未验证 提交 d3aed98d 编写于 作者: D dzhwinter 提交者: GitHub

Merge pull request #14320 from wopeizl/windows/online

Windows/online
......@@ -26,6 +26,11 @@ message(STATUS "C compiler: ${CMAKE_C_COMPILER}, version: "
"${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}")
if(WIN32)
set(CMAKE_STATIC_LIBRARY_PREFIX lib)
add_definitions("/DGOOGLE_GLOG_DLL_DECL=")
set(CMAKE_C_FLAGS_DEBUG "${CMAKE_C_FLAGS_DEBUG} /bigobj /MTd")
set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} /bigobj /MT")
set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} /bigobj /MTd")
set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /bigobj /MT")
endif(WIN32)
if(NOT CMAKE_CROSSCOMPILING)
......
......@@ -157,6 +157,9 @@ 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)
endif(NOT WITH_DSO)
# setting nvcc arch flags
......@@ -196,10 +199,12 @@ elseif(CMAKE_BUILD_TYPE STREQUAL "MinSizeRel")
list(APPEND CUDA_NVCC_FLAGS ${CMAKE_CXX_FLAGS_RELEASE})
endif()
else(NOT WIN32)
if(CMAKE_BUILD_TYPE STREQUAL "Release")
if(CMAKE_BUILD_TYPE STREQUAL "Debug")
list(APPEND CUDA_NVCC_FLAGS "-g -G")
elseif(CMAKE_BUILD_TYPE STREQUAL "Release")
list(APPEND CUDA_NVCC_FLAGS "-O3 -DNDEBUG")
else()
message(FATAL "Windows only support Release build now. Please set visual studio build type to Release, x64 build.")
message(FATAL "Windows only support Release or Debug build now. Please set visual studio build type to Release/Debug, x64 build.")
endif()
endif(NOT WIN32)
......
......@@ -2,7 +2,12 @@ if(NOT WITH_GPU)
return()
endif()
set(CUDNN_ROOT "/usr" CACHE PATH "CUDNN ROOT")
if(WIN32)
set(CUDNN_ROOT ${CUDA_TOOLKIT_ROOT_DIR})
else(WIN32)
set(CUDNN_ROOT "/usr" CACHE PATH "CUDNN ROOT")
endif(WIN32)
find_path(CUDNN_INCLUDE_DIR cudnn.h
PATHS ${CUDNN_ROOT} ${CUDNN_ROOT}/include
$ENV{CUDNN_ROOT} $ENV{CUDNN_ROOT}/include ${CUDA_TOOLKIT_INCLUDE}
......
......@@ -28,34 +28,28 @@ if((NOT DEFINED BOOST_TAR) OR (NOT DEFINED BOOST_URL))
set(BOOST_TAR "boost_1_41_0" CACHE STRING "" FORCE)
set(BOOST_URL "http://paddlepaddledeps.cdn.bcebos.com/${BOOST_TAR}.tar.gz" CACHE STRING "" FORCE)
endif()
IF (WIN32)
MESSAGE(WARNING, "In windows, boost can not be downloaded automaticlly, please build it manually and put it at " ${THIRD_PARTY_PATH}install/boost)
else()
MESSAGE(STATUS "BOOST_TAR: ${BOOST_TAR}, BOOST_URL: ${BOOST_URL}")
ENDIF(WIN32)
MESSAGE(STATUS "BOOST_TAR: ${BOOST_TAR}, BOOST_URL: ${BOOST_URL}")
set(BOOST_SOURCES_DIR ${THIRD_PARTY_PATH}/boost)
set(BOOST_DOWNLOAD_DIR "${BOOST_SOURCES_DIR}/src/${BOOST_PROJECT}")
set(BOOST_INCLUDE_DIR "${BOOST_DOWNLOAD_DIR}/${BOOST_TAR}" CACHE PATH "boost include directory." FORCE)
set_directory_properties(PROPERTIES CLEAN_NO_CUSTOM 1)
set(BOOST_INCLUDE_DIR "${BOOST_DOWNLOAD_DIR}" CACHE PATH "boost include directory." FORCE)
set_directory_properties(PROPERTIES CLEAN_NO_CUSTOM 1)
include_directories(${BOOST_INCLUDE_DIR})
if (NOT WIN32)
ExternalProject_Add(
${BOOST_PROJECT}
${EXTERNAL_PROJECT_LOG_ARGS}
DOWNLOAD_DIR ${BOOST_DOWNLOAD_DIR}
DOWNLOAD_COMMAND wget --no-check-certificate ${BOOST_URL} -c -q -O ${BOOST_TAR}.tar.gz
&& tar zxf ${BOOST_TAR}.tar.gz
URL ${BOOST_URL}
DOWNLOAD_NO_PROGRESS 1
PREFIX ${BOOST_SOURCES_DIR}
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
INSTALL_COMMAND ""
UPDATE_COMMAND ""
)
endif(NOT WIN32)
)
if (${CMAKE_VERSION} VERSION_LESS "3.3.0" OR NOT WIN32)
set(dummyfile ${CMAKE_CURRENT_BINARY_DIR}/boost_dummy.c)
......
......@@ -35,7 +35,12 @@ ExternalProject_Add(
CMAKE_ARGS -DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}
-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER}
-DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}
-DCMAKE_CXX_FLAGS_RELEASE=${CMAKE_CXX_FLAGS_RELEASE}
-DCMAKE_CXX_FLAGS_DEBUG=${CMAKE_CXX_FLAGS_DEBUG}
-DCMAKE_C_FLAGS=${CMAKE_C_FLAGS}
-DCMAKE_C_FLAGS_DEBUG=${CMAKE_C_FLAGS_DEBUG}
-DCMAKE_C_FLAGS_RELEASE=${CMAKE_C_FLAGS_RELEASE}
-DBUILD_STATIC_LIBS=ON
-DCMAKE_INSTALL_PREFIX=${GFLAGS_INSTALL_DIR}
-DCMAKE_POSITION_INDEPENDENT_CODE=ON
-DBUILD_TESTING=OFF
......@@ -48,8 +53,8 @@ ExternalProject_Add(
IF(WIN32)
IF(NOT EXISTS "${GFLAGS_INSTALL_DIR}/lib/libgflags.lib")
add_custom_command(TARGET extern_gflags POST_BUILD
COMMAND cmake -E rename ${GFLAGS_INSTALL_DIR}/lib/gflags_static.lib ${GFLAGS_INSTALL_DIR}/lib/libgflags.lib
)
COMMAND cmake -E copy ${GFLAGS_INSTALL_DIR}/lib/gflags_static.lib ${GFLAGS_INSTALL_DIR}/lib/libgflags.lib
)
ENDIF()
ENDIF(WIN32)
ADD_LIBRARY(gflags STATIC IMPORTED GLOBAL)
......
......@@ -46,7 +46,11 @@ ExternalProject_Add(
CMAKE_ARGS -DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}
-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER}
-DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}
-DCMAKE_CXX_FLAGS_RELEASE=${CMAKE_CXX_FLAGS_RELEASE}
-DCMAKE_CXX_FLAGS_DEBUG=${CMAKE_CXX_FLAGS_DEBUG}
-DCMAKE_C_FLAGS=${CMAKE_C_FLAGS}
-DCMAKE_C_FLAGS_DEBUG=${CMAKE_C_FLAGS_DEBUG}
-DCMAKE_C_FLAGS_RELEASE=${CMAKE_C_FLAGS_RELEASE}
-DCMAKE_INSTALL_PREFIX=${GLOG_INSTALL_DIR}
-DCMAKE_INSTALL_LIBDIR=${GLOG_INSTALL_DIR}/lib
-DCMAKE_POSITION_INDEPENDENT_CODE=ON
......@@ -63,7 +67,7 @@ ExternalProject_Add(
IF(WIN32)
IF(NOT EXISTS "${GLOG_INSTALL_DIR}/lib/libglog.lib")
add_custom_command(TARGET extern_glog POST_BUILD
COMMAND cmake -E rename ${GLOG_INSTALL_DIR}/lib/glog.lib ${GLOG_INSTALL_DIR}/lib/libglog.lib
COMMAND cmake -E copy ${GLOG_INSTALL_DIR}/lib/glog.lib ${GLOG_INSTALL_DIR}/lib/libglog.lib
)
ENDIF()
ENDIF(WIN32)
......
......@@ -17,12 +17,8 @@ IF(USE_EIGEN_FOR_BLAS)
ENDIF(USE_EIGEN_FOR_BLAS)
INCLUDE(cblas)
# IF(WIN32 AND NOT ${CBLAS_FOUND})
IF(NOT ${CBLAS_FOUND})
INCLUDE(ExternalProject)
SET(CBLAS_SOURCES_DIR ${THIRD_PARTY_PATH}/openblas)
......@@ -34,6 +30,7 @@ IF(NOT ${CBLAS_FOUND})
CACHE FILEPATH "openblas library." FORCE)
ADD_DEFINITIONS(-DPADDLE_USE_OPENBLAS)
IF (WIN32)
SET(CBLAS_FOUND true)
MESSAGE(WARNING, "In windows, openblas only support msvc build, please build it manually and put it at " ${CBLAS_INSTALL_DIR})
......
......@@ -140,7 +140,6 @@ endmacro()
set(PROTOBUF_ROOT "" CACHE PATH "Folder contains protobuf")
IF (WIN32)
SET(PROTOBUF_ROOT ${THIRD_PARTY_PATH}/install/protobuf)
MESSAGE(WARNING, "In windows, protobuf only support msvc build, please build it manually and put it at " ${PROTOBUF_ROOT})
ENDIF(WIN32)
if (NOT "${PROTOBUF_ROOT}" STREQUAL "")
......@@ -188,13 +187,20 @@ FUNCTION(build_protobuf TARGET_NAME BUILD_FOR_HOST)
SET(OPTIONAL_ARGS
"-DCMAKE_CXX_COMPILER=${CMAKE_CXX_COMPILER}"
"-DCMAKE_C_COMPILER=${CMAKE_C_COMPILER}"
"-DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}"
"-DCMAKE_C_FLAGS=${CMAKE_C_FLAGS}"
"-DCMAKE_C_FLAGS_DEBUG=${CMAKE_C_FLAGS_DEBUG}"
"-DCMAKE_C_FLAGS_RELEASE=${CMAKE_C_FLAGS_RELEASE}"
"-DCMAKE_CXX_FLAGS=${CMAKE_CXX_FLAGS}"
"-DCMAKE_CXX_FLAGS_RELEASE=${CMAKE_CXX_FLAGS_RELEASE}"
"-DCMAKE_CXX_FLAGS_DEBUG=${CMAKE_CXX_FLAGS_DEBUG}"
"-Dprotobuf_WITH_ZLIB=ON"
"-DZLIB_ROOT:FILEPATH=${ZLIB_ROOT}"
${EXTERNAL_OPTIONAL_ARGS})
SET(OPTIONAL_CACHE_ARGS "-DZLIB_ROOT:STRING=${ZLIB_ROOT}")
ENDIF()
IF(WIN32)
SET(OPTIONAL_ARGS ${OPTIONAL_ARGS} "-DCMAKE_GENERATOR_PLATFORM=x64")
ENDIF()
SET(PROTOBUF_REPO "https://github.com/google/protobuf.git")
SET(PROTOBUF_TAG "9f75c5aa851cd877fb0d93ccc31b8567a6706546")
......
......@@ -21,6 +21,48 @@ INCLUDE(python_module)
FIND_PACKAGE(PythonInterp ${PY_VERSION})
FIND_PACKAGE(PythonLibs ${PY_VERSION})
if(WIN32)
execute_process(COMMAND "${PYTHON_EXECUTABLE}" "-c"
"from distutils import sysconfig as s;import sys;import struct;
print(sys.prefix);
print(s.get_config_var('LDVERSION') or s.get_config_var('VERSION'));
"
RESULT_VARIABLE _PYTHON_SUCCESS
OUTPUT_VARIABLE _PYTHON_VALUES
ERROR_VARIABLE _PYTHON_ERROR_VALUE)
if(NOT _PYTHON_SUCCESS MATCHES 0)
set(PYTHONLIBS_FOUND FALSE)
return()
endif()
# Convert the process output into a list
string(REGEX REPLACE ";" "\\\\;" _PYTHON_VALUES ${_PYTHON_VALUES})
string(REGEX REPLACE "\n" ";" _PYTHON_VALUES ${_PYTHON_VALUES})
list(GET _PYTHON_VALUES 0 PYTHON_PREFIX)
list(GET _PYTHON_VALUES 1 PYTHON_LIBRARY_SUFFIX)
# Make sure all directory separators are '/'
string(REGEX REPLACE "\\\\" "/" PYTHON_PREFIX ${PYTHON_PREFIX})
set(PYTHON_LIBRARY
"${PYTHON_PREFIX}/libs/Python${PYTHON_LIBRARY_SUFFIX}.lib")
# when run in a venv, PYTHON_PREFIX points to it. But the libraries remain in the
# original python installation. They may be found relative to PYTHON_INCLUDE_DIR.
if(NOT EXISTS "${PYTHON_LIBRARY}")
get_filename_component(_PYTHON_ROOT ${PYTHON_INCLUDE_DIR} DIRECTORY)
set(PYTHON_LIBRARY
"${_PYTHON_ROOT}/libs/Python${PYTHON_LIBRARY_SUFFIX}.lib")
endif()
# raise an error if the python libs are still not found.
if(NOT EXISTS "${PYTHON_LIBRARY}")
message(FATAL_ERROR "Python libraries not found")
endif()
SET(PYTHON_LIBRARIES "${PYTHON_LIBRARY}")
endif(WIN32)
# Fixme: Maybe find a static library. Get SHARED/STATIC by FIND_PACKAGE.
ADD_LIBRARY(python SHARED IMPORTED GLOBAL)
SET_PROPERTY(TARGET python PROPERTY IMPORTED_LOCATION ${PYTHON_LIBRARIES})
......
......@@ -14,23 +14,52 @@ ELSE()
ENDIF(APPLE)
ENDIF()
ExternalProject_Add(
extern_xxhash
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/Cyan4973/xxHash"
GIT_TAG "v0.6.5"
PREFIX ${XXHASH_SOURCE_DIR}
DOWNLOAD_NAME "xxhash"
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_IN_SOURCE 1
PATCH_COMMAND
BUILD_COMMAND ${BUILD_CMD}
INSTALL_COMMAND export PREFIX=${XXHASH_INSTALL_DIR}/ && make install
TEST_COMMAND ""
)
if(WIN32)
ExternalProject_Add(
extern_xxhash
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/Cyan4973/xxHash"
GIT_TAG "v0.6.5"
PREFIX ${XXHASH_SOURCE_DIR}
DOWNLOAD_NAME "xxhash"
UPDATE_COMMAND ""
BUILD_IN_SOURCE 1
PATCH_COMMAND
CONFIGURE_COMMAND
${CMAKE_COMMAND} ${XXHASH_SOURCE_DIR}/src/extern_xxhash/cmake_unofficial
-DCMAKE_INSTALL_PREFIX:PATH=${XXHASH_INSTALL_DIR}
-DCMAKE_BUILD_TYPE:STRING=${CMAKE_BUILD_TYPE}
-DCMAKE_VERBOSE_MAKEFILE:BOOL=OFF
-DCMAKE_POSITION_INDEPENDENT_CODE:BOOL=ON
-DBUILD_XXHSUM=OFF
-DCMAKE_GENERATOR_PLATFORM=x64
-DBUILD_SHARED_LIBS=OFF
${OPTIONAL_CACHE_ARGS}
TEST_COMMAND ""
)
else()
ExternalProject_Add(
extern_xxhash
${EXTERNAL_PROJECT_LOG_ARGS}
GIT_REPOSITORY "https://github.com/Cyan4973/xxHash"
GIT_TAG "v0.6.5"
PREFIX ${XXHASH_SOURCE_DIR}
DOWNLOAD_NAME "xxhash"
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_IN_SOURCE 1
PATCH_COMMAND
BUILD_COMMAND ${BUILD_CMD}
INSTALL_COMMAND export PREFIX=${XXHASH_INSTALL_DIR}/ && make install
TEST_COMMAND ""
)
endif()
set(XXHASH_LIBRARIES "${XXHASH_INSTALL_DIR}/lib/libxxhash.a")
if (WIN32)
set(XXHASH_LIBRARIES "${XXHASH_INSTALL_DIR}/lib/xxhash.lib")
else()
set(XXHASH_LIBRARIES "${XXHASH_INSTALL_DIR}/lib/libxxhash.a")
endif ()
INCLUDE_DIRECTORIES(${XXHASH_INCLUDE_DIR})
add_library(xxhash STATIC IMPORTED GLOBAL)
......
......@@ -266,7 +266,11 @@ function(cc_library TARGET_NAME)
if("${cc_library_DEPS};" MATCHES "python;")
list(REMOVE_ITEM cc_library_DEPS python)
add_dependencies(${TARGET_NAME} python)
target_link_libraries(${TARGET_NAME} "-Wl,-undefined,dynamic_lookup")
if(WIN32)
target_link_libraries(${TARGET_NAME} ${PYTHON_LIBRARIES})
else()
target_link_libraries(${TARGET_NAME} "-Wl,-undefined,dynamic_lookup")
endif(WIN32)
endif()
target_link_libraries(${TARGET_NAME} ${cc_library_DEPS})
add_dependencies(${TARGET_NAME} ${cc_library_DEPS})
......@@ -288,6 +292,45 @@ function(cc_library TARGET_NAME)
endif(cc_library_SRCS)
endfunction(cc_library)
# The link operation under windows may exceeds the maximum characters limit, simply break the link command
# into multiple link opeartion can fix that, say
# original:
# lib /out:target.lib a.lib b.lib c.lib d.lib
# after:
# 1. lib /out:dummy_lib_1.lib a.lib b.lib
# 2. lib /out:dummy_lib_2.lib c.lib d.lib
# 1. lib /out:target.lib dummy_lib_1.lib dummy_lib_2.lib
function(sep_library TARGET_NAME)
set(options STATIC static SHARED shared)
set(oneValueArgs "")
set(multiValueArgs SRCS DEPS)
cmake_parse_arguments(sep_library "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
set(dummy_index 1)
set(dummy_offset 1)
# the dummy target would be consisted of limit size libraries
set(dummy_limit 50)
list(LENGTH sep_library_DEPS sep_all_len)
foreach(v ${sep_library_DEPS})
list(APPEND dummy_list ${v})
list(LENGTH dummy_list listlen )
if ((${listlen} GREATER ${dummy_limit}) OR (${dummy_offset} EQUAL ${sep_all_len}))
message("create dummy library ${TARGET_NAME}_dummy_lib_${dummy_index} for ${TARGET_NAME}")
cc_library(${TARGET_NAME}_dummy_lib_${dummy_index} STATIC DEPS ${dummy_list})
foreach(i ${dummy_list})
list(REMOVE_AT dummy_list 0)
endforeach()
list(APPEND ${TARGET_NAME}_dummy_list ${TARGET_NAME}_dummy_lib_${dummy_index})
MATH(EXPR dummy_index "${dummy_index}+1")
endif()
MATH(EXPR dummy_offset "${dummy_offset}+1")
endforeach()
if(${sep_library_SHARED})
cc_library(${TARGET_NAME} SHARED SRCS ${sep_library_SRCS} DEPS ${${TARGET_NAME}_dummy_list})
else(${sep_library_SHARED})
cc_library(${TARGET_NAME} STATIC SRCS ${sep_library_SRCS} DEPS ${${TARGET_NAME}_dummy_list})
endif(${sep_library_SHARED})
endfunction(sep_library)
function(cc_binary TARGET_NAME)
set(options "")
set(oneValueArgs "")
......
......@@ -22,144 +22,165 @@ function(copy TARGET)
list(LENGTH copy_lib_SRCS copy_lib_SRCS_len)
list(LENGTH copy_lib_DSTS copy_lib_DSTS_len)
if(NOT ${copy_lib_SRCS_len} EQUAL ${copy_lib_DSTS_len})
if (NOT ${copy_lib_SRCS_len} EQUAL ${copy_lib_DSTS_len})
message(FATAL_ERROR "${TARGET} source numbers are not equal to destination numbers")
endif()
endif ()
math(EXPR len "${copy_lib_SRCS_len} - 1")
add_custom_target(${TARGET} DEPENDS ${copy_lib_DEPS})
foreach(index RANGE ${len})
foreach (index RANGE ${len})
list(GET copy_lib_SRCS ${index} src)
list(GET copy_lib_DSTS ${index} dst)
add_custom_command(TARGET ${TARGET} PRE_BUILD
COMMAND mkdir -p "${dst}"
COMMAND cp -r "${src}" "${dst}"
COMMENT "copying ${src} -> ${dst}")
endforeach()
if (WIN32)
# windows cmd shell will not expand wildcard automatically.
# below expand the files,libs and copy them by rules.
file(GLOB header_files ${src} "*.h")
file(GLOB static_lib_files ${src} "*.lib")
file(GLOB dll_lib_files ${src} "*.dll")
set(src_files ${header_files} ${static_lib_files} ${dll_lib_files})
if (NOT "${src_files}" STREQUAL "")
list(REMOVE_DUPLICATES src_files)
endif ()
add_custom_command(TARGET ${TARGET} PRE_BUILD
COMMAND ${CMAKE_COMMAND} -E make_directory "${dst}"
)
foreach (src_file ${src_files})
add_custom_command(TARGET ${TARGET} PRE_BUILD
COMMAND ${CMAKE_COMMAND} -E copy "${src_file}" "${dst}"
COMMENT "copying ${src_file} -> ${dst}")
endforeach ()
else (WIN32) # not windows
add_custom_command(TARGET ${TARGET} PRE_BUILD
COMMAND mkdir -p "${dst}"
COMMAND cp -r "${src}" "${dst}"
COMMENT "copying ${src} -> ${dst}")
endif (WIN32) # not windows
endforeach ()
endfunction()
# third party
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/eigen3")
copy(eigen3_lib
SRCS ${EIGEN_INCLUDE_DIR}/Eigen/Core ${EIGEN_INCLUDE_DIR}/Eigen/src ${EIGEN_INCLUDE_DIR}/unsupported/Eigen
DSTS ${dst_dir}/Eigen ${dst_dir}/Eigen ${dst_dir}/unsupported
DEPS eigen3
)
SRCS ${EIGEN_INCLUDE_DIR}/Eigen/Core ${EIGEN_INCLUDE_DIR}/Eigen/src ${EIGEN_INCLUDE_DIR}/unsupported/Eigen
DSTS ${dst_dir}/Eigen ${dst_dir}/Eigen ${dst_dir}/unsupported
DEPS eigen3
)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/gflags")
copy(gflags_lib
SRCS ${GFLAGS_INCLUDE_DIR} ${GFLAGS_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS gflags
)
SRCS ${GFLAGS_INCLUDE_DIR} ${GFLAGS_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS gflags
)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/glog")
copy(glog_lib
SRCS ${GLOG_INCLUDE_DIR} ${GLOG_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS glog
)
SRCS ${GLOG_INCLUDE_DIR} ${GLOG_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS glog
)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/boost/")
copy(boost_lib
SRCS ${BOOST_INCLUDE_DIR}/boost
DSTS ${dst_dir}
DEPS boost
)
SRCS ${BOOST_INCLUDE_DIR}/boost
DSTS ${dst_dir}
DEPS boost
)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/xxhash")
copy(xxhash_lib
SRCS ${XXHASH_INCLUDE_DIR} ${XXHASH_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS xxhash
)
SRCS ${XXHASH_INCLUDE_DIR} ${XXHASH_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS xxhash
)
if(NOT PROTOBUF_FOUND)
if (NOT PROTOBUF_FOUND)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/protobuf")
copy(protobuf_lib
SRCS ${PROTOBUF_INCLUDE_DIR} ${PROTOBUF_LIBRARY}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS extern_protobuf
)
endif()
SRCS ${PROTOBUF_INCLUDE_DIR} ${PROTOBUF_LIBRARY}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS extern_protobuf
)
endif ()
if(NOT CBLAS_FOUND)
if (NOT CBLAS_FOUND)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/openblas")
copy(openblas_lib
SRCS ${CBLAS_INSTALL_DIR}/lib ${CBLAS_INSTALL_DIR}/include
DSTS ${dst_dir} ${dst_dir}
DEPS extern_openblas
)
SRCS ${CBLAS_INSTALL_DIR}/lib ${CBLAS_INSTALL_DIR}/include
DSTS ${dst_dir} ${dst_dir}
DEPS extern_openblas
)
elseif (WITH_MKLML)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/mklml")
copy(mklml_lib
SRCS ${MKLML_LIB} ${MKLML_IOMP_LIB} ${MKLML_INC_DIR}
DSTS ${dst_dir}/lib ${dst_dir}/lib ${dst_dir}
DEPS mklml
)
endif()
if(WITH_MKLDNN)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/mkldnn")
copy(mkldnn_lib
SRCS ${MKLDNN_INC_DIR} ${MKLDNN_SHARED_LIB}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS mkldnn
)
endif()
SRCS ${MKLML_LIB} ${MKLML_IOMP_LIB} ${MKLML_INC_DIR}
DSTS ${dst_dir}/lib ${dst_dir}/lib ${dst_dir}
DEPS mklml
)
endif ()
if (WITH_MKLDNN)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/mkldnn")
copy(mkldnn_lib
SRCS ${MKLDNN_INC_DIR} ${MKLDNN_SHARED_LIB}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS mkldnn
)
endif ()
if (NOT WIN32)
if(NOT MOBILE_INFERENCE AND NOT RPI)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/snappy")
copy(snappy_lib
SRCS ${SNAPPY_INCLUDE_DIR} ${SNAPPY_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS snappy)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/snappystream")
copy(snappystream_lib
SRCS ${SNAPPYSTREAM_INCLUDE_DIR} ${SNAPPYSTREAM_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS snappystream)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/zlib")
copy(zlib_lib
SRCS ${ZLIB_INCLUDE_DIR} ${ZLIB_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS zlib)
endif()
endif(NOT WIN32)
if (NOT MOBILE_INFERENCE AND NOT RPI)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/snappy")
copy(snappy_lib
SRCS ${SNAPPY_INCLUDE_DIR} ${SNAPPY_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS snappy)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/snappystream")
copy(snappystream_lib
SRCS ${SNAPPYSTREAM_INCLUDE_DIR} ${SNAPPYSTREAM_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS snappystream)
set(dst_dir "${FLUID_INSTALL_DIR}/third_party/install/zlib")
copy(zlib_lib
SRCS ${ZLIB_INCLUDE_DIR} ${ZLIB_LIBRARIES}
DSTS ${dst_dir} ${dst_dir}/lib
DEPS zlib)
endif ()
endif (NOT WIN32)
# paddle fluid module
set(src_dir "${PADDLE_SOURCE_DIR}/paddle/fluid")
set(dst_dir "${FLUID_INSTALL_DIR}/paddle/fluid")
set(module "framework")
if (NOT WIN32)
set(framework_lib_deps framework_py_proto)
endif(NOT WIN32)
set(framework_lib_deps framework_py_proto)
endif (NOT WIN32)
copy(framework_lib DEPS ${framework_lib_deps}
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/details/*.h ${PADDLE_BINARY_DIR}/paddle/fluid/framework/framework.pb.h
${src_dir}/${module}/ir/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/details ${dst_dir}/${module} ${dst_dir}/${module}/ir
)
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/details/*.h ${PADDLE_BINARY_DIR}/paddle/fluid/framework/framework.pb.h
${src_dir}/${module}/ir/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/details ${dst_dir}/${module} ${dst_dir}/${module}/ir
)
set(module "memory")
copy(memory_lib
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/detail/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/detail
)
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/detail/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/detail
)
set(inference_deps paddle_fluid_shared paddle_fluid)
set(module "inference/api")
if (WITH_ANAKIN AND WITH_MKL)
copy(anakin_inference_lib DEPS paddle_inference_api inference_anakin_api
SRCS
${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libinference_anakin_api* # compiled anakin api
${ANAKIN_INSTALL_DIR} # anakin release
DSTS ${FLUID_INSTALL_DIR}/third_party/install/anakin ${FLUID_INSTALL_DIR}/third_party/install/anakin)
list(APPEND inference_deps anakin_inference_lib)
endif()
SRCS
${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/libinference_anakin_api* # compiled anakin api
${ANAKIN_INSTALL_DIR} # anakin release
DSTS ${FLUID_INSTALL_DIR}/third_party/install/anakin ${FLUID_INSTALL_DIR}/third_party/install/anakin)
list(APPEND inference_deps anakin_inference_lib)
endif ()
set(module "inference")
copy(inference_lib DEPS ${inference_deps}
......@@ -167,30 +188,30 @@ copy(inference_lib DEPS ${inference_deps}
${src_dir}/${module}/api/paddle_*.h
${PADDLE_BINARY_DIR}/paddle/fluid/inference/api/paddle_inference_pass.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module} ${dst_dir}/${module} ${dst_dir}/${module}
)
)
set(module "platform")
copy(platform_lib DEPS profiler_py_proto
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/dynload/*.h ${src_dir}/${module}/details/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/dynload ${dst_dir}/${module}/details
)
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/dynload/*.h ${src_dir}/${module}/details/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/dynload ${dst_dir}/${module}/details
)
set(module "string")
copy(string_lib
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/tinyformat/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/tinyformat
)
SRCS ${src_dir}/${module}/*.h ${src_dir}/${module}/tinyformat/*.h
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/tinyformat
)
set(module "pybind")
copy(pybind_lib
SRCS ${CMAKE_CURRENT_BINARY_DIR}/paddle/fluid/${module}/pybind.h
DSTS ${dst_dir}/${module}
)
SRCS ${CMAKE_CURRENT_BINARY_DIR}/paddle/fluid/${module}/pybind.h
DSTS ${dst_dir}/${module}
)
# CMakeCache Info
copy(cmake_cache
SRCS ${CMAKE_CURRENT_BINARY_DIR}/CMakeCache.txt
DSTS ${FLUID_INSTALL_DIR})
SRCS ${CMAKE_CURRENT_BINARY_DIR}/CMakeCache.txt
DSTS ${FLUID_INSTALL_DIR})
# This command generates a complete fluid library for both train and inference
add_custom_target(fluid_lib_dist DEPENDS ${fluid_lib_dist_dep})
......@@ -198,9 +219,9 @@ add_custom_target(fluid_lib_dist DEPENDS ${fluid_lib_dist_dep})
# Following commands generate a inference-only fluid library
# third_party, version.txt and CMakeCache.txt are the same position with ${FLUID_INSTALL_DIR}
copy(third_party DEPS fluid_lib_dist
SRCS ${FLUID_INSTALL_DIR}/third_party ${FLUID_INSTALL_DIR}/CMakeCache.txt
DSTS ${FLUID_INFERENCE_INSTALL_DIR} ${FLUID_INFERENCE_INSTALL_DIR}
)
SRCS ${FLUID_INSTALL_DIR}/third_party ${FLUID_INSTALL_DIR}/CMakeCache.txt
DSTS ${FLUID_INFERENCE_INSTALL_DIR} ${FLUID_INFERENCE_INSTALL_DIR}
)
# only need libpaddle_fluid.so/a and paddle_*.h for inference-only library
copy(inference_api_lib DEPS fluid_lib_dist
......@@ -213,20 +234,20 @@ add_custom_target(inference_lib_dist DEPENDS third_party inference_api_lib)
# paddle fluid version
function(version version_file)
execute_process(
COMMAND ${GIT_EXECUTABLE} log --pretty=format:%H -1
WORKING_DIRECTORY ${PADDLE_SOURCE_DIR}
OUTPUT_VARIABLE PADDLE_GIT_COMMIT)
file(WRITE ${version_file}
"GIT COMMIT ID: ${PADDLE_GIT_COMMIT}\n"
"WITH_MKL: ${WITH_MKL}\n"
"WITH_MKLDNN: ${WITH_MKLDNN}\n"
"WITH_GPU: ${WITH_GPU}\n")
if(WITH_GPU)
file(APPEND ${version_file}
"CUDA version: ${CUDA_VERSION}\n"
"CUDNN version: v${CUDNN_MAJOR_VERSION}\n")
endif()
execute_process(
COMMAND ${GIT_EXECUTABLE} log --pretty=format:%H -1
WORKING_DIRECTORY ${PADDLE_SOURCE_DIR}
OUTPUT_VARIABLE PADDLE_GIT_COMMIT)
file(WRITE ${version_file}
"GIT COMMIT ID: ${PADDLE_GIT_COMMIT}\n"
"WITH_MKL: ${WITH_MKL}\n"
"WITH_MKLDNN: ${WITH_MKLDNN}\n"
"WITH_GPU: ${WITH_GPU}\n")
if (WITH_GPU)
file(APPEND ${version_file}
"CUDA version: ${CUDA_VERSION}\n"
"CUDNN version: v${CUDNN_MAJOR_VERSION}\n")
endif ()
endfunction()
version(${FLUID_INSTALL_DIR}/version.txt)
version(${FLUID_INFERENCE_INSTALL_DIR}/version.txt)
../../../CONTRIBUTING.md
\ No newline at end of file
../../../CONTRIBUTING.md
......@@ -4,11 +4,12 @@ add_subdirectory(framework)
add_subdirectory(operators)
add_subdirectory(string)
if (NOT WIN32)
add_subdirectory(pybind)
if (NOT WIN32)
add_subdirectory(recordio)
endif(NOT WIN32)
# NOTE: please add subdirectory inference at last.
add_subdirectory(inference)
add_subdirectory(train)
......@@ -137,23 +137,31 @@ cc_test(version_test SRCS version_test.cc DEPS version)
cc_library(proto_desc SRCS var_desc.cc op_desc.cc block_desc.cc program_desc.cc DEPS shape_inference op_info operator glog version)
cc_library(ngraph_bridge SRCS ngraph_bridge.cc DEPS operator framework_proto)
if(NOT WIN32)
cc_library(ngraph_operator SRCS ngraph_operator.cc DEPS ngraph_bridge operator op_info device_context tensor scope glog
shape_inference data_transform lod_tensor profiler)
endif(NOT WIN32)
cc_library(op_registry SRCS op_registry.cc DEPS op_proto_maker op_info operator glog proto_desc)
nv_test(op_registry_test SRCS op_registry_test.cc DEPS op_registry)
if (NOT WIN32)
py_proto_compile(framework_py_proto SRCS framework.proto)
# Generate an empty __init__.py to make framework_py_proto as a valid python module.
add_custom_target(framework_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
add_dependencies(framework_py_proto framework_py_proto_init)
add_custom_command(TARGET framework_py_proto POST_BUILD
COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_BINARY_DIR}/python/paddle/fluid/proto
COMMAND cp *.py ${PADDLE_BINARY_DIR}/python/paddle/fluid/proto/
COMMENT "Copy generated python proto into directory paddle/fluid/proto."
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR})
if (NOT WIN32)
add_custom_command(TARGET framework_py_proto POST_BUILD
COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_BINARY_DIR}/python/paddle/fluid/proto
COMMAND cp *.py ${PADDLE_BINARY_DIR}/python/paddle/fluid/proto/
COMMENT "Copy generated python proto into directory paddle/fluid/proto."
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR})
else(NOT WIN32)
string(REPLACE "/" "\\" proto_dstpath "${PADDLE_BINARY_DIR}/python/paddle/fluid/proto/")
add_custom_command(TARGET framework_py_proto POST_BUILD
COMMAND ${CMAKE_COMMAND} -E make_directory ${PADDLE_BINARY_DIR}/python/paddle/fluid/proto
COMMAND copy /Y *.py ${proto_dstpath}
COMMENT "Copy generated python proto into directory paddle/fluid/proto."
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR})
endif(NOT WIN32)
cc_library(lod_rank_table SRCS lod_rank_table.cc DEPS lod_tensor)
......@@ -167,7 +175,11 @@ if(WITH_DISTRIBUTE)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
else()
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph_operator)
if(NOT WIN32)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph_operator)
else(NOT WIN32)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass)
endif(NOT WIN32)
cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op)
endif()
......
......@@ -29,7 +29,7 @@ template <typename T>
class GarbageCollector {
public:
GarbageCollector(const platform::Place &place, size_t max_memory_size)
: max_memory_size_(std::max(max_memory_size, static_cast<size_t>(1))) {
: max_memory_size_((std::max)(max_memory_size, static_cast<size_t>(1))) {
garbages_.reset(new std::deque<T *>());
dev_ctx_ = platform::DeviceContextPool::Instance().Get(place);
}
......
......@@ -211,12 +211,12 @@ void PrepareLSTMWeight(const LoDTensor& W_forget_w0,
VLOG(30) << "LSTMWeight resized to " << out->dims();
float* out_data = out->mutable_data<float>(platform::CPUPlace());
std::array<const float*, 4> tensors(
{{W_forget_w0.data<float>(), W_input_w0.data<float>(),
W_output_w0.data<float>(), W_cell_w0.data<float>()}});
std::array<const float*, 4> tensors1(
{{W_forget_w1.data<float>(), W_input_w1.data<float>(),
W_output_w1.data<float>(), W_cell_w1.data<float>()}});
std::array<const float*, 4> tensors{
W_forget_w0.data<float>(), W_input_w0.data<float>(),
W_output_w0.data<float>(), W_cell_w0.data<float>()};
std::array<const float*, 4> tensors1{
W_forget_w1.data<float>(), W_input_w1.data<float>(),
W_output_w1.data<float>(), W_cell_w1.data<float>()};
for (int row = 0; row < D; row++) {
for (int col = 0; col < 4; col++) {
......@@ -238,9 +238,9 @@ void PrepareLSTMWeight(const LoDTensor& W_forget_w0,
void PrepareLSTMBias(const LoDTensor& B_forget, const LoDTensor& B_input,
const LoDTensor& B_output, const LoDTensor& B_cell,
LoDTensor* out) {
std::array<const float*, 4> tensors(
{{B_forget.data<float>(), B_input.data<float>(), B_output.data<float>(),
B_cell.data<float>()}});
std::array<const float*, 4> tensors{
B_forget.data<float>(), B_input.data<float>(), B_output.data<float>(),
B_cell.data<float>()};
PADDLE_ENFORCE_EQ(B_forget.dims().size(), 1);
int D = B_forget.dims()[0];
......
......@@ -17,7 +17,12 @@ limitations under the License. */
namespace paddle {
namespace framework {
namespace ir {
// msvc15 don't support constexpr in correct way.
#if !defined(_WIN32)
constexpr char Node::kControlDepVarName[];
#else
const char Node::kControlDepVarName[] = "__control_var";
#endif
std::unique_ptr<Node> CreateNodeForTest(const std::string& name,
Node::Type type) {
......
......@@ -55,7 +55,11 @@ class Node {
}
enum class Type { kOperation, kVariable };
#if !defined(_WIN32) // msvc not support constexpr correctly.
static constexpr char kControlDepVarName[] = "__control_var";
#else
static const char kControlDepVarName[];
#endif
Type NodeType() const { return type_; }
......
......@@ -197,26 +197,26 @@ struct PassRegistrar : public Registrar {
msg)
// Register a new pass that can be applied on the IR.
#define REGISTER_PASS(pass_type, pass_class) \
STATIC_ASSERT_PASS_GLOBAL_NAMESPACE( \
__reg_pass__##pass_type, \
"REGISTER_PASS must be called in global namespace"); \
static ::paddle::framework::ir::PassRegistrar<pass_class> \
__pass_registrar_##pass_type##__(#pass_type); \
int TouchPassRegistrar_##pass_type() { \
__pass_registrar_##pass_type##__.Touch(); \
return 0; \
} \
static ::paddle::framework::ir::PassRegistrar<pass_class> \
&__pass_tmp_registrar_##pass_type##__ __attribute__((unused)) = \
#define REGISTER_PASS(pass_type, pass_class) \
STATIC_ASSERT_PASS_GLOBAL_NAMESPACE( \
__reg_pass__##pass_type, \
"REGISTER_PASS must be called in global namespace"); \
static ::paddle::framework::ir::PassRegistrar<pass_class> \
__pass_registrar_##pass_type##__(#pass_type); \
int TouchPassRegistrar_##pass_type() { \
__pass_registrar_##pass_type##__.Touch(); \
return 0; \
} \
static ::paddle::framework::ir::PassRegistrar<pass_class> \
&__pass_tmp_registrar_##pass_type##__ UNUSED = \
__pass_registrar_##pass_type##__
#define USE_PASS(pass_type) \
STATIC_ASSERT_PASS_GLOBAL_NAMESPACE( \
__use_pass_itself_##pass_type, \
"USE_PASS must be called in global namespace"); \
extern int TouchPassRegistrar_##pass_type(); \
static int use_pass_itself_##pass_type##_ __attribute__((unused)) = \
#define USE_PASS(pass_type) \
STATIC_ASSERT_PASS_GLOBAL_NAMESPACE( \
__use_pass_itself_##pass_type, \
"USE_PASS must be called in global namespace"); \
extern int TouchPassRegistrar_##pass_type(); \
static int use_pass_itself_##pass_type##_ UNUSED = \
TouchPassRegistrar_##pass_type()
} // namespace ir
......
......@@ -150,14 +150,17 @@ void OperatorBase::Run(const Scope& scope, const platform::Place& place) {
#endif
}
// The profile has a process-wide mutex, results in serious performance issue
// in concurrency scenerio. Here use an `if` to fix this issue.
// Please not remove the `if`, ask @Superjomn if there are any concern.
// The profile has a process-wide mutex, results in serious performance issue
// in concurrency scenerio. Here use an `if` to fix this issue.
// Please not remove the `if`, ask @Superjomn if there are any concern.
#ifndef _WIN32
if (platform::IsProfileEnabled()) {
platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
platform::RecordEvent record_event(Type(), pool.Get(place));
RunImpl(scope, place);
} else {
} else
#endif
{
RunImpl(scope, place);
}
VLOG(30) << place << " " << DebugStringEx(&scope);
......
......@@ -16,9 +16,21 @@ cc_library(paddle_fluid_api
DEPS ${FLUID_CORE_MODULES} ${GLOB_OP_LIB})
get_property(fluid_modules GLOBAL PROPERTY FLUID_MODULES)
get_property(cuda_modules GLOBAL PROPERTY CUDA_MODULES)
get_property(fluid_third_partys GLOBAL PROPERTY FLUID_THRID_PARTYS)
if (WIN32)
list(APPEND fluid_third_partys gflags glog protobuf cblas)
endif(WIN32)
# paddle_fluid_origin exclude inference api interface
cc_library(paddle_fluid_origin DEPS ${fluid_modules} paddle_fluid_api)
if(WIN32)
sep_library(paddle_fluid_origin DEPS ${fluid_modules} paddle_fluid_api)
if(WITH_GPU AND NOT WITH_DSO)
target_link_libraries(paddle_fluid_origin ${cuda_modules})
endif(WITH_GPU AND NOT WITH_DSO)
else(WIN32)
cc_library(paddle_fluid_origin DEPS ${fluid_modules} paddle_fluid_api)
endif(WIN32)
add_subdirectory(api)
......@@ -28,8 +40,16 @@ set(SHARED_INFERENCE_SRCS
${CMAKE_CURRENT_SOURCE_DIR}/api/analysis_predictor.cc
${CMAKE_CURRENT_SOURCE_DIR}/api/details/zero_copy_tensor.cc)
# Create static library
cc_library(paddle_fluid DEPS ${fluid_modules} ${STATIC_INFERENCE_APIS} zero_copy_tensor reset_tensor_array analysis_config paddle_pass_builder)
if(WIN32)
sep_library(paddle_fluid DEPS ${fluid_modules} ${STATIC_INFERENCE_APIS} zero_copy_tensor reset_tensor_array
analysis_config paddle_pass_builder)
if(WITH_GPU AND NOT WITH_DSO)
target_link_libraries(paddle_fluid ${cuda_modules})
endif(WITH_GPU AND NOT WITH_DSO)
else(WIN32)
cc_library(paddle_fluid DEPS ${fluid_modules} ${STATIC_INFERENCE_APIS} zero_copy_tensor reset_tensor_array
analysis_config paddle_pass_builder)
endif(WIN32)
if(NOT APPLE)
# TODO(liuyiqu: Temporarily disable the link flag because it is not support on Mac.
......@@ -38,11 +58,20 @@ if(NOT APPLE)
endif()
# Create shared library
cc_library(paddle_fluid_shared SHARED SRCS ${SHARED_INFERENCE_SRCS}
DEPS ${fluid_modules} paddle_fluid_api reset_tensor_array analysis_config paddle_pass_builder)
if(WIN32)
sep_library(paddle_fluid_shared SHARED SRCS ${SHARED_INFERENCE_SRCS}
DEPS ${fluid_modules} paddle_fluid_api reset_tensor_array analysis_config paddle_pass_builder)
target_link_libraries(paddle_fluid_shared shlwapi)
if(WITH_GPU AND NOT WITH_DSO)
target_link_libraries(paddle_fluid_origin ${cuda_modules})
endif(WITH_GPU AND NOT WITH_DSO)
else(WIN32)
cc_library(paddle_fluid_shared SHARED SRCS ${SHARED_INFERENCE_SRCS}
DEPS ${fluid_modules} paddle_fluid_api reset_tensor_array analysis_config paddle_pass_builder)
endif()
set_target_properties(paddle_fluid_shared PROPERTIES OUTPUT_NAME paddle_fluid)
if(NOT APPLE)
if(NOT APPLE AND NOT WIN32)
# TODO(liuyiqun): Temporarily disable the link flag because it is not support on Mac.
set(LINK_FLAGS "-Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/paddle_fluid.map")
set_target_properties(paddle_fluid_shared PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
......
......@@ -26,6 +26,7 @@ limitations under the License. */
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/port.h"
namespace paddle {
namespace inference {
......@@ -124,20 +125,6 @@ T &GetFromScope(const framework::Scope &scope, const std::string &name) {
return *var->GetMutable<T>();
}
static void ExecShellCommand(const std::string &cmd, std::string *message) {
char buffer[128];
std::shared_ptr<FILE> pipe(popen(cmd.c_str(), "r"), pclose);
if (!pipe) {
LOG(ERROR) << "error running command: " << cmd;
return;
}
while (!feof(pipe.get())) {
if (fgets(buffer, 128, pipe.get()) != nullptr) {
*message += buffer;
}
}
}
static framework::proto::ProgramDesc LoadProgramDesc(
const std::string &model_path) {
std::ifstream fin(model_path, std::ios::in | std::ios::binary);
......
......@@ -15,9 +15,14 @@
#pragma once
#include <glog/logging.h>
#if !defined(_WIN32)
#include <sys/time.h>
#else
#endif
#include <algorithm>
#include <chrono> // NOLINT
#include <iterator>
#include <numeric>
#include <sstream>
#include <string>
......
......@@ -94,7 +94,8 @@ function(op_library TARGET)
# remove windows unsupported op, because windows has no nccl, no warpctc such ops.
foreach(windows_unsupport_op "nccl_op" "gen_nccl_id_op" "warpctc_op" "hierarchical_sigmoid_op"
"crf_decoding_op" "select_op" "lstmp_op" "gru_op" "fusion_gru_op" "lstm_op" "fusion_lstm_op" "cumsum_op"
"fusion_seqconv_eltadd_relu_op" "channel_send_op" "channel_create_op" "channel_close_op" "channel_recv_op")
"fusion_seqconv_eltadd_relu_op" "channel_send_op" "channel_create_op" "channel_close_op" "channel_recv_op"
"fusion_seqexpand_concat_fc_op" "attention_lstm_op" "fused_embedding_fc_lstm_op" "fc_op")
if ("${TARGET}" STREQUAL "${windows_unsupport_op}")
return()
endif()
......@@ -308,8 +309,10 @@ op_library(flatten_op DEPS reshape_op)
op_library(sequence_pad_op DEPS sequence_padding)
op_library(unstack_op DEPS stack_op)
op_library(fake_quantize_op DEPS memory)
if (NOT WIN32)
op_library(crf_decoding_op DEPS jit_kernel)
op_library(fusion_lstm_op DEPS jit_kernel)
endif(NOT WIN32)
if (WITH_GPU)
op_library(conv_op DEPS vol2col depthwise_conv im2col)
op_library(layer_norm_op DEPS cub)
......@@ -325,8 +328,8 @@ op_library(save_op DEPS lod_tensor)
op_library(load_op DEPS lod_tensor)
op_library(save_combine_op DEPS lod_tensor)
op_library(load_combine_op DEPS lod_tensor)
op_library(tensor_array_to_tensor_op DEPS concat_op)
op_library(concat_op DEPS concat_and_split)
op_library(tensor_array_to_tensor_op DEPS concat_op)
list(REMOVE_ITEM GENERAL_OPS ${DEPS_OPS})
......
......@@ -15,6 +15,10 @@ limitations under the License. */
#include <algorithm>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/float16.h"
using paddle::platform::PADDLE_CUDA_NUM_THREADS;
using paddle::platform::float16;
namespace paddle {
namespace operators {
......
......@@ -111,6 +111,17 @@ class RowwiseTransformIterator<T, platform::CPUDeviceContext>
return *this;
}
RowwiseTransformIterator<T, platform::CPUDeviceContext> &operator+(int n) {
while (n-- > 0) {
++i_;
if (UNLIKELY(i_ == n_)) {
i_ = 0;
}
}
return *this;
}
bool operator==(const RowwiseTransformIterator<T, platform::CPUDeviceContext>
&rhs) const {
return (ptr_ + i_) == &(*rhs);
......@@ -149,6 +160,21 @@ class MidWiseTransformIterator<T, platform::CPUDeviceContext>
return *this;
}
MidWiseTransformIterator<T, platform::CPUDeviceContext> &operator+(int n) {
while (n-- > 0) {
++j_;
if (UNLIKELY(j_ == post_)) {
++i_;
j_ = 0;
if (UNLIKELY(i_ == n_)) {
i_ = 0;
}
}
}
return *this;
}
bool operator==(const MidWiseTransformIterator<T, platform::CPUDeviceContext>
&rhs) const {
return (ptr_ + i_) == &(*rhs);
......
......@@ -63,7 +63,8 @@ static void CalcGridLocations(const platform::CPUDeviceContext& ctx,
Tensor ones;
ones.mutable_data<T>({n, h, w}, ctx.GetPlace());
auto ones_t = EigenTensor<T, 3>::From(ones).setConstant(1.0);
Tensor half_xmax, half_ymax;
Tensor half_xmax;
Tensor half_ymax;
half_xmax.mutable_data<T>({n, h, w}, ctx.GetPlace());
auto half_xmax_t =
EigenTensor<T, 3>::From(half_xmax).setConstant(0.5 * x_max);
......
......@@ -75,12 +75,13 @@ if(WITH_GPU)
endif()
cc_test(concat_test SRCS concat_test.cc DEPS concat_and_split)
cc_test(cpu_vec_test SRCS cpu_vec_test.cc DEPS blas cpu_info)
set(JIT_KERNEL_SRCS jit_kernel.cc jit_kernel_blas.cc jit_kernel_exp.cc jit_kernel_rnn.cc jit_kernel_crf_decode.cc)
set(JIT_KERNEL_DEPS cpu_info cblas gflags enforce)
if(WITH_XBYAK)
list(APPEND JIT_KERNEL_SRCS jit_gen.cc jit_code.cc)
list(APPEND JIT_KERNEL_DEPS xbyak)
endif()
cc_library(jit_kernel SRCS ${JIT_KERNEL_SRCS} DEPS ${JIT_KERNEL_DEPS})
cc_test(jit_kernel_test SRCS jit_kernel_test.cc DEPS jit_kernel)
if (NOT WIN32)
set(JIT_KERNEL_SRCS jit_kernel.cc jit_kernel_blas.cc jit_kernel_exp.cc jit_kernel_rnn.cc jit_kernel_crf_decode.cc)
set(JIT_KERNEL_DEPS cpu_info cblas gflags enforce)
if(WITH_XBYAK)
list(APPEND JIT_KERNEL_SRCS jit_gen.cc jit_code.cc)
list(APPEND JIT_KERNEL_DEPS xbyak)
endif()
cc_library(jit_kernel SRCS ${JIT_KERNEL_SRCS} DEPS ${JIT_KERNEL_DEPS})
cc_test(jit_kernel_test SRCS jit_kernel_test.cc DEPS jit_kernel)
endif (NOT WIN32)
......@@ -74,7 +74,7 @@ PadConstantLikeOp Operator.
Pad input(Y) with a pad_value, the number of values padded to the edges of each
axis is specified by the difference of the shape of X and Y.
((0, shape_x_0 - shape_y_0), (0, shape_x_n - shape_y_n)) unique pad widths for
((0, shape_x_0 - shape_y_0), ... (0, shape_x_n - shape_y_n)) unique pad widths for
each axis.
The input should be a k-D tensor(k > 0 and k < 7). As an example:
......
......@@ -122,7 +122,7 @@ class ROIPoolOpMaker : public framework::OpProtoAndCheckerMaker {
"(Tensor), "
"Argmaxes corresponding to indices in X used "
"for gradient computation. Only output "
"if arg “is_test” is false.")
"if arg \"is_test\" is false.")
.AsIntermediate();
AddAttr<float>("spatial_scale",
"(float, default 1.0), "
......
......@@ -57,8 +57,8 @@ class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
Input shape is: $(N, C_{in}, H_{in}, W_{in})$, Output shape is:
$(N, C_{out}, H_{out}, W_{out})$, where
$$
H_{out} = (H_{in}−1) * strides[0] − 2 * paddings[0] + ksize[0] \\
W_{out} = (W_{in}−1) * strides[1] − 2 * paddings[1] + ksize[1]
H_{out} = (H_{in}-1) * strides[0] - 2 * paddings[0] + ksize[0] \\
W_{out} = (W_{in}-1) * strides[1] - 2 * paddings[1] + ksize[1]
$$
Paper: http://www.matthewzeiler.com/wp-content/uploads/2017/07/iccv2011.pdf
)DOC");
......
......@@ -112,6 +112,14 @@ void InitDevices(bool init_p2p, const std::vector<int> devices) {
}
places.emplace_back(platform::CPUPlace());
platform::DeviceContextPool::Init(places);
// windows has no support for openblas multi-thread
#ifdef _WIN32
if (FLAGS_paddle_num_threads > 1) {
FLAGS_paddle_num_threads = 1;
}
#endif
#ifndef PADDLE_WITH_MKLDNN
platform::SetNumThreads(FLAGS_paddle_num_threads);
#endif
......@@ -167,7 +175,9 @@ void InitGLOG(const std::string &prog_name) {
// glog will not hold the ARGV[0] inside.
// Use strdup to alloc a new string.
google::InitGoogleLogging(strdup(prog_name.c_str()));
#ifndef _WIN32
google::InstallFailureSignalHandler();
#endif
}
} // namespace framework
......
......@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef _WIN32
#pragma once
#include <stdio.h>
......@@ -149,3 +150,4 @@ struct NCCLContextMap {
} // namespace platform
} // namespace paddle
#endif
......@@ -24,21 +24,16 @@
#include "glog/logging.h"
#if !defined(_WIN32)
#define UNUSED __attribute__((unused))
#include <dlfcn.h> // dladdr
#include <execinfo.h> // backtrace
#include <sys/stat.h>
#include <algorithm> // std::accumulate
#else
#include <io.h> // _popen, _pclose
#include <stdio.h>
#include <windows.h>
#if defined(_WIN32)
#include <numeric> // std::accumulate in msvc
#endif
// windows version of __attribute__((unused))
#define UNUSED __pragma(warning(suppress : 4100))
#ifndef S_ISDIR // windows port for sys/stat.h
#ifndef S_ISDIR // windows port for sys/stat.h
#define S_ISDIR(mode) (((mode)&S_IFMT) == S_IFDIR)
#endif // S_ISDIR
......
......@@ -42,3 +42,11 @@ limitations under the License. */
#include <boost/mpl/comparison.hpp>
#include <boost/mpl/less_equal.hpp>
#include <boost/variant.hpp>
// some platform-independent defintion
#if defined(_WIN32)
#define UNUSED
#define __builtin_expect(EXP, C) (EXP)
#else
#define UNUSED __attribute__((unused))
#endif
......@@ -2,9 +2,9 @@
set(PYBIND_DEPS pybind python proto_desc memory executor prune feed_fetch_method pass_builder)
set(PYBIND_SRCS pybind.cc exception.cc protobuf.cc const_value.cc)
if(NOT WIN32)
list(APPEND PYBIND_DEPS parallel_executor profiler)
list(APPEND PYBIND_SRCS recordio.cc)
endif()
list(APPEND PYBIND_DEPS parallel_executor profiler)
list(APPEND PYBIND_SRCS recordio.cc)
endif(NOT WIN32)
if(WITH_PYTHON)
if(WITH_AMD_GPU)
hip_library(paddle_pybind SHARED
......@@ -21,5 +21,13 @@ if(WITH_PYTHON)
endif(NOT APPLE AND NOT ANDROID AND NOT WIN32)
endif(WITH_AMD_GPU)
if(WIN32)
if(WITH_GPU AND NOT WITH_DSO)
get_property(cuda_modules GLOBAL PROPERTY CUDA_MODULES)
target_link_libraries(paddle_pybind ${cuda_modules})
endif(WITH_GPU AND NOT WITH_DSO)
target_link_libraries(paddle_pybind shlwapi)
endif(WIN32)
cc_test(tensor_py_test SRCS tensor_py_test.cc DEPS python)
endif(WITH_PYTHON)
......@@ -21,6 +21,13 @@ limitations under the License. */
#include <utility>
#include <vector>
#if defined(_WIN32)
#define NOMINMAX
#define GLOG_NO_ABBREVIATED_SEVERITIES // msvc conflict logging with windows.h
#define GOOGLE_GLOG_DLL_DECL
#include <Windows.h>
#endif
#include "paddle/fluid/framework/executor.h"
#include "paddle/fluid/framework/feed_fetch_method.h"
#include "paddle/fluid/framework/framework.pb.h"
......@@ -29,7 +36,9 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/op_registry.h"
#ifndef _WIN32
#include "paddle/fluid/framework/parallel_executor.h"
#endif
#include "paddle/fluid/framework/prune.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/selected_rows.h"
......@@ -50,7 +59,9 @@ limitations under the License. */
#include "paddle/fluid/string/to_string.h"
#ifdef PADDLE_WITH_CUDA
#ifndef _WIN32
#include "paddle/fluid/operators/nccl/nccl_gpu_common.h"
#endif
#include "paddle/fluid/platform/cuda_profiler.h"
#include "paddle/fluid/platform/gpu_info.h"
#endif
......@@ -340,22 +351,25 @@ All parameter, weight, gradient are variables in Paddle.
.def("get_lod_tensor_array",
[](Variable &self) { return self.GetMutable<LoDTensorArray>(); },
py::return_value_policy::reference)
#ifdef PADDLE_WITH_CUDA
#if (defined(PADDLE_WITH_CUDA) && !defined(_WIN32))
.def("get_communicator",
[](Variable &self) -> platform::Communicator * {
return self.GetMutable<platform::Communicator>();
},
py::return_value_policy::reference)
#endif
.def("get_reader",
[](Variable &self) -> framework::ReaderHolder * {
PADDLE_ENFORCE(self.IsType<framework::ReaderHolder>());
return self.GetMutable<framework::ReaderHolder>();
},
py::return_value_policy::reference);
py::return_value_policy::reference)
#endif
;
#if !defined(_WIN32)
py::class_<framework::ReaderHolder>(m, "Reader", "")
.def("reset", &framework::ReaderHolder::ResetAll);
#endif
using LoDTensorBlockingQueue =
::paddle::operators::reader::LoDTensorBlockingQueue;
......@@ -480,7 +494,7 @@ All parameter, weight, gradient are variables in Paddle.
#endif
});;
// clang-format on
#ifdef PADDLE_WITH_CUDA
#if (defined(PADDLE_WITH_CUDA) && !defined(_WIN32))
py::class_<platform::Communicator>(m, "Communicator").def(py::init<>());
#endif
py::class_<platform::CUDAPlace>(m, "CUDAPlace")
......@@ -617,11 +631,14 @@ All parameter, weight, gradient are variables in Paddle.
#ifdef PADDLE_WITH_CUDA
m.def("get_cuda_device_count", platform::GetCUDADeviceCount);
#ifndef _WIN32
m.def("nvprof_init", platform::CudaProfilerInit);
m.def("nvprof_start", platform::CudaProfilerStart);
m.def("nvprof_stop", platform::CudaProfilerStop);
#endif
#endif
#ifndef _WIN32
py::enum_<platform::ProfilerState>(m, "ProfilerState", py::arithmetic())
.value("kDisabled", platform::ProfilerState::kDisabled)
.value("kCPU", platform::ProfilerState::kCPU)
......@@ -642,6 +659,7 @@ All parameter, weight, gradient are variables in Paddle.
m.def("disable_profiler", platform::DisableProfiler);
m.def("is_profiler_enabled", platform::IsProfileEnabled);
m.def("reset_profiler", platform::ResetProfiler);
#endif
py::class_<ir::Pass, std::shared_ptr<ir::Pass>> pass(m, "Pass");
pass.def(py::init())
......@@ -670,6 +688,7 @@ All parameter, weight, gradient are variables in Paddle.
.def("remove_pass",
[](ir::PassBuilder &self, size_t idx) { self.RemovePass(idx); });
#ifndef _WIN32
// -- python binds for parallel executor.
py::class_<ParallelExecutor> pe(m, "ParallelExecutor");
py::class_<ExecutionStrategy> exec_strategy(pe, "ExecutionStrategy", R"DOC(
......@@ -897,6 +916,7 @@ All parameter, weight, gradient are variables in Paddle.
});
BindRecordIOWriter(&m);
#endif
return m.ptr();
}
} // namespace pybind
......
......@@ -45,23 +45,42 @@ endif()
configure_file(${CMAKE_CURRENT_SOURCE_DIR}/setup.py.in
${CMAKE_CURRENT_BINARY_DIR}/setup.py)
set(FLUID_CORE ${PADDLE_BINARY_DIR}/python/paddle/fluid/core.so)
add_custom_command(OUTPUT ${FLUID_CORE}
COMMAND cmake -E copy $<TARGET_FILE:paddle_pybind> ${FLUID_CORE}
DEPENDS paddle_pybind)
IF(WIN32)
# Python would use the .pyd by default under Windows series platform
set(FLUID_DST_DIR ${PADDLE_BINARY_DIR}/python/paddle/fluid/)
get_filename_component(openblas_refpath ${CBLAS_LIBRARIES} DIRECTORY)
set(FLUID_CORE ${FLUID_DST_DIR}/core.pyd)
add_custom_command(OUTPUT ${FLUID_CORE}
COMMAND cmake -E copy $<TARGET_FILE:paddle_pybind> ${FLUID_CORE}
COMMAND cmake -E copy ${openblas_refpath}/openblas.dll ${FLUID_DST_DIR}
DEPENDS paddle_pybind)
ELSE()
set(FLUID_CORE ${PADDLE_BINARY_DIR}/python/paddle/fluid/core.so)
add_custom_command(OUTPUT ${FLUID_CORE}
COMMAND cmake -E copy $<TARGET_FILE:paddle_pybind> ${FLUID_CORE}
DEPENDS paddle_pybind)
ENDIF()
add_custom_target(copy_paddle_pybind ALL DEPENDS ${FLUID_CORE})
add_custom_command(OUTPUT ${PADDLE_PYTHON_BUILD_DIR}/.timestamp
COMMAND touch stub.cc
COMMAND cp -r ${PADDLE_SOURCE_DIR}/python/paddle ${PADDLE_BINARY_DIR}/python
COMMAND cp -r ${PADDLE_SOURCE_DIR}/paddle/py_paddle ${PADDLE_BINARY_DIR}/python/
COMMAND env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
COMMAND ${CMAKE_COMMAND} -E touch ${PADDLE_PYTHON_BUILD_DIR}/.timestamp
COMMAND ${CMAKE_COMMAND} -E remove_directory ${PADDLE_PYTHON_BUILD_DIR}/lib-python
COMMAND ${CMAKE_COMMAND} -E copy_directory ${PADDLE_PYTHON_BUILD_DIR}/lib.* ${PADDLE_PYTHON_BUILD_DIR}/lib-python
DEPENDS gen_proto_py copy_paddle_pybind ${FLUID_CORE} framework_py_proto profiler_py_proto ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
IF(WIN32)
add_custom_command(OUTPUT ${PADDLE_PYTHON_BUILD_DIR}/.timestamp
COMMAND ${CMAKE_COMMAND} -E copy_directory ${PADDLE_SOURCE_DIR}/python/paddle ${PADDLE_BINARY_DIR}/python/paddle/
COMMAND ${CMAKE_COMMAND} -E copy_directory ${PADDLE_SOURCE_DIR}/paddle/py_paddle ${PADDLE_BINARY_DIR}/python/
COMMAND ${CMAKE_COMMAND} -E env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
COMMAND ${CMAKE_COMMAND} -E touch ${PADDLE_PYTHON_BUILD_DIR}/.timestamp
COMMAND ${CMAKE_COMMAND} -E remove_directory ${PADDLE_PYTHON_BUILD_DIR}/lib-python
DEPENDS gen_proto_py copy_paddle_pybind ${FLUID_CORE} framework_py_proto profiler_py_proto ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
ELSE(WIN32)
add_custom_command(OUTPUT ${PADDLE_PYTHON_BUILD_DIR}/.timestamp
COMMAND touch stub.cc
COMMAND cp -r ${PADDLE_SOURCE_DIR}/python/paddle ${PADDLE_BINARY_DIR}/python
COMMAND cp -r ${PADDLE_SOURCE_DIR}/paddle/py_paddle ${PADDLE_BINARY_DIR}/python/
COMMAND env ${py_env} ${PYTHON_EXECUTABLE} setup.py bdist_wheel
COMMAND ${CMAKE_COMMAND} -E touch ${PADDLE_PYTHON_BUILD_DIR}/.timestamp
COMMAND ${CMAKE_COMMAND} -E remove_directory ${PADDLE_PYTHON_BUILD_DIR}/lib-python
COMMAND ${CMAKE_COMMAND} -E copy_directory ${PADDLE_PYTHON_BUILD_DIR}/lib* ${PADDLE_PYTHON_BUILD_DIR}/lib-python
DEPENDS gen_proto_py copy_paddle_pybind ${FLUID_CORE} framework_py_proto profiler_py_proto ${PY_FILES} ${external_project_dependencies} ${COPY_PADDLE_MASTER})
ENDIF()
set(paddle_python_deps ${PADDLE_PYTHON_BUILD_DIR}/.timestamp ${MKL_DEPENDS})
if(NOT WITH_FLUID_ONLY)
......
......@@ -13,6 +13,7 @@
# limitations under the License.
from __future__ import print_function
import os
# import all class inside framework into fluid module
from . import framework
from .framework import *
......@@ -111,12 +112,16 @@ def __bootstrap__():
os.environ['OMP_NUM_THREADS'] = str(num_threads)
read_env_flags = [
'use_pinned_memory', 'check_nan_inf', 'benchmark', 'warpctc_dir',
'eager_delete_scope', 'use_mkldnn', 'use_ngraph',
'initial_cpu_memory_in_mb', 'init_allocated_mem', 'free_idle_memory',
'paddle_num_threads', 'dist_threadpool_size', 'cpu_deterministic',
'eager_delete_tensor_gb', 'reader_queue_speed_test_mode'
'use_pinned_memory', 'check_nan_inf', 'benchmark', 'eager_delete_scope',
'use_mkldnn', 'use_ngraph', 'initial_cpu_memory_in_mb',
'init_allocated_mem', 'free_idle_memory', 'paddle_num_threads',
'dist_threadpool_size', 'eager_delete_tensor_gb',
'reader_queue_speed_test_mode'
]
if os.name != 'nt':
read_env_flags.append('warpctc_dir')
read_env_flags.append('cpu_deterministic')
if core.is_compiled_with_dist():
read_env_flags.append('rpc_deadline')
read_env_flags.append('rpc_server_profile_path')
......
......@@ -15,13 +15,15 @@
from __future__ import print_function
import contextlib
import os
from .. import core
from .. import executor
from .. import framework
from .. import io
from .. import parallel_executor
if os.name != 'nt':
from .. import parallel_executor
from .. import unique_name
from .trainer import check_and_get_place
......
......@@ -28,7 +28,8 @@ from .. import framework
from .. import io
# optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
from .. import optimizer as opt_module
from .. import parallel_executor
if os.name != 'nt':
from .. import parallel_executor
from ..transpiler import distribute_transpiler
__all__ = [
......
......@@ -15,6 +15,7 @@
from __future__ import print_function
import contextlib
import multiprocessing
import os
import six
import threading
......@@ -346,70 +347,72 @@ def _copy_reader_create_op_(block, op):
return new_op
@templatedoc(op_type='create_recordio_file_reader')
def open_recordio_file(filename,
shapes,
lod_levels,
dtypes,
pass_num=1,
for_parallel=True):
"""
${comment}
Args:
filename(${filename_type}): ${filename_comment}.
shapes(list): List of tuples which declaring data shapes.
lod_levels(${lod_levels_type}): ${lod_levels_comment}.
dtypes(list): List of strs which declaring data type.
pass_num(int): Number of passes to run.
for_parallel(Bool): Set it as True if you are going to run
subsequent operators in parallel.
Returns:
${out_comment}.
Examples:
>>> import paddle.fluid as fluid
>>> reader = fluid.layers.io.open_recordio_file(
>>> filename='./data.recordio',
>>> shapes=[(3,224,224), (1)],
>>> lod_levels=[0, 0],
>>> dtypes=['float32', 'int64'])
>>> # Via the reader, we can use 'read_file' layer to get data:
>>> image, label = fluid.layers.io.read_file(reader)
"""
dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
shape_concat = []
ranks = []
if os.name != 'nt':
@templatedoc(op_type='create_recordio_file_reader')
def open_recordio_file(filename,
shapes,
lod_levels,
dtypes,
pass_num=1,
for_parallel=True):
"""
${comment}
Args:
filename(${filename_type}): ${filename_comment}.
shapes(list): List of tuples which declaring data shapes.
lod_levels(${lod_levels_type}): ${lod_levels_comment}.
dtypes(list): List of strs which declaring data type.
pass_num(int): Number of passes to run.
for_parallel(Bool): Set it as True if you are going to run
subsequent operators in parallel.
Returns:
${out_comment}.
Examples:
>>> import paddle.fluid as fluid
>>> reader = fluid.layers.io.open_recordio_file(
>>> filename='./data.recordio',
>>> shapes=[(3,224,224), (1)],
>>> lod_levels=[0, 0],
>>> dtypes=['float32', 'int64'])
>>> # Via the reader, we can use 'read_file' layer to get data:
>>> image, label = fluid.layers.io.read_file(reader)
"""
dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
shape_concat = []
ranks = []
for shape in shapes:
shape_concat.extend(shape)
ranks.append(len(shape))
for shape in shapes:
shape_concat.extend(shape)
ranks.append(len(shape))
var_name = unique_name('open_recordio_file')
var_name = unique_name('open_recordio_file')
startup_blk = default_startup_program().current_block()
startup_var = startup_blk.create_var(name=var_name)
startup_blk.append_op(
type='create_recordio_file_reader',
outputs={'Out': [startup_var]},
attrs={
'shape_concat': shape_concat,
'lod_levels': lod_levels,
'filename': filename,
'ranks': ranks
})
startup_blk = default_startup_program().current_block()
startup_var = startup_blk.create_var(name=var_name)
startup_blk.append_op(
type='create_recordio_file_reader',
outputs={'Out': [startup_var]},
attrs={
'shape_concat': shape_concat,
'lod_levels': lod_levels,
'filename': filename,
'ranks': ranks
})
startup_var.desc.set_dtypes(dtypes)
startup_var.persistable = True
main_prog_var = _copy_reader_var_(default_main_program().current_block(),
startup_var)
startup_var.desc.set_dtypes(dtypes)
startup_var.persistable = True
main_prog_var = _copy_reader_var_(
default_main_program().current_block(), startup_var)
if pass_num > 1:
main_prog_var = multi_pass(reader=main_prog_var, pass_num=pass_num)
if pass_num > 1:
main_prog_var = multi_pass(reader=main_prog_var, pass_num=pass_num)
return monkey_patch_reader_methods(main_prog_var)
return monkey_patch_reader_methods(main_prog_var)
def random_data_generator(low, high, shapes, lod_levels, for_parallel=True):
......
......@@ -18,6 +18,7 @@ All layers just related to the neural network.
from __future__ import print_function
import numpy as np
import os
from ..layer_helper import LayerHelper
from ..initializer import Normal, Constant
from ..framework import Variable, OpProtoHolder
......@@ -341,126 +342,128 @@ def embedding(input,
return tmp
@templatedoc(op_type="lstm")
def dynamic_lstm(input,
size,
h_0=None,
c_0=None,
param_attr=None,
bias_attr=None,
use_peepholes=True,
is_reverse=False,
gate_activation='sigmoid',
cell_activation='tanh',
candidate_activation='tanh',
dtype='float32',
name=None):
"""
${comment}
Args:
input (Variable): ${input_comment}
size (int): 4 * hidden size.
h_0(Variable): The initial hidden state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size and D is the hidden size.
c_0(Variable): The initial cell state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size. `h_0` and `c_0` can be NULL but only at the same time.
param_attr(ParamAttr|None): The parameter attribute for the learnable
hidden-hidden weights.
- Weights = {:math:`W_{ch}, W_{ih}, \
W_{fh}, W_{oh}`}
- The shape is (D x 4D), where D is the hidden
size.
If it is set to None or one attribute of ParamAttr,
dynamic_lstm will create ParamAttr as param_attr.
If the Initializer of the param_attr is not set, the
parameter is initialized with Xavier. Default: None.
bias_attr (ParamAttr|None): The bias attribute for the learnable bias
weights, which contains two parts, input-hidden
bias weights and peephole connections weights if
setting `use_peepholes` to `True`.
1. `use_peepholes = False`
- Biases = {:math:`b_c, b_i, b_f, b_o`}.
- The shape is (1 x 4D).
2. `use_peepholes = True`
- Biases = { :math:`b_c, b_i, b_f, b_o, W_{ic}, \
W_{fc}, W_{oc}`}.
- The shape is (1 x 7D).
If it is set to None or one attribute of ParamAttr,
dynamic_lstm will create ParamAttr as bias_attr.
If the Initializer of the bias_attr is not set,
the bias is initialized zero. Default: None.
use_peepholes (bool): ${use_peepholes_comment}
is_reverse (bool): ${is_reverse_comment}
gate_activation (str): ${gate_activation_comment}
cell_activation (str): ${cell_activation_comment}
candidate_activation (str): ${candidate_activation_comment}
dtype (str): Data type. Choices = ["float32", "float64"], default "float32".
name (str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
if os.name != 'nt':
Returns:
tuple: The hidden state, and cell state of LSTM. The shape of both \
is (T x D), and lod is the same with the `input`.
Examples:
.. code-block:: python
hidden_dim = 512
forward_proj = fluid.layers.fc(input=input_seq, size=hidden_dim * 4,
bias_attr=False)
forward, _ = fluid.layers.dynamic_lstm(
input=forward_proj, size=hidden_dim * 4, use_peepholes=False)
"""
assert bias_attr is not False, "bias_attr should not be False in dynamic_lstmp."
helper = LayerHelper('lstm', **locals())
size = size // 4
weight = helper.create_parameter(
attr=helper.param_attr, shape=[size, 4 * size], dtype=dtype)
bias_size = [1, 7 * size]
if not use_peepholes:
bias_size[1] = 4 * size
bias = helper.create_parameter(
attr=helper.bias_attr, shape=bias_size, dtype=dtype, is_bias=True)
@templatedoc(op_type="lstm")
def dynamic_lstm(input,
size,
h_0=None,
c_0=None,
param_attr=None,
bias_attr=None,
use_peepholes=True,
is_reverse=False,
gate_activation='sigmoid',
cell_activation='tanh',
candidate_activation='tanh',
dtype='float32',
name=None):
"""
${comment}
Args:
input (Variable): ${input_comment}
size (int): 4 * hidden size.
h_0(Variable): The initial hidden state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size and D is the hidden size.
c_0(Variable): The initial cell state is an optional input, default is zero.
This is a tensor with shape (N x D), where N is the
batch size. `h_0` and `c_0` can be NULL but only at the same time.
param_attr(ParamAttr|None): The parameter attribute for the learnable
hidden-hidden weights.
- Weights = {:math:`W_{ch}, W_{ih}, \
W_{fh}, W_{oh}`}
- The shape is (D x 4D), where D is the hidden
size.
If it is set to None or one attribute of ParamAttr,
dynamic_lstm will create ParamAttr as param_attr.
If the Initializer of the param_attr is not set, the
parameter is initialized with Xavier. Default: None.
bias_attr (ParamAttr|None): The bias attribute for the learnable bias
weights, which contains two parts, input-hidden
bias weights and peephole connections weights if
setting `use_peepholes` to `True`.
1. `use_peepholes = False`
- Biases = {:math:`b_c, b_i, b_f, b_o`}.
- The shape is (1 x 4D).
2. `use_peepholes = True`
- Biases = { :math:`b_c, b_i, b_f, b_o, W_{ic}, \
W_{fc}, W_{oc}`}.
- The shape is (1 x 7D).
If it is set to None or one attribute of ParamAttr,
dynamic_lstm will create ParamAttr as bias_attr.
If the Initializer of the bias_attr is not set,
the bias is initialized zero. Default: None.
use_peepholes (bool): ${use_peepholes_comment}
is_reverse (bool): ${is_reverse_comment}
gate_activation (str): ${gate_activation_comment}
cell_activation (str): ${cell_activation_comment}
candidate_activation (str): ${candidate_activation_comment}
dtype (str): Data type. Choices = ["float32", "float64"], default "float32".
name (str|None): A name for this layer(optional). If set None, the layer
will be named automatically.
Returns:
tuple: The hidden state, and cell state of LSTM. The shape of both \
is (T x D), and lod is the same with the `input`.
Examples:
.. code-block:: python
hidden_dim = 512
forward_proj = fluid.layers.fc(input=input_seq, size=hidden_dim * 4,
bias_attr=False)
forward, _ = fluid.layers.dynamic_lstm(
input=forward_proj, size=hidden_dim * 4, use_peepholes=False)
"""
assert bias_attr is not False, "bias_attr should not be False in dynamic_lstmp."
helper = LayerHelper('lstm', **locals())
size = size // 4
weight = helper.create_parameter(
attr=helper.param_attr, shape=[size, 4 * size], dtype=dtype)
bias_size = [1, 7 * size]
if not use_peepholes:
bias_size[1] = 4 * size
bias = helper.create_parameter(
attr=helper.bias_attr, shape=bias_size, dtype=dtype, is_bias=True)
hidden = helper.create_variable_for_type_inference(dtype)
cell = helper.create_variable_for_type_inference(dtype)
batch_gate = helper.create_variable_for_type_inference(dtype)
batch_cell_pre_act = helper.create_variable_for_type_inference(dtype)
inputs = {'Input': input, 'Weight': weight, 'Bias': bias}
batch_size = input.shape[0]
if h_0:
assert h_0.shape == (batch_size, size), \
'The shape of h0 should be (batch_size, %d)' % size
inputs['H0'] = h_0
if c_0:
assert c_0.shape == (batch_size, size), \
'The shape of c0 should be (batch_size, %d)' % size
inputs['C0'] = c_0
hidden = helper.create_variable_for_type_inference(dtype)
cell = helper.create_variable_for_type_inference(dtype)
batch_gate = helper.create_variable_for_type_inference(dtype)
batch_cell_pre_act = helper.create_variable_for_type_inference(dtype)
inputs = {'Input': input, 'Weight': weight, 'Bias': bias}
batch_size = input.shape[0]
if h_0:
assert h_0.shape == (batch_size, size), \
'The shape of h0 should be (batch_size, %d)' % size
inputs['H0'] = h_0
if c_0:
assert c_0.shape == (batch_size, size), \
'The shape of c0 should be (batch_size, %d)' % size
inputs['C0'] = c_0
helper.append_op(
type='lstm',
inputs=inputs,
outputs={
'Hidden': hidden,
'Cell': cell,
'BatchGate': batch_gate,
'BatchCellPreAct': batch_cell_pre_act
},
attrs={
'use_peepholes': use_peepholes,
'is_reverse': is_reverse,
'gate_activation': gate_activation,
'cell_activation': cell_activation,
'candidate_activation': candidate_activation
})
return hidden, cell
helper.append_op(
type='lstm',
inputs=inputs,
outputs={
'Hidden': hidden,
'Cell': cell,
'BatchGate': batch_gate,
'BatchCellPreAct': batch_cell_pre_act
},
attrs={
'use_peepholes': use_peepholes,
'is_reverse': is_reverse,
'gate_activation': gate_activation,
'cell_activation': cell_activation,
'candidate_activation': candidate_activation
})
return hidden, cell
def dynamic_lstmp(input,
......@@ -959,39 +962,43 @@ def linear_chain_crf(input, label, param_attr=None):
return log_likelihood
@templatedoc()
def crf_decoding(input, param_attr, label=None):
"""
${comment}
if os.name != 'nt':
Args:
input(${emission_type}): ${emission_comment}
@templatedoc()
def crf_decoding(input, param_attr, label=None):
"""
${comment}
param_attr(ParamAttr): The parameter attribute for training.
Args:
input(${emission_type}): ${emission_comment}
label(${label_type}): ${label_comment}
param_attr(ParamAttr): The parameter attribute for training.
Returns:
Variable: ${viterbi_path_comment}
label(${label_type}): ${label_comment}
Examples:
.. code-block:: python
Returns:
Variable: ${viterbi_path_comment}
crf_decode = layers.crf_decoding(
input=hidden, param_attr=ParamAttr(name="crfw"))
"""
helper = LayerHelper('crf_decoding', **locals())
transition = helper.get_parameter(param_attr.name)
viterbi_path = helper.create_variable_for_type_inference(
dtype=helper.input_dtype())
helper.append_op(
type='crf_decoding',
inputs={"Emission": [input],
Examples:
.. code-block:: python
crf_decode = layers.crf_decoding(
input=hidden, param_attr=ParamAttr(name="crfw"))
"""
helper = LayerHelper('crf_decoding', **locals())
transition = helper.get_parameter(param_attr.name)
viterbi_path = helper.create_variable_for_type_inference(
dtype=helper.input_dtype())
helper.append_op(
type='crf_decoding',
inputs={
"Emission": [input],
"Transition": transition,
"Label": label},
outputs={"ViterbiPath": [viterbi_path]})
"Label": label
},
outputs={"ViterbiPath": [viterbi_path]})
return viterbi_path
return viterbi_path
@templatedoc()
......@@ -5538,42 +5545,48 @@ def label_smooth(label,
return smooth_label
@templatedoc()
def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
"""
${comment}
Args:
input (Variable): ${x_comment}
rois (Variable): ROIs (Regions of Interest) to pool over.
pooled_height (integer): ${pooled_height_comment} Default: 1
pooled_width (integer): ${pooled_width_comment} Default: 1
spatial_scale (float): ${spatial_scale_comment} Default: 1.0
Returns:
Variable: ${out_comment}.
Examples:
.. code-block:: python
pool_out = fluid.layers.roi_pool(input=x, rois=rois, 7, 7, 1.0)
"""
helper = LayerHelper('roi_pool', **locals())
dtype = helper.input_dtype()
pool_out = helper.create_variable_for_type_inference(dtype)
argmaxes = helper.create_variable_for_type_inference(dtype='int32')
helper.append_op(
type="roi_pool",
inputs={"X": input,
"ROIs": rois},
outputs={"Out": pool_out,
"Argmax": argmaxes},
attrs={
"pooled_height": pooled_height,
"pooled_width": pooled_width,
"spatial_scale": spatial_scale
})
return pool_out
if os.name != 'nt':
@templatedoc()
def roi_pool(input,
rois,
pooled_height=1,
pooled_width=1,
spatial_scale=1.0):
"""
${comment}
Args:
input (Variable): ${x_comment}
rois (Variable): ROIs (Regions of Interest) to pool over.
pooled_height (integer): ${pooled_height_comment} Default: 1
pooled_width (integer): ${pooled_width_comment} Default: 1
spatial_scale (float): ${spatial_scale_comment} Default: 1.0
Returns:
Variable: ${out_comment}.
Examples:
.. code-block:: python
pool_out = fluid.layers.roi_pool(input=x, rois=rois, 7, 7, 1.0)
"""
helper = LayerHelper('roi_pool', **locals())
dtype = helper.input_dtype()
pool_out = helper.create_variable_for_type_inference(dtype)
argmaxes = helper.create_variable_for_type_inference(dtype='int32')
helper.append_op(
type="roi_pool",
inputs={"X": input,
"ROIs": rois},
outputs={"Out": pool_out,
"Argmax": argmaxes},
attrs={
"pooled_height": pooled_height,
"pooled_width": pooled_width,
"spatial_scale": spatial_scale
})
return pool_out
@templatedoc()
......
......@@ -13,6 +13,7 @@
# limitations under the License.
from __future__ import print_function
import os
from .layer_function_generator import generate_layer_fn, generate_layer_fn_noattr
from .. import core
from ..framework import convert_np_dtype_to_dtype_
......@@ -99,27 +100,26 @@ Examples:
>>> result = fluid.layers.hard_shrink(x=data, threshold=0.3)
"""
__all__ += ['cumsum']
_cum_sum_ = generate_layer_fn('cumsum')
def cumsum(x, axis=None, exclusive=None, reverse=None):
locals_var = locals().keys()
kwargs = dict()
for name in locals_var:
val = locals()[name]
if val is not None:
kwargs[name] = val
return _cum_sum_(**kwargs)
cumsum.__doc__ = _cum_sum_.__doc__ + """
Examples:
>>> data = fluid.layers.data(name="input", shape=[32, 784])
>>> result = fluid.layers.cumsum(data, axis=0)
"""
if os.name != 'nt':
__all__ += ['cumsum']
_cum_sum_ = generate_layer_fn('cumsum')
def cumsum(x, axis=None, exclusive=None, reverse=None):
locals_var = locals().keys()
kwargs = dict()
for name in locals_var:
val = locals()[name]
if val is not None:
kwargs[name] = val
return _cum_sum_(**kwargs)
cumsum.__doc__ = _cum_sum_.__doc__ + """
Examples:
>>> data = fluid.layers.data(name="input", shape=[32, 784])
>>> result = fluid.layers.cumsum(data, axis=0)
"""
__all__ += ['thresholded_relu']
......
requests==2.9.2
numpy>=1.12,<=1.14 #TODO:change to ">=1.12" when numpy fix bug in 1.15 and higher version
protobuf==3.1
recordio>=0.1.0
recordio>=0.1.0; sys_platform != 'win32'
matplotlib==2.2.3 # TODO: let python3 paddlepaddle package use latest matplotlib
rarfile
scipy>=0.19.0
......
......@@ -9,7 +9,7 @@ class BinaryDistribution(Distribution):
RC = 0
ext_name = '.dll' if os.name == 'nt' else '.so'
def git_commit():
try:
......@@ -136,10 +136,13 @@ if '${WITH_FLUID_ONLY}'== 'OFF':
'${PADDLE_BINARY_DIR}/paddle/legacy/pserver/paddle_pserver_main',
'${PADDLE_BINARY_DIR}/paddle/scripts/paddle']
package_data={'paddle.fluid': ['core.so']}
package_data={'paddle.fluid': ['core' + (ext_name if os.name != 'nt' else '.pyd')]}
if os.name == 'nt':
package_data['paddle.fluid'] += ['openblas' + ext_name]
if '${WITH_FLUID_ONLY}'== 'OFF':
package_data['paddle.v2.master']=['libpaddle_master.so']
package_data['py_paddle']=['*.py','_swig_paddle.so']
package_data['paddle.v2.master']=['libpaddle_master' + ext_name]
package_data['py_paddle']=['*.py','_swig_paddle' + + ext_name]
package_dir={
'': '${PADDLE_BINARY_DIR}/python',
......@@ -153,13 +156,15 @@ if '${WITH_FLUID_ONLY}'== 'OFF':
package_dir['py_paddle']='${PADDLE_BINARY_DIR}/python/py_paddle'
# put all thirdparty libraries in paddle.libs
package_data['paddle.libs']=['libwarpctc.so']
libs_path='${PADDLE_BINARY_DIR}/python/paddle/libs'
shutil.copy('${WARPCTC_LIBRARIES}', libs_path)
if os.name != 'nt':
package_data['paddle.libs']= []
package_data['paddle.libs']=['libwarpctc' + ext_name]
shutil.copy('${WARPCTC_LIBRARIES}', libs_path)
if '${WITH_MKL}' == 'ON':
shutil.copy('${MKLML_LIB}', libs_path)
shutil.copy('${MKLML_IOMP_LIB}', libs_path)
package_data['paddle.libs']+=['libmklml_intel.so','libiomp5.so']
package_data['paddle.libs']+=['libmklml_intel' + ext_name,'libiomp5' + ext_name]
if '${CMAKE_BUILD_TYPE}' == 'Release':
# only change rpath in Release mode.
if '${WITH_MKLDNN}' == 'ON':
......@@ -187,36 +192,47 @@ if '${WITH_NGRAPH}' == 'ON':
'${NGRAPH_CPU_LIB_NAME}',
'${NGRAPH_TBB_LIB_NAME}']
# remove unused paddle/libs/__init__.py
os.remove(libs_path+'/__init__.py')
if os.path.isfile(libs_path+'/__init__.py'):
os.remove(libs_path+'/__init__.py')
package_dir['paddle.libs']=libs_path
# change rpath of core.so, add $ORIGIN/../libs/ to it.
# The reason is that libwarpctc.so, libiomp5.so etc are in paddle.libs, and
# core.so is in paddle.fluid, thus paddle/fluid/../libs will pointer to above libraries.
# change rpath of core.ext, add $ORIGIN/../libs/ to it.
# The reason is that libwarpctc.ext, libiomp5.ext etc are in paddle.libs, and
# core.ext is in paddle.fluid, thus paddle/fluid/../libs will pointer to above libraries.
# This operation will fix https://github.com/PaddlePaddle/Paddle/issues/3213
if '${CMAKE_BUILD_TYPE}' == 'Release':
# only change rpath in Release mode, since in Debug mode, core.so is too large to be changed.
if "@APPLE@" == "1":
command = "install_name_tool -id \"@loader_path/../libs/\" ${PADDLE_BINARY_DIR}/python/paddle/fluid/core.so"
else:
command = "patchelf --set-rpath '$ORIGIN/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/core.so"
if os.system(command) != 0:
raise Exception("patch core.so failed, command: %s" % command)
if '${WITH_FLUID_ONLY}'== 'OFF':
# change rpath of _swig_paddle.so.
if os.name != 'nt':
# only change rpath in Release mode, since in Debug mode, core.xx is too large to be changed.
if "@APPLE@" == "1":
command = "install_name_tool -id \"@loader_path/../paddle/libs/\" ${PADDLE_BINARY_DIR}/python/py_paddle/_swig_paddle.so"
command = "install_name_tool -id \"@loader_path/../libs/\" ${PADDLE_BINARY_DIR}/python/paddle/fluid/core" + ext_name
else:
command = "patchelf --set-rpath '$ORIGIN/../paddle/libs/' ${PADDLE_BINARY_DIR}/python/py_paddle/_swig_paddle.so"
command = "patchelf --set-rpath '$ORIGIN/../libs/' ${PADDLE_BINARY_DIR}/python/paddle/fluid/core" + ext_name
if os.system(command) != 0:
raise Exception("patch _swig_paddle.so failed, command: %s" % command)
raise Exception("patch core.%s failed, command: %s" % (ext_name, command))
if '${WITH_FLUID_ONLY}'== 'OFF':
# change rpath of _swig_paddle.xx.
if "@APPLE@" == "1":
command = "install_name_tool -id \"@loader_path/../paddle/libs/\" ${PADDLE_BINARY_DIR}/python/py_paddle/_swig_paddle" + ext_name
else:
command = "patchelf --set-rpath '$ORIGIN/../paddle/libs/' ${PADDLE_BINARY_DIR}/python/py_paddle/_swig_paddle" + ext_name
if os.system(command) != 0:
raise Exception("patch _swig_paddle.%s failed, command: %s" % (ext_name, command))
ext_modules = [Extension('_foo', ['stub.cc'])]
if os.name == 'nt':
# fix the path separator under windows
fix_package_dir = {}
for k, v in package_dir.items():
fix_package_dir[k] = v.replace('/', '\\')
package_dir = fix_package_dir
ext_modules = []
setup(name='${PACKAGE_NAME}',
version='${PADDLE_VERSION}',
description='Parallel Distributed Deep Learning',
install_requires=setup_requires,
packages=packages,
ext_modules=[Extension('_foo', ['stub.cc'])],
ext_modules=ext_modules,
package_data=package_data,
package_dir=package_dir,
scripts=paddle_bins
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册