scripts/README.md b/paddle/scripts/README.md index 6c608fce3cdad38f3109e563be3ffbe2f73e5390..1db262f06d97665ee09b8e1d3485982b6b1b33d6 100644 --- a/paddle/scripts/README.md +++ b/paddle/scripts/README.md @@ -66,12 +66,10 @@ Users can specify the following Docker build arguments with either "ON" or "OFF" | `WITH_AVX` | OFF | Set to "ON" to enable AVX support. | | `WITH_TESTING` | OFF | Build unit tests binaries. | | `WITH_MKL` | ON | Build with [Intel® MKL](https://software.intel.com/en-us/mkl) and [Intel® MKL-DNN](https://github.com/01org/mkl-dnn) support. | -| `WITH_GOLANG` | OFF | Build fault-tolerant parameter server written in go. | | `WITH_PYTHON` | ON | Build with python support. Turn this off if build is only for capi. | | `WITH_STYLE_CHECK` | ON | Check the code style when building. | | `PYTHON_ABI` | "" | Build for different python ABI support, can be cp27-cp27m or cp27-cp27mu | | `RUN_TEST` | OFF | Run unit test immediently after the build. | -| `WITH_DOC` | OFF | Build docs after build binaries. | | `WOBOQ` | OFF | Generate WOBOQ code viewer under `build/woboq_out` | ## Docker Images diff --git a/paddle/scripts/fast_install.sh b/paddle/scripts/fast_install.sh index b960d0f00a26196c827053c41a3b35b97e7cdb07..0461944ca8c6c5aeaffcac1eceac097e4d25b6d1 100644 --- a/paddle/scripts/fast_install.sh +++ b/paddle/scripts/fast_install.sh @@ -1,5 +1,37 @@ #!/bin/bash +## purple to echo +function purple(){ + echo -e "\033[35m$1\033[0m" +} + + +## green to echo +function green(){ + echo -e "\033[32m$1\033[0m" +} + +## Error to warning with blink +function bred(){ + echo -e "\033[31m\033[01m\033[05m$1\033[0m" +} + +## Error to warning with blink +function byellow(){ + echo -e "\033[33m\033[01m\033[05m$1\033[0m" +} + + +## Error +function red(){ + echo -e "\033[31m\033[01m$1\033[0m" +} + +## warning +function yellow(){ + echo -e "\033[33m\033[01m$1\033[0m" +} + path='http://paddlepaddle.org/download?url=' #release_version=`curl -s https://pypi.org/project/paddlepaddle/|grep -E "/project/paddlepaddle/"|grep "release"|awk -F '/' '{print $(NF-1)}'|head -1` release_version=1.2.0 @@ -228,36 +260,128 @@ function checkLinuxPaddleVersion(){ done } -function checkLinuxPip(){ +function checkPythonVirtualenv(){ while true do - echo "请输入您要使用的pip目录（您可以另起终端，并使用which pip来查看）：" - read -p "" pip_path - if [ "$pip_path" == "" -o ! -f "$pip_path" ];then - echo "检测结果：pip不存在,请重新输入" - continue - fi - python_version=`$pip_path --version|awk -F "[ |)]" '{print $6}'|sed 's#\.##g'` - if [ "$python_version" == "27" ];then - uncode=`python -c "import pip._internal;print(pip._internal.pep425tags.get_supported())"|grep "cp27mu"` - if [[ "$uncode" == "" ]];then - uncode= - else - uncode=u - fi - fi - if [ "$python_version" == "" ];then - echo "检测结果：pip不存在,请重新输入" - else - version_list=`echo "${python_list[@]}" | grep "$python_version" ` - if [ "$version_list" != "" ];then - echo "检测结果：找到python${python_version}版本" - break - else - echo "检测结果：找不到可用的 pip, 我们只支持Python27/35/36/37及其对应的pip, 请重新输入， 或使用ctrl + c退出 " - fi - fi + read -p " + 是否使用python virtualenv虚环境安装(y/n)": check_virtualenv + case $check_virtualenv in + y) + echo "为您使用python虚环境安装" + ;; + n) + break + ;; + *) + continue + ;; + esac + + virtualenv_path=`which virtualenv 2>&1` + if [ "$virtualenv_path" == "" ];then + $python_path -m pip install virtualenv + if [ "$?" != '0' ];then + echo "安装虚拟环境失败,请检查本地环境" + fi + fi + + while true + do + read -p "请输入虚拟环境名字：" virtualenv_name + if [ "$virtualenv_name" == "" ];then + echo "不能为空" + continue + fi + break + done + + virtualenv -p $python_path ${virtualenv_name} + if [ "$?" != 0 ];then + echo "创建虚环境失败,请检查环境" + exit 2 + fi + cd ${virtualenv_name} + source ./bin/activate + + if [ "$?" == 0 ];then + use_virtualenv= + python_path=`which python` + break + else + echo "创建虚环境失败,请检查环境" + exit 2 + fi + done +} + +function checkLinuxPython(){ + python_path=`which python 2>/dev/null` + while true + do + if [ "$python_path" == '' ];then + while true + do + read -p "没有找到默认的python版本,请输入要安装的python路径:" python_path + python_path=`$python_path -V` + if [ "$python_path" != "" ];then + break + else + echo "输入路径有误,未找到pyrhon" + fi done + fi + + python_version=`$python_path -V 2>&1|awk -F '[ .]' '{print $2$3}'` + pip_version=`$python_path -m pip -V|awk -F '[ .]' '{print $2}'` + while true + do + read -p " + 找到python版本$python_version,使用请输入y,选择其他版本请输n(y/n):" check_python + case $check_python in + n) + read -p "请指定您的python路径:" new_python_path + python_V=`$new_python_path -V 2>/dev/null` + if [ "$python_V" != "" ];then + python_path=$new_python_path + python_version=`$python_path -V 2>&1|awk -F '[ .]' '{print $2$3}'` + pip_version=`python -m pip -V|awk -F '[ .]' '{print $2}'` + echo "您的python版本为${python_version}" + break + else + echo 输入有误,未找到python路径 + fi + ;; + y) + break + ;; + *) + echo "输入有误，请重新输入." + continue + ;; + esac + done + + if [ "$pip_version" -lt 9 ];then + echo "您的pip版本小于9.0.1 请升级pip (pip install --upgrade pip)" + exit 0 + fi + + if [ "$python_version" == "27" ];then + uncode=`python -c "import pip._internal;print(pip._internal.pep425tags.get_supported())"|grep "cp27mu"` + if [[ "$uncode" == "" ]];then + uncode= + else + uncode=u + fi + fi + + version_list=`echo "${python_list[@]}" | grep "$python_version" ` + if [ "$version_list" == "" ];then + echo "找不到可用的 pip, 我们只支持Python27/35/36/37及其对应的pip, 请重新输入， 或使用ctrl + c退出 " + else + break + fi + done } function checkLinuxAVX(){ @@ -287,25 +411,36 @@ function PipLinuxInstall(){ wheel_cpu_develop="http://paddle-wheel.bj.bcebos.com/latest-cpu-${AVX}-${math}/paddlepaddle-latest-cp${python_version}-cp${python_version}m${uncode}-linux_x86_64.whl" wheel_gpu_develop="http://paddle-wheel.bj.bcebos.com/latest-gpu-cuda${CUDA}-cudnn${CUDNN}-${AVX}-${math}/paddlepaddle_gpu-latest-cp${python_version}-cp${python_version}m${uncode}-linux_x86_64.whl" - if [[ "$paddle_version" == "2" ]];then if [[ "$GPU" == "gpu" ]];then if [[ ${AVX} == "avx" ]];then rm -rf `echo $wheel_gpu_release|awk -F '/' '{print $NF}'` wget -q $wheel_gpu_release if [ "$?" == "0" ];then - $pip_path install --user -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_gpu_release + $python_path -m pip install ${use_virtualenv} -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_gpu_release + if [ "$?" == 0 ];then + echo 安装成功 + else + echo 安装失败 + exit 1 + fi else - echo "paddlepaddle whl包下载失败" + echo paddlepaddle whl包下载失败 exit 1 fi else rm -rf `echo $wheel_gpu_release_novax|awk -F '/' '{print $NF}'` wget -q $wheel_gpu_release_novax if [ "$?" == "0" ];then - $pip_path install --user -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_gpu_release_noavx + $python_path -m pip install ${use_virtualenv} -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_gpu_release_noavx + if [ "$?" == 0 ];then + echo 安装成功 + else + echo 安装失败 + exit 1 + fi else - echo "paddlepaddle whl包下载失败" + echo paddlepaddle whl包下载失败 exit 1 fi fi @@ -313,9 +448,15 @@ function PipLinuxInstall(){ rm -rf `echo $wheel_cpu_release|awk -F '/' '{print $NF}'` wget -q $wheel_cpu_release if [ "$?" == "0" ];then - $pip_path install --user -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_cpu_release + $python_path -m pip install ${use_virtualenv} -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_cpu_release + if [ "$?" == 0 ];then + echo 安装成功 + else + echo 安装失败 + exit 1 + fi else - echo "paddlepaddle whl包下载失败" + echo paddlepaddle whl包下载失败 exit 1 fi fi @@ -324,18 +465,30 @@ function PipLinuxInstall(){ rm -rf `echo $wheel_gpu_develop|awk -F '/' '{print $NF}'` wget -q $wheel_gpu_develop if [ "$?" == "0" ];then - $pip_path install --user -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_gpu_develop + $python_path -m pip install ${use_virtualenv} -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_gpu_develop + if [ "$?" == 0 ];then + echo 安装成功 + else + echo 安装失败 + exit 1 + fi else - echo "paddlepaddle whl包下载失败" + echo paddlepaddle whl包下载失败 exit 1 fi else rm -rf `echo $wheel_cpu_develop|awk -F '/' '{print $NF}'` wget -q $wheel_cpu_develop if [ "$?" == "0" ];then - $pip_path install --user -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_cpu_develop + $python_path -m pip install ${use_virtualenv} -i https://mirrors.aliyun.com/pypi/simple --trusted-host=mirrors.aliyun.com $wheel_cpu_develop + if [ "$?" == 0 ];then + echo 安装成功 + else + echo 安装失败 + exit 1 + fi else - echo "paddlepaddle whl包下载失败" + echo paddlepaddle whl包下载失败 exit 1 fi fi @@ -575,95 +728,122 @@ gpu_list=( echo echo "Step 5. 检测pip版本" echo - checkLinuxPip + checkLinuxPython echo checkLinuxAVX + echo + echo "Step 6.是否使用Python的虚拟环境" + use_virtualenv="--user" + checkPythonVirtualenv echo "*********************2. 开始安装*****************************" PipLinuxInstall + if [ "$check_virtualenv" == 'y' ];then + echo "虚环境创建成功，请cd 进入${virtualenv_name}, 执行 source bin/activate　进入虚环境。退出虚环境执行 deactivate命令。 + 更多虚环境使用方法请参考virtualenv官网:https://virtualenv.pypa.io/en/latest/" + fi +} + +function clearMacPythonEnv(){ + python_version="" + python_brief_version="" + python_root="" } function checkMacPython2(){ while true do - read -p " - => 未能在常规路径下找到Python2，请使用ctrl+c命令退出安装程序，并使用brew或pypi.org下载安装Python2（注意Python版本不能低于2.7.15） - 如希望自定义Python路径，请输入路径：" python_root - echo python_version=`$python_root --version 2>&1 1>&1` - if [ $? == "0" ];then - : + if [[ $? == "0" ]];then + if [ "$python_version" == "" ] || [ "$python_root" == "/usr/bin/python" -a "$python_version" == "Python 2.7.10" ];then + clearMacPythonEnv + else + check_python=`echo $python_version | grep "Python 2"` + if [[ -n "$check_python" ]];then + while true + do + echo -e " => 在您的环境中找到 \033[32m[ $python_version ]\033[0m, 确认使用此版本请输入y；如您希望自定义Python路径请输入n。请在这里输入（y/n）并回车: " + read -p "" use_python + echo + use_python=`echo $use_python | tr 'A-Z' 'a-z'` + if [[ "$use_python" == "y" ]]||[[ "$use_python" == "" ]];then + use_python="y" + break + elif [[ "$use_python" == "n" ]];then + clearMacPythonEnv + break + else + red " 输入错误，请重新输入(y/n)" + fi + done + if [[ "$use_python" == "y" ]];then + return 0 + fi + else + red " 您输入Python的不是Python2" + clearMacPythonEnv + fi + fi else - python_version="" + clearMacPythonEnv + red " => 未能在常规路径下找到可用的Python2，请使用ctrl+c命令退出安装程序，并使用brew或pypi.org下载安装Python2（注意Python版本不能低于2.7.15）" + read -p " 如希望自定义Python路径，请输入路径 + 如果希望重新选择Python版本，请回车：" python_root + echo + if [[ "$python_root" == "" ]];then + python_V="" + clearMacPythonEnv + return 1 + fi fi - check_python=`echo $python_version | grep "Python 2"` - if [ "$python_version" == "" ] || [ "$python_root" == "/usr/bin/python" -a "$python_version" == "Python 2.7.10" ] ;then - python_version="" - elif [ -n "$check_python" ];then - while true - do - read -p " - => 在您的环境中找到 $python_version, 确认使用此版本请输入y；如您希望自定义Python路径请输入n。请在这里输入（y/n）并回车: " use_python - echo - use_python=`echo $use_python | tr 'A-Z' 'a-z'` - if [ "$use_python" == "y" ]||[ "$use_python" == "" ];then - use_python="y" - break - elif [ "$use_python" == "n" ];then - python_root="" - break - else - echo "输入错误，请重新输入(y/n)" - fi - done - if [ "$use_python" == "y" ];then - break - fi - else - echo "您输入Python的不是Python2" - python_version="" - fi done } function checkMacPython3(){ while true do - read -p " - => 未能在常规路径下找到Python3，请使用ctrl+c命令退出安装程序，并使用brew或pypi.org下载Python3 - 如希望自定义Python路径，请输入路径：" python_root - python_version=`$python_root --version 2>&1 1>&1` - if [ $? == "0" ];then - : + python_version=`$python_root --version 2>&1 1>&1` + if [[ $? == "0" ]];then + if [ "$python_version" == "" ] || [ "$python_root" == "/usr/bin/python" -a "$python_version" == "Python 2.7.10" ] ;then + clearMacPythonEnv + else + check_python=`echo $python_version | grep "Python 3"` + if [[ -n "$check_python" ]];then + while true + do + echo -e " => 在您的环境中找到 \033[32m[ $python_version ]\033[0m, 确认使用此版本请输入y；如您希望自定义Python路径请输入n。请在这里输入（y/n）并回车: " + read -p "" use_python + echo + use_python=`echo $use_python | tr 'A-Z' 'a-z'` + if [[ "$use_python" == "y" ]]||[[ "$use_python" == "" ]];then + use_python="y" + break + elif [[ "$use_python" == "n" ]];then + clearMacPythonEnv + break + else + red " 输入错误，请重新输入(y/n)" + fi + done + if [[ "$use_python" == "y" ]];then + return 0 + fi + else + red " 您输入Python的不是Python3" + clearMacPythonEnv + fi + fi else - python_version="" + clearMacPythonEnv + red " => 未能在常规路径下找到可用的Python3，请使用ctrl+c命令退出安装程序，并使用brew或pypi.org下载安装Python3（注意Python版本不能低于3.5.x)" + read -p " 如希望自定义Python路径，请输入路径 + 如果希望重新选择Python版本，请回车：" python_root + echo + if [[ "$python_root" == "" ]];then + python_V="" + clearMacPythonEnv + return 1 + fi fi - check_python=`echo $python_version | grep "Python 3"` - if [ "$python_version" == "" ] || [ "$python_root" == "/usr/bin/python" -a "$python_version" == "Python 2.7.10" ] ;then - python_version="" - elif [ -n "$check_python" ] ;then - while true - do - read -p " - => 在您的环境中找到 $python_version, 确认使用此版本请输入y；如您希望自定义Python路径请输入n。请在这里输入（y/n）并回车: " use_python - echo - use_python=`echo $use_python | tr 'A-Z' 'a-z'` - if [ "$use_python" == "y" ]||[ "$use_python" == "" ];then - use_python="y" - break - elif [ "$use_python" == "n" ];then - python_root="" - break - else - echo "输入错误，请重新输入(y/n)" - fi - done - if [ "$use_python" == "y" ];then - break - fi - else - echo "您输入Python的不是Python3" - python_version="" - fi done } @@ -672,145 +852,160 @@ function checkMacPaddleVersion(){ do read -n1 -p "Step 2. 选择PaddlePaddle的版本，请按回车键继续..." echo - read -p " - 1. 开发版：对应Github上develop分支，如您需要开发、或希望使用PaddlePaddle最新功能，请选用此版本 - 2. 稳定版（推荐）：如您无特殊开发需求，建议使用此版本，目前最新的版本号为 ${release_version} - - => 请输入数字1或2。如输入其他字符或直接回车，将会默认选择【 2. 稳定版 】 。请在这里输入并回车：" paddle_version - if [ "$paddle_version" == "1" ]||[ "$paddle_version" == "2" ];then + yellow " 1. 开发版：对应Github上develop分支，如您需要开发、或希望使用PaddlePaddle最新功能，请选用此版本" + yellow " 2. 稳定版（推荐）：如您无特殊开发需求，建议使用此版本，目前最新的版本号为 ${release_version}" + read -p " => 请输入数字1或2。如输入其他字符或直接回车，将会默认选择【 2. 稳定版 】 。请在这里输入并回车：" paddle_version + if [[ "$paddle_version" == "1" ]]||[[ "$paddle_version" == "2" ]];then echo - echo "您选择了数字【"$paddle_version" 】" + yellow " 您选择了数字【"$paddle_version" 】" echo break else paddle_version="2" echo - echo "您选择了数字【2】" + yellow " 您选择了数字【2】" echo break fi done } +function initCheckMacPython2(){ + echo + yellow " 您选择了Python "$python_V"，正在寻找符合要求的Python 2版本" + echo + python_root=`which python2.7` + if [[ "$python_root" == "" ]];then + python_root=`which python` + fi + checkMacPython2 + if [[ "$?" == "1" ]];then + return 1 + else + return 0 + fi +} -function checkMacPythonVersion(){ - while true - do - read -n1 -p "Step 3. 选择Python版本，请按回车键继续..." - read -p " - 2. 使用python 2.x - 3. 使用python 3.x +function initCheckMacPython3(){ + echo + yellow " 您选择了Python "$python_V"，正在寻找符合您要求的Python 2版本" + echo + python_root=`which python3` + checkMacPython3 + if [[ "$?" == "1" ]];then + return 1 + else + return 0 + fi +} - => 请输入数字2或3。如输入其他字符或直接回车，将会默认使用【Python 2 】。请在这里输入并回车：" python_V - echo - if [ "$python_V" == "" ];then - python_V="2" +function checkMacPip(){ + if [[ "$python_V" == "2" ]]||[[ "$python_V" == "3" ]];then + + python_brief_version=`$python_root -m pip -V |awk -F "[ |)]" '{print $6}'|sed 's#\.##g'` + if [[ ${python_brief_version} == "" ]];then + red "您输入的python：${python_root} 对应的pip不可用，请检查此pip或重新选择其他python" + echo + return 1 fi - echo "您选择了数字【"$python_V"】，正在寻找符合您要求的Python版本，请按回车键继续..." - echo - if [ "$python_V" == "2" ];then - python_root=`which python2.7` - if [ "$python_root" == "" ];then - python_root=`which python` - fi - python_version=`$python_root --version 2>&1 1>&1` - if [ $? == "0" ];then - : - else - python_version="" - fi - if [ "$python_root" == "" ]||[ "$python_root" == "/usr/bin/python" -a "$python_version" == "Python 2.7.10" ]||[ "$python_root" == "/usr/bin/python2.7" -a "$python_version" == "Python 2.7.10" ];then - checkMacPython2 - fi - while true - do - read -p " - => 在您的环境中找到 $python_version, 确认使用此版本请输入y；如您希望自定义Python路径请输入n。请在这里输入（y/n）并回车：" use_python - echo - use_python=`echo $use_python | tr 'A-Z' 'a-z'` - if [ "$use_python" == "y" ]||[ "$use_python" == "" ];then - break - elif [ "$use_python" == "n" ];then - python_root="" - checkMacPython2 - break + pip_version=`$python_root -m pip -V |awk -F '[ .]' '{print $2}'` + if [[ 9 -le ${pip_version} ]];then + : + else + red "您的pip版本过低，请安装pip 9.0.1及以上的版本" + echo + return 1 + fi + if [[ "$python_brief_version" == "" ]];then + clearMacPythonEnv + red "您的 $python_root 对应的pip存在问题，请按ctrl + c退出后重新安装pip，或切换其他python版本" + echo + return 1 + else + if [[ $python_brief_version == "27" ]];then + uncode=`python -c "import pip._internal;print(pip._internal.pep425tags.get_supported())"|grep "cp27"` + if [[ $uncode == "" ]];then + uncode="mu" else - echo "输入错误，请重新输入(y/n)" + uncode="m" fi - done - - elif [ "$python_V" == "3" ];then - python_root=`which python3` - python_version=`$python_root --version 2>&1 1>&1` - if [ $? == "0" ];then - : - else - python_version="" - fi - if [ "$python_root" == "" ]||[ "$python_root" == "/usr/bin/python" -a "$python_version" == "Python 2.7.10" ];then - checkMacPython3 - fi - while true - do - read -p " - => 在您的环境中找到 $python_version, 确认使用此版本请输入y；如您希望自定义Python路径请输入n。请在这里输入（y/n）并回车：" use_python + fi + version_list=`echo "${python_list[@]}" | grep "$python_brief_version" ` + if [[ "$version_list" != "" ]];then + return 0 + else + red "未找到可用的pip或pip3。PaddlePaddle目前支持：Python2.7/3.5/3.6/3.7及其对应的pip, 请重新输入，或使用ctrl + c退出" echo - use_python=`echo $use_python | tr 'A-Z' 'a-z'` - if [ "$use_python" == "y" ]||[ "$use_python" == "" ];then - break - elif [ "$use_python" == "n" ];then - checkMacPython3 - break - else - echo "输入错误，请重新输入(y/n)" - fi - done - else - : - fi + clearMacPythonEnv + return 1 + fi + fi + fi +} - if [ "$python_V" == "2" ]||[ "$python_V" == "3" ];then - python_brief_version=`$python_root -m pip -V |awk -F "[ |)]" '{print $6}'|sed 's#\.##g'` - if [[ $python_brief_version == "27" ]];then - uncode=`python -c "import pip._internal;print(pip._internal.pep425tags.get_supported())"|grep "cp27"` - if [[ $uncode == "" ]];then - uncode="mu" - else - uncode="m" - fi - fi - version_list=`echo "${python_list[@]}" | grep "$python_brief_version" ` - if [ "$version_list" != "" ];then - break +function checkMacPythonVersion(){ + while true + do + read -n1 -p "Step 3. 选择Python版本，请按回车键继续..." + echo + yellow " 2. 使用python 2.x" + yellow " 3. 使用python 3.x" + read -p " => 请输入数字2或3。如输入其他字符或直接回车，将会默认使用【Python 2 】。请在这里输入并回车：" python_V + if [[ "$python_V" == "" ]];then + python_V="2" + fi + if [[ "$python_V" == "2" ]];then + initCheckMacPython2 + if [[ "$?" == "0" ]];then + checkMacPip + if [[ "$?" == "0" ]];then + return 0 + else + : + fi else - echo "未找到可用的pip或pip3。PaddlePaddle目前支持：Python2.7/3.5/3.6/3.7及其对应的pip, 请重新输入，或使用ctrl + c退出" - fi - else - echo "输入错误，请重新输入" - fi + : + fi + elif [[ "$python_V" == "3" ]];then + initCheckMacPython3 + if [[ "$?" == "0" ]];then + checkMacPip + if [[ "$?" == "0" ]];then + return 0 + else + : + fi + else + : + fi + else + red "输入错误，请重新输入" + fi done } function checkMacAVX(){ read -n1 -p "Step 4. 检测您的Mac是否支持AVX指令集，请按回车键继续..." - echo if [[ $AVX != "" ]];then AVX="avx" - echo "检测结果：支持" + echo "" + green " 检测结果：支持" + echo "" + return 0 else - read -n1 -p "检测结果：不支持。非常抱歉，PaddlePaddle在Mac系统暂不提供no_avx类型的安装包，您可以选择在Linux系统中安装no_avx版的PaddlePaddle, 请按回车键退出..." - exit + red " 检测结果：不支持。非常抱歉，PaddlePaddle在Mac系统暂不提供no_avx类型的安装包，您可以选择在Linux系统中安装no_avx版的PaddlePaddle, 请按回车键退出..." + echo + return 1 fi - echo } function checkMacGPU(){ read -n1 -p "Step 5. 选择CPU/GPU版本，请按回车键继续..." echo if [[ $GPU != "" ]];then - echo "MacOS环境下，暂未提供GPU版本的PaddlePaddle安装包，将为您安装CPU版本的PaddlePaddle" + yellow " MacOS环境下，暂未提供GPU版本的PaddlePaddle安装包，将为您安装CPU版本的PaddlePaddle" else - echo "MacOS环境下，暂未提供GPU版本的PaddlePaddle安装包，将为您安装CPU版本的PaddlePaddle" + yellow " MacOS环境下，暂未提供GPU版本的PaddlePaddle安装包，将为您安装CPU版本的PaddlePaddle" GPU=cpu fi echo @@ -822,38 +1017,44 @@ function macos() { while true do + checkMacPaddleVersion + checkMacPythonVersion + checkMacAVX + checkMacGPU - echo "*********************2. 开始安装*****************************" + green "*********************2. 开始安装*****************************" echo - read -n1 -p "即将为您下载并安装PaddlePaddle，请按回车键继续..." + yellow "即将为您下载并安装PaddlePaddle，请按回车键继续..." + read -n1 -p "" echo if [[ $paddle_version == "2" ]];then $python_root -m pip install paddlepaddle - if [ $? == "0" ];then - echo "安装成功，可以使用: ${python_root} 来启动安装了PaddlePaddle的Python解释器" + if [[ $? == "0" ]];then + green "安装成功，可以使用: ${python_root} 来启动安装了PaddlePaddle的Python解释器" break else rm $whl_cpu_release - echo "未能正常安装PaddlePaddle，请尝试更换您输入的python路径，或者ctrl + c退出后请检查您使用的python对应的pip或pip源是否可用" + red "未能正常安装PaddlePaddle，请尝试更换您输入的python路径，或者ctrl + c退出后请检查您使用的python对应的pip或pip源是否可用" echo"" echo "==========================================================================================" echo"" exit 1 fi else - if [ -f $whl_cpu_develop ];then + if [[ -f $whl_cpu_develop ]];then $python_root -m pip install $whl_cpu_develop - if [ $? == "0" ];then + if [[ $? == "0" ]];then rm -rf $whl_cpu_develop - echo "安装成功！小提示：可以使用: ${python_root} 来启动安装了PaddlePaddle的Python解释器" + # TODO add install success check here + green "安装成功！小提示：可以使用: ${python_root} 来启动安装了PaddlePaddle的Python解释器" break else - echo "未能正常安装PaddlePaddle，请尝试更换您输入的python路径，或者ctrl + c退出后请检查您使用的python对应的pip或pip源是否可用" + red "未能正常安装PaddlePaddle，请尝试更换您输入的python路径，或者ctrl + c退出后请检查您使用的python对应的pip或pip源是否可用" echo"" echo "==========================================================================================" echo"" @@ -861,15 +1062,15 @@ function macos() { fi else wget ${path}$whl_cpu_develop -O $whl_cpu_develop - if [ $? == "0" ];then + if [[ $? == "0" ]];then $python_root -m pip install $whl_cpu_develop - if [ $? == "0" ];then + if [[ $? == "0" ]];then rm $wheel_cpu_develop - echo "安装成功，可以使用: ${python_root} 来启动安装了PaddlePaddle的Python解释器" + green "安装成功，可以使用: ${python_root} 来启动安装了PaddlePaddle的Python解释器" break else rm $whl_cpu_release - echo "未能正常安装PaddlePaddle，请尝试更换您输入的python路径，或者ctrl + c退出后请检查您使用的python对应的pip或pip源是否可用" + red "未能正常安装PaddlePaddle，请尝试更换您输入的python路径，或者ctrl + c退出后请检查您使用的python对应的pip或pip源是否可用" echo"" echo "==========================================================================================" echo"" @@ -877,7 +1078,7 @@ function macos() { fi else rm $whl_cpu_develop - echo "未能正常安装PaddlePaddle，请检查您的网络 或者确认您是否安装有 wget，或者ctrl + c退出后反馈至https://github.com/PaddlePaddle/Paddle/issues" + red "未能正常安装PaddlePaddle，请检查您的网络 或者确认您是否安装有 wget，或者ctrl + c退出后反馈至https://github.com/PaddlePaddle/Paddle/issues" echo"" echo "==========================================================================================" echo"" @@ -890,33 +1091,35 @@ function macos() { function main() { echo "*********************************" - echo "欢迎使用PaddlePaddle快速安装脚本" + green "欢迎使用PaddlePaddle快速安装脚本" echo "*********************************" echo - echo "如果您在安装过程中遇到任何问题，请在https://github.com/PaddlePaddle/Paddle/issues反馈，我们的工作人员将会帮您答疑解惑" + yellow "如果您在安装过程中遇到任何问题，请在https://github.com/PaddlePaddle/Paddle/issues反馈，我们的工作人员将会帮您答疑解惑" echo - echo "本安装包将帮助您在Linux或Mac系统下安装PaddlePaddle，包括 1）安装前的准备和 2）开始安装 两部分" + echo "本安装包将帮助您在Linux或Mac系统下安装PaddlePaddle,包括" + yellow "1）安装前的准备" + yellow "2）开始安装" echo read -n1 -p "请按回车键进行下一步..." echo echo - echo "*********************1. 安装前的准备*****************************" + green "*********************1. 安装前的准备*****************************" echo echo "Step 1. 正在检测您的操作系统信息..." echo SYSTEM=`uname -s` - if [ "$SYSTEM" == "Darwin" ];then - echo "您的系统为：MAC OSX" + if [[ "$SYSTEM" == "Darwin" ]];then + yellow " 您的系统为：MAC OSX" echo macos else - echo "您的系统为：Linux" + yellow " 您的系统为：Linux" echo OS=`cat /etc/issue|awk 'NR==1 {print $1}'` - if [ $OS == "\S" ] || [ "$OS" == "CentOS" ] || [ $OS == "Ubuntu" ];then + if [[ $OS == "\S" ]] || [[ "$OS" == "CentOS" ]] || [[ $OS == "Ubuntu" ]];then linux else - echo "您的系统不在本安装包的支持范围，如您需要在windows环境下安装PaddlePaddle，请您参考PaddlePaddle官网的windows安装文档" + red "您的系统不在本安装包的支持范围，如您需要在windows环境下安装PaddlePaddle，请您参考PaddlePaddle官网的windows安装文档" fi fi } diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh index e7078499cae87b8a255c6c6d4774052e1f768aa7..26b26c9b1faf7bd976b57f1320bff878f1a21770 100755 --- a/paddle/scripts/paddle_build.sh +++ b/paddle/scripts/paddle_build.sh @@ -87,7 +87,6 @@ function cmake_gen() { PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/Library/Frameworks/Python.framework/Versions/3.5/bin/python3 -DPYTHON_INCLUDE_DIR:PATH=/Library/Frameworks/Python.framework/Versions/3.5/include/python3.5m/ -DPYTHON_LIBRARY:FILEPATH=/Library/Frameworks/Python.framework/Versions/3.5/lib/libpython3.5m.dylib" - WITH_FLUID_ONLY=${WITH_FLUID_ONLY:-ON} pip3.5 uninstall -y protobuf pip3.5 install --user -r ${PADDLE_ROOT}/python/requirements.txt else @@ -101,7 +100,6 @@ function cmake_gen() { PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/Library/Frameworks/Python.framework/Versions/3.6/bin/python3 -DPYTHON_INCLUDE_DIR:PATH=/Library/Frameworks/Python.framework/Versions/3.6/include/python3.6m/ -DPYTHON_LIBRARY:FILEPATH=/Library/Frameworks/Python.framework/Versions/3.6/lib/libpython3.6m.dylib" - WITH_FLUID_ONLY=${WITH_FLUID_ONLY:-ON} pip3.6 uninstall -y protobuf pip3.6 install --user -r ${PADDLE_ROOT}/python/requirements.txt else @@ -115,7 +113,6 @@ function cmake_gen() { PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/Library/Frameworks/Python.framework/Versions/3.7/bin/python3 -DPYTHON_INCLUDE_DIR:PATH=/Library/Frameworks/Python.framework/Versions/3.7/include/python3.7m/ -DPYTHON_LIBRARY:FILEPATH=/Library/Frameworks/Python.framework/Versions/3.7/lib/libpython3.7m.dylib" - WITH_FLUID_ONLY=${WITH_FLUID_ONLY:-ON} pip3.7 uninstall -y protobuf pip3.7 install --user -r ${PADDLE_ROOT}/python/requirements.txt else @@ -202,7 +199,6 @@ function cmake_gen() { -DWITH_TESTING=${WITH_TESTING:-ON} -DCMAKE_MODULE_PATH=/opt/rocm/hip/cmake -DCMAKE_EXPORT_COMPILE_COMMANDS=ON - -DWITH_FLUID_ONLY=${WITH_FLUID_ONLY:-OFF} -DCMAKE_EXPORT_COMPILE_COMMANDS=ON -DWITH_CONTRIB=${WITH_CONTRIB:-ON} -DWITH_INFERENCE_API_TEST=${WITH_INFERENCE_API_TEST:-ON} @@ -235,7 +231,6 @@ EOF -DCUDNN_ROOT=/usr/ \ -DWITH_TESTING=${WITH_TESTING:-ON} \ -DCMAKE_MODULE_PATH=/opt/rocm/hip/cmake \ - -DWITH_FLUID_ONLY=${WITH_FLUID_ONLY:-OFF} \ -DCMAKE_EXPORT_COMPILE_COMMANDS=ON \ -DWITH_CONTRIB=${WITH_CONTRIB:-ON} \ -DWITH_INFERENCE_API_TEST=${WITH_INFERENCE_API_TEST:-ON} \ @@ -398,9 +393,7 @@ EOF pip3.7 install --user ${INSTALL_PREFIX:-/paddle/build}/opt/paddle/share/wheels/*.whl fi - if [[ ${WITH_FLUID_ONLY:-OFF} == "OFF" ]] ; then - paddle version - fi + paddle version if [ "$1" == "cp27-cp27m" ]; then pip uninstall -y paddlepaddle @@ -555,7 +548,6 @@ EOF -DCMAKE_BUILD_TYPE=Release \ -DWITH_GPU=OFF \ -DWITH_MKL=OFF \ - -DWITH_FLUID_ONLY=ON local LIB_TYPE=$1 case $LIB_TYPE in @@ -631,13 +623,8 @@ EOF NCCL_DEPS="true" fi - if [[ ${WITH_FLUID_ONLY:-OFF} == "OFF" ]]; then - PADDLE_VERSION="paddle version" - CMD='"paddle", "version"' - else - PADDLE_VERSION="true" - CMD='"true"' - fi + PADDLE_VERSION="paddle version" + CMD='"paddle", "version"' if [ "$1" == "cp35-cp35m" ]; then cat >> ${PADDLE_ROOT}/build/Dockerfile <> ${PADDLE_ROOT}/build/Dockerfile <> ${PADDLE_ROOT}/build/Dockerfile < 1 and trainers_endpoints: assert self._build_strategy.num_trainers == len( @@ -220,7 +220,7 @@ class CompiledProgram(object): if self._compiled: if scope and self._scope != scope: raise ValueError("Cannot compile with different scope") - if place and self._place != place: + if place and not self._place._equals(place): raise ValueError("Cannot compile with different place") return self self._compiled = True diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py index a2abbf36c0267d85c9c97af00c9faabf1187822c..24e102b6c2612b58a9b8367ebbefcece535d58bb 100644 --- a/python/paddle/fluid/io.py +++ b/python/paddle/fluid/io.py @@ -766,7 +766,10 @@ def _load_distributed_persistables(executor, dirname, main_program=None): dtype=slice_var.dtype, persistable=True) - dim1_flatten = reduce(lambda x, y: x * y, slice.shape[1:]) + dim1_flatten = 1 + if len(slice.shape) >= 2: + dim1_flatten = reduce(lambda x, y: x * y, slice.shape[1:]) + start = int(offset / dim1_flatten) end = int(offset / dim1_flatten + slice.shape[0]) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index fe257f9a37fd5291ec0d8d5f33971e94bfae09e0..1a7d076835841e3c1b8a90a43437eff13645fb8a 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -8744,16 +8744,17 @@ def slice(input, axes, starts, ends): return out -@templatedoc() def shape(input): """ - ${comment} + **Shape Layer** + + Get the shape of the input. Args: - input (Variable): ${input_comment} + input (Variable): The input variable. Returns: - out (Variable): ${out_comment} + Variable: The shape of the input variable. Examples: .. code-block:: python diff --git a/python/paddle/fluid/optimizer.py b/python/paddle/fluid/optimizer.py index fe2b3fbbd91f24881341003ad78af06e33772fd4..cb799b639648fc0af64a890ffe788d23e7f4f9eb 100644 --- a/python/paddle/fluid/optimizer.py +++ b/python/paddle/fluid/optimizer.py @@ -649,6 +649,7 @@ class AdagradOptimizer(Optimizer): regularization: A Regularizer, such as fluid.regularizer.L2DecayRegularizer. name: A optional name prefix. + initial_accumulator_value (float): Initial value for moment accumulator. Examples: .. code-block:: python @@ -662,7 +663,8 @@ class AdagradOptimizer(Optimizer): learning_rate, epsilon=1.0e-6, regularization=None, - name=None): + name=None, + initial_accumulator_value=0.0): assert learning_rate is not None assert epsilon is not None super(AdagradOptimizer, self).__init__( @@ -671,6 +673,7 @@ class AdagradOptimizer(Optimizer): name=name) self.type = "adagrad" self._epsilon = epsilon + self.initial_accumulator_value = initial_accumulator_value def _create_accumulators(self, block, parameters): assert isinstance(block, framework.Block) @@ -683,6 +686,16 @@ class AdagradOptimizer(Optimizer): moment_acc = self._get_accumulator(self._moment_acc_str, param_and_grad[0]) + startup_block = framework.default_startup_program().global_block() + startup_block.append_op( + type='fill_constant', + inputs={}, + outputs={'Out': [moment_acc]}, + attrs={ + 'dtype': moment_acc.dtype, + 'value': self.initial_accumulator_value, + 'shape': moment_acc.shape, + }) # Create the adagrad optimizer op adagrad_op = block.append_op( diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index 289a48aac9cf7ff52295feb722a8116939442425..a1cf5fad138f068c9eac5fe8d681c9f08b192270 100644 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -113,12 +113,11 @@ py_test_modules(test_ir_memory_optimize_transformer MODULES test_ir_memory_optim endif() if(NOT APPLE) py_test_modules(test_image_classification_resnet MODULES test_image_classification_resnet SERIAL) - if(CMAKE_BUILD_TYPE STREQUAL "Debug") - # change the timeout from 600 to 1200, because in debug mode, this test need more time. - set_tests_properties(test_image_classification_resnet PROPERTIES TIMEOUT 1200) - endif() endif() - +if(CMAKE_BUILD_TYPE STREQUAL "Debug") + # change the timeout from 600 to 1200, because in debug mode, this test need more time. + set_tests_properties(test_parallel_executor_seresnext PROPERTIES TIMEOUT 1200) +endif() if (WITH_NGRAPH) add_subdirectory(ngraph) diff --git a/python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py b/python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py index ad94a4b21c347c9a2782437948c20d3b3071c679..0f301de47f53f3fcacd38d1415ebdbd7b4efc8f1 100644 --- a/python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py +++ b/python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py @@ -18,8 +18,8 @@ import unittest import numpy as np import paddle.fluid.core as core from paddle.fluid.tests.unittests.op_test import OpTest -from scipy.special import expit from paddle.fluid.tests.unittests.test_activation_op import TestRelu, TestTanh, TestSqrt, TestAbs +import paddle.fluid as fluid class TestMKLDNNReluDim2(TestRelu): @@ -97,5 +97,64 @@ class TestMKLDNNAbsDim4(TestAbs): self.attrs = {"use_mkldnn": True} +# Check if primitives already exist in backward +class TestMKLDNNReluPrimitivesAlreadyExist(unittest.TestCase): + def __assert_close(self, tensor, np_array, msg, atol=1e-4): + self.assertTrue(np.allclose(np.array(tensor), np_array, atol=atol), msg) + + def test_check_forward_backward(self): + place = core.CPUPlace() + + np.random.seed(123) + x = np.random.uniform(-1, 1, [2, 2]).astype(np.float32) + out = np.abs(x) + + out_grad = np.random.random_sample(x.shape).astype(np.float32) + x_grad = out_grad * np.sign(x) # Abs grad calculation + + var_dict = {'x': x, 'out': out, 'out@GRAD': out_grad, 'x@GRAD': x_grad} + var_names = list(var_dict.keys()) + ground_truth = {name: var_dict[name] for name in var_names} + + program = fluid.Program() + with fluid.program_guard(program): + block = program.global_block() + for name in ground_truth: + block.create_var( + name=name, dtype='float32', shape=ground_truth[name].shape) + + relu_op = block.append_op( + type="abs", + inputs={"X": block.var('x'), }, + outputs={"Out": block.var('out')}, + attrs={"use_mkldnn": True}) + + # Generate backward op_desc + grad_op_desc_list, op_grad_to_var = core.get_grad_op_desc( + relu_op.desc, set(), []) + grad_op_desc = grad_op_desc_list[0] + new_op_desc = block.desc.append_op() + new_op_desc.copy_from(grad_op_desc) + for var_name in grad_op_desc.output_arg_names(): + block.desc.var(var_name.encode("ascii")) + grad_op_desc.infer_var_type(block.desc) + grad_op_desc.infer_shape(block.desc) + for arg in grad_op_desc.output_arg_names(): + grad_var = block.desc.find_var(arg.encode("ascii")) + grad_var.set_dtype(core.VarDesc.VarType.FP32) + + exe = fluid.Executor(place) + + # Do at least 2 iterations + for i in range(2): + out = exe.run( + program, + feed={name: var_dict[name] + for name in ['x', 'out@GRAD']}, + fetch_list=['x@GRAD']) + + self.__assert_close(x_grad, out[0], "x@GRAD") + + if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/ngraph/test_cross_entropy_ngraph_op.py b/python/paddle/fluid/tests/unittests/ngraph/test_cross_entropy_ngraph_op.py index 9a185eb97ca6ad4d7987f1a422073d3c8db0d8df..3057218a1d80deffe7eb3164c2350143fc38007d 100644 --- a/python/paddle/fluid/tests/unittests/ngraph/test_cross_entropy_ngraph_op.py +++ b/python/paddle/fluid/tests/unittests/ngraph/test_cross_entropy_ngraph_op.py @@ -1,4 +1,4 @@ -# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# 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. @@ -15,261 +15,7 @@ from __future__ import print_function import unittest -import numpy as np -import paddle.fluid.core as core -from paddle.fluid.tests.unittests.op_test import OpTest, randomize_probability - - -class TestCrossEntropyOp(OpTest): - """Test cross-entropy with discrete one-hot labels. - """ - - def setUp(self): - self.op_type = "cross_entropy" - self.soft_label = False - self.ignore_index = -100 - self.dtype = np.float64 - self.batch_size = 30 - self.class_num = 10 - self._cpu_only = True - - self.init_dtype_type() - self.init_attr_type() - self.init_bs_class_num() - self.init_x() - self.init_label() - self.get_cross_entropy() - - self.inputs = {"X": self.x, "Label": self.label} - self.outputs = {"Y": self.cross_entropy} - self.attrs = { - "soft_label": self.soft_label, - "ignore_index": self.ignore_index - } - - def init_x(self): - self.x = randomize_probability( - self.batch_size, self.class_num, dtype=self.dtype) - - def init_label(self): - self.label = np.random.randint( - 0, self.class_num, (self.batch_size, 1), dtype="int64") - - def get_cross_entropy(self): - self.cross_entropy = np.asmatrix( - [[-np.log(self.x[i][self.label[i][0]])] - for i in range(self.x.shape[0])], - dtype="float64") - - def init_attr_type(self): - pass - - def init_dtype_type(self): - pass - - def init_bs_class_num(self): - pass - - def test_check_output(self): - self.check_output() - - def test_check_grad(self): - self.check_grad(["X"], "Y", numeric_grad_delta=0.001) - - -class TestCrossEntropyOp2(TestCrossEntropyOp): - """Test cross-entropy with vectorized soft labels. - """ - - def init_label(self): - self.label = np.random.uniform( - 0.1, 1.0, [self.batch_size, self.class_num]).astype(self.dtype) - self.label /= self.label.sum(axis=1, keepdims=True) - - def get_cross_entropy(self): - self.cross_entropy = (-self.label * np.log(self.x)).sum( - axis=1, keepdims=True).astype(self.dtype) - - def init_attr_type(self): - self.soft_label = True - - def init_dtype_type(self): - self.dtype = np.float32 - - def init_bs_class_num(self): - self.batch_size = 5 - self.class_num = 37 - - def test_check_grad(self): - self.check_grad( - ["X"], "Y", max_relative_error=0.05, numeric_grad_delta=0.001) - - -class TestCrossEntropyOp3(TestCrossEntropyOp): - """Test cross-entropy with vectorized one-hot representation of labels. - """ - - def init_label(self): - self.label_index = np.random.randint(0, self.class_num, - (self.batch_size)) - self.label = np.zeros(self.x.shape).astype(self.dtype) - self.label[np.arange(self.batch_size), self.label_index] = 1 - - def get_cross_entropy(self): - self.cross_entropy = np.asmatrix( - [[-np.log(self.x[i][self.label_index[i]])] - for i in range(self.x.shape[0])]).astype(self.dtype) - - def init_attr_type(self): - self.soft_label = True - - def init_dtype_type(self): - self.dtype = np.float32 - - def init_bs_class_num(self): - self.batch_size = 5 - self.class_num = 17 - - def test_check_grad(self): - self.check_grad( - ["X"], "Y", max_relative_error=0.05, numeric_grad_delta=0.001) - - -class TestCrossEntropyOp4(TestCrossEntropyOp): - """Test high rank tensor cross-entropy with discrete one-hot labels. - """ - - def init_x(self): - self.shape = [10, 2, 4] - self.ins_num = np.prod(np.array(self.shape)) - self.X_2d = randomize_probability(self.ins_num, - self.class_num).astype(self.dtype) - self.x = self.X_2d.reshape(self.shape + [self.class_num]) - - def init_label(self): - self.label_2d = np.random.randint( - 0, self.class_num, (self.ins_num, 1), dtype="int64") - self.label = self.label_2d.reshape(self.shape + [1]) - - def get_cross_entropy(self): - cross_entropy_2d = np.asmatrix( - [[-np.log(self.X_2d[i][self.label_2d[i][0]])] - for i in range(self.X_2d.shape[0])]).astype(self.dtype) - self.cross_entropy = np.array(cross_entropy_2d).reshape(self.shape + - [1]) - - def init_attr_type(self): - self.soft_label = False - - def init_dtype_type(self): - self.dtype = np.float64 - - def init_bs_class_num(self): - self.class_num = 10 - - -class TestCrossEntropyOp5(TestCrossEntropyOp): - """Test high rank tensor cross-entropy with vectorized soft labels. - """ - - def init_x(self): - self.shape = [4, 3] - self.ins_num = np.prod(np.array(self.shape)) - self.X_2d = randomize_probability(self.ins_num, - self.class_num).astype(self.dtype) - self.x = self.X_2d.reshape(self.shape + [self.class_num]) - - def init_label(self): - self.label_2d = np.random.uniform( - 0.1, 1.0, [self.ins_num, self.class_num]).astype(self.dtype) - self.label_2d /= self.label_2d.sum(axis=1, keepdims=True) - self.label = self.label_2d.reshape(self.shape + [self.class_num]) - - def get_cross_entropy(self): - cross_entropy_2d = (-self.label_2d * np.log(self.X_2d)).sum( - axis=1, keepdims=True).astype(self.dtype) - self.cross_entropy = np.array(cross_entropy_2d).reshape(self.shape + - [1]) - - def init_attr_type(self): - self.soft_label = True - - def init_dtype_type(self): - self.dtype = np.float32 - - def init_bs_class_num(self): - self.class_num = 37 - - def test_check_grad(self): - self.check_grad( - ["X"], "Y", max_relative_error=0.05, numeric_grad_delta=0.001) - - -class TestCrossEntropyOp6(TestCrossEntropyOp): - """Test high rank tensor cross-entropy with vectorized one-hot representation of labels. - """ - - def init_x(self): - self.shape = [4, 3, 2] - self.ins_num = np.prod(np.array(self.shape)) - self.X_2d = randomize_probability(self.ins_num, - self.class_num).astype(self.dtype) - self.x = self.X_2d.reshape(self.shape + [self.class_num]) - - def init_label(self): - self.label_index_2d = np.random.randint( - 0, self.class_num, (self.ins_num), dtype="int64") - label_2d = np.zeros(self.X_2d.shape) - label_2d[np.arange(self.ins_num), self.label_index_2d] = 1 - self.label = label_2d.reshape(self.shape + [self.class_num]).astype( - self.dtype) - - def get_cross_entropy(self): - cross_entropy_2d = np.asmatrix( - [[-np.log(self.X_2d[i][self.label_index_2d[i]])] - for i in range(self.X_2d.shape[0])]) - self.cross_entropy = np.array(cross_entropy_2d).reshape( - self.shape + [1]).astype(self.dtype) - - def init_attr_type(self): - self.soft_label = True - - def init_dtype_type(self): - self.dtype = np.float32 - - def init_bs_class_num(self): - self.class_num = 17 - - def test_check_grad(self): - self.check_grad( - ["X"], "Y", max_relative_error=0.05, numeric_grad_delta=0.001) - - -class TestCrossEntropyOp7(TestCrossEntropyOp): - """Test cross-entropy with ignore index. - """ - - def init_label(self): - self.label = np.random.randint( - 0, self.class_num, (self.batch_size, 1), dtype="int64") - - def get_cross_entropy(self): - self.cross_entropy = np.asmatrix( - [[-np.log(self.x[i][self.label[i][0]])] - if self.label[i][0] != self.ignore_index else [0] - for i in range(self.x.shape[0])]).astype(self.dtype) - - def init_attr_type(self): - self.soft_label = False - self.ignore_index = 3 - - def init_dtype_type(self): - self.dtype = np.float64 - - def init_bs_class_num(self): - self.batch_size = 30 - self.class_num = 10 - +from paddle.fluid.tests.unittests.test_cross_entropy_op import TestCrossEntropyOp, TestCrossEntropyOp2, TestCrossEntropyOp3, TestCrossEntropyOp4, TestCrossEntropyOp5, TestCrossEntropyOp6, TestCrossEntropyOp7 if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/ngraph/test_momentum_ngraph_op.py b/python/paddle/fluid/tests/unittests/ngraph/test_momentum_ngraph_op.py new file mode 100644 index 0000000000000000000000000000000000000000..2c3549d907f5f67abc0cbd448a492d95b8ae6c32 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/ngraph/test_momentum_ngraph_op.py @@ -0,0 +1,21 @@ +# 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. + +from __future__ import print_function + +import unittest +from paddle.fluid.tests.unittests.test_momentum_op import TestMomentumOp1, TestMomentumOp2, TestLarsMomentumOp, TestSparseMomentumOp, TestSparseMomentumOp2 + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py b/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py index 82aff18b728f45388cd747e3bce19c1c9d6f91cc..7cf3bf13d2072bac3bf7bd74760c56e7ac12b8a7 100644 --- a/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py +++ b/python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py @@ -40,6 +40,8 @@ class SimpleLSTMRNN(fluid.imperative.Layer): self._dropout = dropout self._input = None self._num_steps = num_steps + from paddle.fluid.layer_helper import LayerHelper + self._helper = LayerHelper('SimpleLSTMRNN', act="tanh") def _build_once(self, input_embedding, init_hidden=None, init_cell=None): self.weight_1_arr = [] @@ -50,17 +52,21 @@ class SimpleLSTMRNN(fluid.imperative.Layer): self.mask_array = [] for i in range(self._num_layers): - weight_1 = fluid.layers.create_parameter( + weight_1 = self._helper.create_parameter( + attr=fluid.ParamAttr( + initializer=fluid.initializer.UniformInitializer( + low=-self._init_scale, high=self._init_scale)), shape=[self._hidden_size * 2, self._hidden_size * 4], dtype="float32", - name="fc_weight1_" + str(i), default_initializer=fluid.initializer.UniformInitializer( low=-self._init_scale, high=self._init_scale)) self.weight_1_arr.append(weight_1) - bias_1 = fluid.layers.create_parameter( - [self._hidden_size * 4], + bias_1 = self._helper.create_parameter( + attr=fluid.ParamAttr( + initializer=fluid.initializer.UniformInitializer( + low=-self._init_scale, high=self._init_scale)), + shape=[self._hidden_size * 4], dtype="float32", - name="fc_bias1_" + str(i), default_initializer=fluid.initializer.Constant(0.0)) self.bias_arr.append(bias_1) @@ -137,6 +143,8 @@ class PtbModel(fluid.imperative.Layer): self.num_layers = num_layers self.num_steps = num_steps self.dropout = dropout + from paddle.fluid.layer_helper import LayerHelper + self._helper = LayerHelper('PtbModel', act="tanh") self.simple_lstm_rnn = SimpleLSTMRNN( hidden_size, num_steps, @@ -151,16 +159,16 @@ class PtbModel(fluid.imperative.Layer): name='embedding_para', initializer=fluid.initializer.UniformInitializer( low=-init_scale, high=init_scale))) - self.softmax_weight = fluid.layers.create_parameter( - [self.hidden_size, self.vocab_size], + self.softmax_weight = self._helper.create_parameter( + attr=fluid.ParamAttr(), + shape=[self.hidden_size, self.vocab_size], dtype="float32", - name="softmax_weight", default_initializer=fluid.initializer.UniformInitializer( low=-self.init_scale, high=self.init_scale)) - self.softmax_bias = fluid.layers.create_parameter( - [self.vocab_size], + self.softmax_bias = self._helper.create_parameter( + attr=fluid.ParamAttr(), + shape=[self.vocab_size], dtype="float32", - name='softmax_bias', default_initializer=fluid.initializer.UniformInitializer( low=-self.init_scale, high=self.init_scale)) @@ -256,7 +264,6 @@ class TestImperativePtbRnn(unittest.TestCase): with new_program_scope(): fluid.default_startup_program().random_seed = seed fluid.default_main_program().random_seed = seed - # TODO: marsyang1993 Change seed to ptb_model = PtbModel( hidden_size=hidden_size, vocab_size=vocab_size, diff --git a/python/paddle/fluid/tests/unittests/test_multiclass_nms_op.py b/python/paddle/fluid/tests/unittests/test_multiclass_nms_op.py index 8fc391a1ff2529460b038979c0c7d0a9d905a7e0..69e060341ed9dbb711f13f860e047e19f741b336 100644 --- a/python/paddle/fluid/tests/unittests/test_multiclass_nms_op.py +++ b/python/paddle/fluid/tests/unittests/test_multiclass_nms_op.py @@ -173,13 +173,16 @@ def lod_multiclass_nms(boxes, scores, background, score_threshold, normalized, shared=False) if nmsed_num == 0: - #lod.append(1) continue lod.append(nmsed_num) + tmp_det_out = [] for c, indices in nmsed_outs.items(): for idx in indices: xmin, ymin, xmax, ymax = box[idx, c, :] - det_outs.append([c, score[idx][c], xmin, ymin, xmax, ymax]) + tmp_det_out.append([c, score[idx][c], xmin, ymin, xmax, ymax]) + sorted_det_out = sorted( + tmp_det_out, key=lambda tup: tup[0], reverse=False) + det_outs.extend(sorted_det_out) if len(lod) == 0: lod.append(1) diff --git a/python/paddle/fluid/tests/unittests/test_optimizer.py b/python/paddle/fluid/tests/unittests/test_optimizer.py index 34c9b7e006950f1c10fb265ce903b1e836281de7..95ddc135b3da5bc144f64f20dab5dfd2b5bd3215 100644 --- a/python/paddle/fluid/tests/unittests/test_optimizer.py +++ b/python/paddle/fluid/tests/unittests/test_optimizer.py @@ -274,7 +274,7 @@ class TestAdagradOptimizer(unittest.TestCase): # Check init_program init_ops = init_program.global_block().ops - self.assertEqual(len(init_ops), 2) + self.assertEqual(len(init_ops), 3) self.assertEqual(init_ops[0].type, "fill_constant") self.assertAlmostEqual(init_ops[0].attr('value'), learning_rate) self.assertEqual(init_ops[1].type, "fill_constant") diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py new file mode 100644 index 0000000000000000000000000000000000000000..041c56fce11e6f6abb0a941a9e9c9ad1cb60ab42 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py @@ -0,0 +1,107 @@ +# Copyright (c) 2018 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. + +from __future__ import print_function + +import unittest + +import numpy as np +import os +os.environ['FLAGS_enable_parallel_graph'] = str(1) +import paddle.fluid.core as core +import os +import paddle.fluid as fluid +from parallel_executor_test_base import TestParallelExecutorBase + + +def simple_fc_net(use_feed): + img = fluid.layers.data(name='image', shape=[784], dtype='float32') + label = fluid.layers.data(name='label', shape=[1], dtype='int64') + hidden = img + for _ in range(4): + hidden = fluid.layers.fc( + hidden, + size=200, + act='tanh', + bias_attr=fluid.ParamAttr( + initializer=fluid.initializer.Constant(value=1.0))) + prediction = fluid.layers.fc(hidden, size=10, act='softmax') + loss = fluid.layers.cross_entropy(input=prediction, label=label) + loss = fluid.layers.mean(loss) + return loss + + +class TestMNIST(TestParallelExecutorBase): + @classmethod + def setUpClass(cls): + os.environ['CPU_NUM'] = str(4) + + def _init_data(self): + np.random.seed(5) + img = np.random.random(size=[32, 784]).astype(np.float32) + label = np.ones(shape=[32, 1], dtype='int64') + return img, label + + # simple_fc + def check_simple_fc_convergence(self, use_cuda, use_reduce=False): + if use_cuda and not core.is_compiled_with_cuda(): + return + + img, label = self._init_data() + + self.check_network_convergence( + simple_fc_net, + feed_dict={"image": img, + "label": label}, + use_cuda=use_cuda, + use_reduce=use_reduce) + + def test_simple_fc(self): + # use_cuda + self.check_simple_fc_convergence(True) + + def check_simple_fc_parallel_accuracy(self, use_cuda): + if use_cuda and not core.is_compiled_with_cuda(): + return + + img, label = self._init_data() + + single_first_loss, single_last_loss = self.check_network_convergence( + method=simple_fc_net, + seed=1, + feed_dict={"image": img, + "label": label}, + use_cuda=use_cuda, + use_parallel_executor=False) + parallel_first_loss, parallel_last_loss = self.check_network_convergence( + method=simple_fc_net, + seed=1, + feed_dict={"image": img, + "label": label}, + use_cuda=use_cuda, + use_parallel_executor=True) + + self.assertAlmostEquals( + np.mean(parallel_first_loss), + single_first_loss, + delta=1e-6, ) + self.assertAlmostEquals( + np.mean(parallel_last_loss), single_last_loss, delta=1e-6) + + def test_simple_fc_parallel_accuracy(self): + self.check_simple_fc_parallel_accuracy(True) + + +if __name__ == '__main__': + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_profiler.py b/python/paddle/fluid/tests/unittests/test_profiler.py index 7934164b84931f886967982ce0cb65c406bbf800..39d778b82a04f403bea030381ff220a68b1ff0ef 100644 --- a/python/paddle/fluid/tests/unittests/test_profiler.py +++ b/python/paddle/fluid/tests/unittests/test_profiler.py @@ -16,15 +16,19 @@ from __future__ import print_function import unittest import os +import tempfile import numpy as np import paddle.fluid as fluid import paddle.fluid.profiler as profiler import paddle.fluid.layers as layers import paddle.fluid.core as core +import paddle.fluid.proto.profiler.profiler_pb2 as profiler_pb2 class TestProfiler(unittest.TestCase): - def net_profiler(self, state, profile_path='/tmp/profile'): + def net_profiler(self, state, use_parallel_executor=False): + profile_path = os.path.join(tempfile.gettempdir(), "profile") + open(profile_path, "w").write("") startup_program = fluid.Program() main_program = fluid.Program() @@ -60,6 +64,11 @@ class TestProfiler(unittest.TestCase): place = fluid.CPUPlace() if state == 'CPU' else fluid.CUDAPlace(0) exe = fluid.Executor(place) exe.run(startup_program) + if use_parallel_executor: + pe = fluid.ParallelExecutor( + state != 'CPU', + loss_name=avg_cost.name, + main_program=main_program) pass_acc_calculator = fluid.average.WeightedAverage() with profiler.profiler(state, 'total', profile_path) as prof: @@ -69,6 +78,9 @@ class TestProfiler(unittest.TestCase): x = np.random.random((32, 784)).astype("float32") y = np.random.randint(0, 10, (32, 1)).astype("int64") + if use_parallel_executor: + pe.run(feed={'x': x, 'y': y}, fetch_list=[avg_cost.name]) + continue outs = exe.run(main_program, feed={'x': x, 'y': y}, @@ -77,21 +89,37 @@ class TestProfiler(unittest.TestCase): b_size = np.array(outs[2]) pass_acc_calculator.add(value=acc, weight=b_size) pass_acc = pass_acc_calculator.eval() + data = open(profile_path, 'rb').read() + self.assertGreater(len(data), 0) + profile_pb = profiler_pb2.Profile() + profile_pb.ParseFromString(data) + self.assertGreater(len(profile_pb.events), 0) + for event in profile_pb.events: + if event.type == profiler_pb2.Event.GPUKernel: + if not event.detail_info and not event.name.startswith("MEM"): + raise Exception( + "Kernel %s missing event. Has this kernel been recorded by RecordEvent?" + % event.name) + elif event.type == profiler_pb2.Event.CPU and ( + event.name.startswith("Driver API") or + event.name.startswith("Runtime API")): + print("Warning: unregister", event.name) def test_cpu_profiler(self): self.net_profiler('CPU') + self.net_profiler('CPU', use_parallel_executor=True) @unittest.skipIf(not core.is_compiled_with_cuda(), "profiler is enabled only with GPU") def test_cuda_profiler(self): self.net_profiler('GPU') + self.net_profiler('GPU', use_parallel_executor=True) @unittest.skipIf(not core.is_compiled_with_cuda(), "profiler is enabled only with GPU") def test_all_profiler(self): - self.net_profiler('All', '/tmp/profile_out') - with open('/tmp/profile_out', 'rb') as f: - self.assertGreater(len(f.read()), 0) + self.net_profiler('All') + self.net_profiler('All', use_parallel_executor=True) if __name__ == '__main__': diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py index a3293afbbd7cef8470c808e98ae88a05f2e492f4..eb54068650e8b3f4e64317778e2ad7c7aa7fe1b2 100644 --- a/python/paddle/fluid/transpiler/distribute_transpiler.py +++ b/python/paddle/fluid/transpiler/distribute_transpiler.py @@ -1020,7 +1020,11 @@ class DistributeTranspiler(object): skip_dim0 = 0 slice_vars = self.param_var_mapping[orig_var_name] - orig_dim1_flatten = reduce(lambda x, y: x * y, slice_vars[0].shape[1:]) + orig_dim1_flatten = 1 + + if len(slice_vars[0].shape) >= 2: + orig_dim1_flatten = reduce(lambda x, y: x * y, + slice_vars[0].shape[1:]) for slice_var in slice_vars[:block_idx]: skip_dim0 += slice_var.shape[0] diff --git a/python/requirements.txt b/python/requirements.txt index 6cbda1db545957b8e7b943366f9b954ff1dfdc77..36bd5d4261cc7aa78d26b8c8ddfd87abd4f4e2e2 100644 --- a/python/requirements.txt +++ b/python/requirements.txt @@ -1,6 +1,6 @@ requests==2.9.2 numpy>=1.12 -protobuf>=3.6 +protobuf>=3.1.0 recordio>=0.1.0 matplotlib==2.2.3 # TODO: let python3 paddlepaddle package use latest matplotlib rarfile diff --git a/tools/manylinux1/build_all.sh b/tools/manylinux1/build_all.sh index 097bedb5265d00f8aa362bb0272af633c97192ba..caf21722158b749ffe8d026a98a8b7d015e555d8 100755 --- a/tools/manylinux1/build_all.sh +++ b/tools/manylinux1/build_all.sh @@ -24,3 +24,8 @@ sed 's//9.0-cudnn7-devel-centos6/g' Dockerfile.x64 | \ sed 's//NVCC_GENCODE="-gencode=arch=compute_35,code=sm_35 -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_60,code=compute_60 -gencode=arch=compute_61,code=sm_61 -gencode=arch=compute_62,code=sm_62 -gencode=arch=compute_70,code=sm_70"/g'> Dockerfile.tmp docker build -t ${REPO}/paddle_manylinux_devel:cuda9.0_cudnn7 -f Dockerfile.tmp . docker push ${REPO}/paddle_manylinux_devel:cuda9.0_cudnn7 + +sed 's//10.0-devel-centos6/g' Dockerfile.x64 | \ +sed 's//NVCC_GENCODE="-gencode=arch=compute_35,code=sm_35 -gencode=arch=compute_50,code=sm_50 -gencode=arch=compute_52,code=sm_52 -gencode=arch=compute_60,code=sm_60 -gencode=arch=compute_60,code=compute_60 -gencode=arch=compute_61,code=sm_61 -gencode=arch=compute_62,code=sm_62 -gencode=arch=compute_70,code=sm_70 -gencode=arch=compute_75,code=sm_75"/g'> Dockerfile.tmp +docker build -t ${REPO}/paddle_manylinux_devel:cuda10.0_cudnn7 -f Dockerfile.tmp . +docker push ${REPO}/paddle_manylinux_devel:cuda10.0_cudnn7 diff --git a/tools/manylinux1/build_scripts/build.sh b/tools/manylinux1/build_scripts/build.sh index 5b676c024317596832870232dccb33895cae0c3e..1b0059a8c69fca93ecbf1db570a6092ca5c908b1 100644 --- a/tools/manylinux1/build_scripts/build.sh +++ b/tools/manylinux1/build_scripts/build.sh @@ -107,11 +107,13 @@ curl-config --features rm -rf /usr/local/ssl # Install patchelf (latest with unreleased bug fixes) -curl -sLO https://nixos.org/releases/patchelf/patchelf-0.9/patchelf-0.9.tar.gz -check_sha256sum patchelf-0.9.tar.gz $PATCHELF_HASH -tar -xzf patchelf-0.9.tar.gz -(cd patchelf-0.9 && ./configure && make && make install) -rm -rf patchelf-0.9.tar.gz patchelf-0.9 +# FIXME(typhoonzero): restore this when the link is fixed. +# curl -sLO http://nipy.bic.berkeley.edu/manylinux/patchelf-0.9njs2.tar.gz +# check_sha256sum patchelf-0.9njs2.tar.gz $PATCHELF_HASH +# tar -xzf patchelf-0.9njs2.tar.gz +# (cd patchelf-0.9njs2 && ./configure && make && make install) +# rm -rf patchelf-0.9njs2.tar.gz patchelf-0.9njs2 +yum install -y patchelf # Install latest pypi release of auditwheel LD_LIBRARY_PATH="${ORIGINAL_LD_LIBRARY_PATH}:$(dirname ${PY35_BIN})/lib" $PY35_BIN/pip install auditwheel diff --git a/tools/manylinux1/build_scripts/build_utils.sh b/tools/manylinux1/build_scripts/build_utils.sh index 48cce15a145138376177731009c61157d1d4d0c8..083101249cd8560f63c95b3fe2aef610b01dd6ac 100755 --- a/tools/manylinux1/build_scripts/build_utils.sh +++ b/tools/manylinux1/build_scripts/build_utils.sh @@ -87,6 +87,8 @@ function do_cpython_build { # NOTE Make libpython shared library visible to python calls below LD_LIBRARY_PATH="${prefix}/lib" ${prefix}/bin/python get-pip.py LD_LIBRARY_PATH="${prefix}/lib" ${prefix}/bin/pip install wheel + cd / + ls ${MY_DIR} local abi_tag=$(LD_LIBRARY_PATH="${prefix}/lib" ${prefix}/bin/python ${MY_DIR}/python-tag-abi-tag.py) ln -s ${prefix} /opt/python/${abi_tag} } diff --git a/tools/timeline.py b/tools/timeline.py index f850476831d84787bf5cc7c7f7c91ff9dd6a2d5b..ebadb29bdbe00caeb3fb16a95b7dde6f418db155 100644 --- a/tools/timeline.py +++ b/tools/timeline.py @@ -131,8 +131,12 @@ class Timeline(object): if (k, event.device_id, "CPU") not in self._devices: pid = self._allocate_pid() self._devices[(k, event.device_id, "CPU")] = pid - self._chrome_trace.emit_pid("%s:cpu:block:%d" % - (k, event.device_id), pid) + # -1 device id represents CUDA api call + if event.device_id == -1: + self._chrome_trace.emit_pid("%s:cuda_api" % k, pid) + else: + self._chrome_trace.emit_pid( + "%s:cpu:block:%d" % (k, event.device_id), pid) elif event.type == profiler_pb2.Event.GPUKernel: if (k, event.device_id, "GPUKernel") not in self._devices: pid = self._allocate_pid() @@ -150,7 +154,9 @@ class Timeline(object): pid = self._devices[(k, event.device_id, type)] args = {'name': event.name} if event.memcopy.bytes > 0: - args = {'mem_bytes': event.memcopy.bytes} + args['mem_bytes'] = event.memcopy.bytes + if event.detail_info: + args['detail_info'] = event.detail_info # TODO(panyx0718): Chrome tracing only handles ms. However, some # ops takes micro-seconds. Hence, we keep the ns here. self._chrome_trace.emit_region( @@ -173,7 +179,7 @@ if args.timeline_path: profile_paths = profile_path.split(',') profile_dict = dict() if len(profile_paths) == 1: - with open(profile_path, 'r') as f: + with open(profile_path, 'rb') as f: profile_s = f.read() profile_pb = profiler_pb2.Profile() profile_pb.ParseFromString(profile_s) @@ -181,7 +187,7 @@ if len(profile_paths) == 1: else: for profile_path in profile_paths: k, v = profile_path.split('=') - with open(v, 'r') as f: + with open(v, 'rb') as f: profile_s = f.read() profile_pb = profiler_pb2.Profile() profile_pb.ParseFromString(profile_s)