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mindspore
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syn code 0706

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pull/3198/head
changzherui 5 years ago
parent 6086a7252e d0dd892884
commit 17da929b82
1120 changed files with 38622 additions and 55782 deletions
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1
.gitignore vendored
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@ -26,6 +26,7 @@ cmake-build-debug
*_pb2.py
*.pb.h
*.pb.cc
*.pb
# Object files
*.o

10
CMakeLists.txt
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@ -12,7 +12,7 @@ if (NOT CMAKE_SYSTEM_NAME MATCHES "Windows")
endif ()
if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
set(CMAKE_CXX_FLAGS_RELEASE "$ENV{CXXFLAGS} -O2 -Werror -Wno-return-std-move -Wno-unused-private-field -Wno-unused-lambda-capture -Wno-sign-compare -Wno-overloaded-virtual -Wno-unneeded-internal-declaration -Wno-unused-variable -Wno-pessimizing-move -Wno-inconsistent-missing-override -DHALF_ENABLE_CPP11_USER_LITERALS=0 -D_FORTIFY_SOURCE=2")
set(CMAKE_CXX_FLAGS_RELEASE "$ENV{CXXFLAGS} -O2 -Werror -Wno-return-std-move -Wno-unused-private-field -Wno-unused-lambda-capture -Wno-sign-compare -Wno-overloaded-virtual -Wno-unneeded-internal-declaration -Wno-unused-variable -Wno-pessimizing-move -Wno-inconsistent-missing-override -DHALF_ENABLE_CPP11_USER_LITERALS=0 -D_FORTIFY_SOURCE=2")
else()
set(CMAKE_CXX_FLAGS_RELEASE "$ENV{CXXFLAGS} -O2 -Wl,--allow-shlib-undefined -DHALF_ENABLE_CPP11_USER_LITERALS=0 -D_FORTIFY_SOURCE=2")
endif()
@ -38,6 +38,10 @@ if (NOT Patch_FOUND)
endif ()
message(PATCH_EXECUTABLE = ${Patch_EXECUTABLE})
if (ENABLE_AKG AND ENABLE_D)
add_subdirectory("${CMAKE_SOURCE_DIR}/akg")
endif()
include(${CMAKE_SOURCE_DIR}/cmake/mind_expression.cmake)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/third_party/flatbuffers/include)
@ -86,10 +90,6 @@ if (ENABLE_GE OR ENABLE_D OR ENABLE_TESTCASES)
include_directories(${CMAKE_CURRENT_SOURCE_DIR}/graphengine/third_party/fwkacllib/inc/toolchain)
endif()
if (ENABLE_AKG AND ENABLE_D)
add_subdirectory("${CMAKE_SOURCE_DIR}/akg")
endif()
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fvisibility=hidden")
add_subdirectory(mindspore/ccsrc)
if (ENABLE_TESTCASES)

15
README.md
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@ -29,7 +29,7 @@ enrichment of the AI software/hardware application ecosystem.
<img src="docs/MindSpore-architecture.png" alt="MindSpore Architecture" width="600"/>
For more details please check out our [Architecture Guide](https://www.mindspore.cn/docs/en/0.3.0-alpha/architecture.html).
For more details please check out our [Architecture Guide](https://www.mindspore.cn/docs/en/master/architecture.html).
### Automatic Differentiation
@ -66,7 +66,6 @@ MindSpore offers build options across multiple backends:
| Ascend910 | Ubuntu-x86 | ✔️ |
| | EulerOS-x86 | ✔️ |
| | EulerOS-aarch64 | ✔️ |
| GPU CUDA 9.2 | Ubuntu-x86 | ✔️ |
| GPU CUDA 10.1 | Ubuntu-x86 | ✔️ |
| CPU | Ubuntu-x86 | ✔️ |
| | Windows-x86 | ✔️ |
@ -76,7 +75,7 @@ For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an ex
1. Download whl from [MindSpore download page](https://www.mindspore.cn/versions/en), and install the package.
```
pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.3.0-alpha/MindSpore/cpu/ubuntu_x86/mindspore-0.3.0-cp37-cp37m-linux_x86_64.whl
pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.5.0-beta/MindSpore/cpu/ubuntu_x86/mindspore-0.5.0-cp37-cp37m-linux_x86_64.whl
```
2. Run the following command to verify the install.
@ -133,8 +132,8 @@ currently the containerized build options are supported as follows:
For `CPU` backend, you can directly pull and run the latest stable image using the below command:
```
docker pull mindspore/mindspore-cpu:0.3.0-alpha
docker run -it mindspore/mindspore-cpu:0.3.0-alpha /bin/bash
docker pull mindspore/mindspore-cpu:0.5.0-beta
docker run -it mindspore/mindspore-cpu:0.5.0-beta /bin/bash
```
* GPU
@ -151,8 +150,8 @@ currently the containerized build options are supported as follows:
Then you can pull and run the latest stable image using the below command:
```
docker pull mindspore/mindspore-gpu:0.3.0-alpha
docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.3.0-alpha /bin/bash
docker pull mindspore/mindspore-gpu:0.5.0-beta
docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.5.0-beta /bin/bash
```
To test if the docker image works, please execute the python code below and check the output:
@ -187,7 +186,7 @@ please check out [docker](docker/README.md) repo for the details.
## Quickstart
See the [Quick Start](https://www.mindspore.cn/tutorial/en/0.3.0-alpha/quick_start/quick_start.html)
See the [Quick Start](https://www.mindspore.cn/tutorial/en/master/quick_start/quick_start.html)
to implement the image classification.
## Docs

72
RELEASE.md
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2
akg

@ -1 +1 @@
Subproject commit c460176523d039c8995f1d71089753725ebc0792
Subproject commit df57a6cf9450e347d1854687d1fe66a420ee3b35

38
build.sh
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@ -25,7 +25,7 @@ usage()
echo "Usage:"
echo "bash build.sh [-d] [-r] [-v] [-c on|off] [-t on|off] [-g on|off] [-h] [-b ge] [-m infer|train] \\"
echo " [-a on|off] [-Q on|off] [-p on|off] [-i] [-L] [-R] [-D on|off] [-j[n]] [-e gpu|d|cpu] \\"
echo " [-P on|off] [-z [on|off]] [-M on|off] [-V 9.2|10.1] [-I] [-K]"
echo " [-P on|off] [-z [on|off]] [-M on|off] [-V 9.2|10.1] [-I] [-K] [-B on|off] [-E]"
echo ""
echo "Options:"
echo " -d Debug mode"
@ -50,10 +50,12 @@ usage()
echo " -D Enable dumping of function graph ir, default on"
echo " -z Compile dataset & mindrecord, default on"
echo " -M Enable MPI and NCCL for GPU training, gpu default on"
echo " -V Specify the minimum required cuda version, default CUDA 9.2"
echo " -V Specify the minimum required cuda version, default CUDA 10.1"
echo " -I Compile predict, default off"
echo " -K Compile with AKG, default off"
echo " -K Compile with AKG, default on"
echo " -s Enable serving module, default off"
echo " -B Enable debugger, default off"
echo " -E Enable IBVERBS for parameter server, default off"
}
# check value of input is 'on' or 'off'
@ -88,14 +90,17 @@ checkopts()
ENABLE_DUMP_IR="on"
COMPILE_MINDDATA="on"
ENABLE_MPI="off"
CUDA_VERSION="9.2"
CUDA_VERSION="10.1"
COMPILE_PREDICT="off"
USE_GLOG="on"
PREDICT_PLATFORM=""
ENABLE_AKG="on"
ENABLE_SERVING="off"
ENABLE_DEBUGGER="off"
ENABLE_IBVERBS="off"
# Process the options
while getopts 'drvj:c:t:hsb:a:g:p:ie:m:I:LRP:Q:D:zM:V:K:s' opt
while getopts 'drvj:c:t:hsb:a:g:p:ie:m:I:LRP:Q:D:zM:V:K:sB:E' opt
do
OPTARG=$(echo ${OPTARG} | tr '[A-Z]' '[a-z]')
case "${opt}" in
@ -191,6 +196,10 @@ checkopts()
usage
exit 1
fi
if [[ "X$OPTARG" == "X9.2" ]]; then
echo "Unsupported CUDA version 9.2"
exit 1
fi
CUDA_VERSION="$OPTARG"
;;
P)
@ -240,6 +249,15 @@ checkopts()
ENABLE_SERVING="on"
echo "enable serving"
;;
B)
check_on_off $OPTARG B
ENABLE_DEBUGGER="on"
echo "enable debugger"
;;
E)
ENABLE_IBVERBS="on"
echo "enable IBVERBS for parameter server"
;;
*)
echo "Unknown option ${opt}!"
usage
@ -322,7 +340,13 @@ build_mindspore()
if [[ "X$ENABLE_SERVING" = "Xon" ]]; then
CMAKE_ARGS="${CMAKE_ARGS} -DENABLE_SERVING=ON"
fi
if [[ "X$ENABLE_DEBUGGER" = "Xon" ]]; then
CMAKE_ARGS="${CMAKE_ARGS} -DENABLE_DEBUGGER=ON"
fi
if [[ "X$ENABLE_IBVERBS" = "Xon" ]]; then
CMAKE_ARGS="${CMAKE_ARGS} -DENABLE_IBVERBS=ON"
fi
echo "${CMAKE_ARGS}"
if [[ "X$INC_BUILD" = "Xoff" ]]; then
cmake ${CMAKE_ARGS} ../..
@ -446,9 +470,9 @@ build_predict()
cd "${BASEPATH}/predict/output/"
if [[ "$PREDICT_PLATFORM" == "x86_64" ]]; then
tar -cf MSPredict-0.3.0-linux_x86_64.tar.gz include/ lib/ --warning=no-file-changed
tar -cf MSPredict-0.5.0-linux_x86_64.tar.gz include/ lib/ --warning=no-file-changed
elif [[ "$PREDICT_PLATFORM" == "arm64" ]]; then
tar -cf MSPredict-0.3.0-linux_aarch64.tar.gz include/ lib/ --warning=no-file-changed
tar -cf MSPredict-0.5.0-linux_aarch64.tar.gz include/ lib/ --warning=no-file-changed
fi
echo "success to build predict project!"
}

14
cmake/external_libs/absl.cmake
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@ -0,0 +1,14 @@
mindspore_add_pkg(absl
VER 20200225.2
LIBS absl_strings absl_throw_delegate absl_raw_logging_internal absl_int128 absl_bad_optional_access
URL https://github.com/abseil/abseil-cpp/archive/20200225.2.tar.gz
MD5 73f2b6e72f1599a9139170c29482ddc4
CMAKE_OPTION -DCMAKE_BUILD_TYPE:STRING=Release -DCMAKE_POSITION_INDEPENDENT_CODE:BOOL=TRUE)
include_directories(${absl_INC})
add_library(mindspore::absl_strings ALIAS absl::absl_strings)
add_library(mindspore::absl_throw_delegate ALIAS absl::absl_throw_delegate)
add_library(mindspore::absl_raw_logging_internal ALIAS absl::absl_raw_logging_internal)
add_library(mindspore::absl_int128 ALIAS absl::absl_int128)
add_library(mindspore::absl_bad_optional_access ALIAS absl::absl_bad_optional_access)

12
cmake/external_libs/c-ares.cmake
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@ -0,0 +1,12 @@
mindspore_add_pkg(c-ares
VER 1.15.0
LIBS cares
URL https://github.com/c-ares/c-ares/releases/download/cares-1_15_0/c-ares-1.15.0.tar.gz
MD5 d2391da274653f7643270623e822dff7
CMAKE_OPTION -DCMAKE_BUILD_TYPE:STRING=Release
-DCARES_SHARED:BOOL=OFF
-DCARES_STATIC:BOOL=ON
-DCARES_STATIC_PIC:BOOL=ON)
include_directories(${c-ares_INC})
add_library(mindspore::cares ALIAS c-ares::cares)

110
cmake/external_libs/grpc.cmake
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@ -0,0 +1,110 @@
set(grpc_USE_STATIC_LIBS ON)
if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
set(grpc_CXXFLAGS "-fstack-protector-all -Wno-uninitialized -Wno-unused-parameter -fPIC -fvisibility=hidden -D_FORTIFY_SOURCE=2 -O2")
elseif (${CMAKE_SYSTEM_NAME} MATCHES "Windows")
set(grpc_CXXFLAGS "-fstack-protector-all -Wno-maybe-uninitialized -Wno-unused-parameter -fPIC -fvisibility=hidden -D_FORTIFY_SOURCE=2 -O2")
else()
set(grpc_CXXFLAGS "-fstack-protector-all -Wno-maybe-uninitialized -Wno-unused-parameter -fPIC -fvisibility=hidden -D_FORTIFY_SOURCE=2 -D_GLIBCXX_USE_CXX11_ABI=0 -O2")
endif()
set(grpc_LDFLAGS "-Wl,-z,relro,-z,now,-z,noexecstack")
if (EXISTS ${protobuf_ROOT}/lib64)
set(_FINDPACKAGE_PROTOBUF_CONFIG_DIR "${protobuf_ROOT}/lib64/cmake/protobuf")
else()
set(_FINDPACKAGE_PROTOBUF_CONFIG_DIR "${protobuf_ROOT}/lib/cmake/protobuf")
endif()
message("grpc using Protobuf_DIR : " ${_FINDPACKAGE_PROTOBUF_CONFIG_DIR})
if (EXISTS ${absl_ROOT}/lib64)
set(_FINDPACKAGE_ABSL_CONFIG_DIR "${absl_ROOT}/lib64/cmake/absl")
else()
set(_FINDPACKAGE_ABSL_CONFIG_DIR "${absl_ROOT}/lib/cmake/absl")
endif()
message("grpc using absl_DIR : " ${_FINDPACKAGE_ABSL_CONFIG_DIR})
set(_CMAKE_ARGS_OPENSSL_ROOT_DIR "")
if (OPENSSL_ROOT_DIR)
set(_CMAKE_ARGS_OPENSSL_ROOT_DIR "-DOPENSSL_ROOT_DIR:PATH=${OPENSSL_ROOT_DIR}")
endif()
mindspore_add_pkg(grpc
VER 1.27.3
LIBS grpc++ grpc gpr upb address_sorting
EXE grpc_cpp_plugin
URL https://github.com/grpc/grpc/archive/v1.27.3.tar.gz
MD5 0c6c3fc8682d4262dd0e5e6fabe1a7e2
CMAKE_OPTION -DCMAKE_BUILD_TYPE:STRING=Release
-DgRPC_INSTALL:BOOL=ON
-DgRPC_BUILD_TESTS:BOOL=OFF
-DgRPC_PROTOBUF_PROVIDER:STRING=package
-DgRPC_PROTOBUF_PACKAGE_TYPE:STRING=CONFIG
-DProtobuf_DIR:PATH=${_FINDPACKAGE_PROTOBUF_CONFIG_DIR}
-DgRPC_ZLIB_PROVIDER:STRING=package
-DZLIB_ROOT:PATH=${zlib_ROOT}
-DgRPC_ABSL_PROVIDER:STRING=package
-Dabsl_DIR:PATH=${_FINDPACKAGE_ABSL_CONFIG_DIR}
-DgRPC_CARES_PROVIDER:STRING=package
-Dc-ares_DIR:PATH=${c-ares_ROOT}/lib/cmake/c-ares
-DgRPC_SSL_PROVIDER:STRING=package
${_CMAKE_ARGS_OPENSSL_ROOT_DIR}
)
include_directories(${grpc_INC})
add_library(mindspore::grpc++ ALIAS grpc::grpc++)
# link other grpc libs
target_link_libraries(grpc::grpc++ INTERFACE grpc::grpc grpc::gpr grpc::upb grpc::address_sorting)
# link built dependencies
target_link_libraries(grpc::grpc++ INTERFACE mindspore::z)
target_link_libraries(grpc::grpc++ INTERFACE mindspore::cares)
target_link_libraries(grpc::grpc++ INTERFACE mindspore::absl_strings mindspore::absl_throw_delegate
mindspore::absl_raw_logging_internal mindspore::absl_int128 mindspore::absl_bad_optional_access)
# link system openssl
find_package(OpenSSL REQUIRED)
target_link_libraries(grpc::grpc++ INTERFACE OpenSSL::SSL OpenSSL::Crypto)
function(ms_grpc_generate c_var h_var)
if(NOT ARGN)
message(SEND_ERROR "Error: ms_grpc_generate() called without any proto files")
return()
endif()
set(${c_var})
set(${h_var})
foreach(file ${ARGN})
get_filename_component(abs_file ${file} ABSOLUTE)
get_filename_component(file_name ${file} NAME_WE)
get_filename_component(file_dir ${abs_file} PATH)
file(RELATIVE_PATH rel_path ${CMAKE_CURRENT_SOURCE_DIR} ${file_dir})
list(APPEND ${c_var} "${CMAKE_BINARY_DIR}/proto/${file_name}.pb.cc")
list(APPEND ${h_var} "${CMAKE_BINARY_DIR}/proto/${file_name}.pb.h")
list(APPEND ${c_var} "${CMAKE_BINARY_DIR}/proto/${file_name}.grpc.pb.cc")
list(APPEND ${h_var} "${CMAKE_BINARY_DIR}/proto/${file_name}.grpc.pb.h")
add_custom_command(
OUTPUT "${CMAKE_BINARY_DIR}/proto/${file_name}.pb.cc"
"${CMAKE_BINARY_DIR}/proto/${file_name}.pb.h"
"${CMAKE_BINARY_DIR}/proto/${file_name}.grpc.pb.cc"
"${CMAKE_BINARY_DIR}/proto/${file_name}.grpc.pb.h"
WORKING_DIRECTORY ${PROJECT_SOURCE_DIR}
COMMAND ${CMAKE_COMMAND} -E make_directory "${CMAKE_BINARY_DIR}/proto"
COMMAND protobuf::protoc --version
COMMAND protobuf::protoc -I${file_dir} --cpp_out=${CMAKE_BINARY_DIR}/proto
--grpc_out=${CMAKE_BINARY_DIR}/proto --plugin=protoc-gen-grpc=$<TARGET_FILE:grpc::grpc_cpp_plugin> ${abs_file}
DEPENDS protobuf::protoc grpc::grpc_cpp_plugin ${abs_file}
COMMENT "Running C++ gRPC compiler on ${file}" VERBATIM)
endforeach()
set_source_files_properties(${${c_var}} ${${h_var}} PROPERTIES GENERATED TRUE)
set(${c_var} ${${c_var}} PARENT_SCOPE)
set(${h_var} ${${h_var}} PARENT_SCOPE)
endfunction()

14
cmake/external_libs/pslite.cmake
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@ -0,0 +1,14 @@
set(pslite_USE_STATIC_LIBS ON)
if (${ENABLE_IBVERBS} STREQUAL "ON")
set(pslite_CXXFLAGS "USE_IBVERBS=1")
endif()
mindspore_add_pkg(pslite
LIBS ps
URL https://github.com/dmlc/ps-lite/archive/34fd45cae457d59850fdcb2066467778d0673f21.zip
MD5 393c0e27b68bfaf96718caa3aa96f5a3
PATCHES ${CMAKE_SOURCE_DIR}/third_party/patch/pslite/ps_lite.patch001
ONLY_MAKE True
ONLY_MAKE_INCS include/*
ONLY_MAKE_LIBS build/*)
include_directories(${pslite_INC})
add_library(mindspore::pslite ALIAS pslite::ps)

5
cmake/external_libs/zeromq.cmake
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@ -0,0 +1,5 @@
mindspore_add_pkg(zeromq
VER 4.1.4
HEAD_ONLY ./
URL https://raw.githubusercontent.com/mli/deps/master/build/zeromq-4.1.4.tar.gz
MD5 a611ecc93fffeb6d058c0e6edf4ad4fb)

9
cmake/external_libs/zlib.cmake
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@ -0,0 +1,9 @@
mindspore_add_pkg(zlib
VER 1.2.11
LIBS z
URL https://github.com/madler/zlib/archive/v1.2.11.tar.gz
MD5 0095d2d2d1f3442ce1318336637b695f
CMAKE_OPTION -DCMAKE_BUILD_TYPE:STRING=Release)
include_directories(${zlib_INC})
add_library(mindspore::z ALIAS zlib::z)

14
cmake/mind_expression.cmake
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@ -14,12 +14,26 @@ include(${CMAKE_SOURCE_DIR}/cmake/external_libs/eigen.cmake)
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/json.cmake)
include(${CMAKE_SOURCE_DIR}/cmake/dependency_securec.cmake)
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/protobuf.cmake)
if (ENABLE_DEBUGGER)
# build dependencies of gRPC
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/absl.cmake)
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/c-ares.cmake)
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/zlib.cmake)
# build gRPC
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/grpc.cmake)
endif()
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/pybind11.cmake)
MESSAGE("go to link flatbuffers")
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/flatbuffers.cmake)
if(USE_GLOG)
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/glog.cmake)
endif()
if (NOT ${CMAKE_SYSTEM_NAME} MATCHES "Windows")
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/zeromq.cmake)
include(${CMAKE_SOURCE_DIR}/cmake/external_libs/pslite.cmake)
endif()
find_package(Python3)
include_directories(${Python3_INCLUDE_DIRS})

6
cmake/options.cmake
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@ -17,6 +17,8 @@ option(ENABLE_DUMP_E2E "Enable dump e2e file, default on" OFF)
option(ENABLE_DUMP_IR "Enable dump funciton graph ir, default on" ON)
option(ENABLE_MPI "enable mpi" OFF)
option(ENABLE_AKG "enable akg" OFF)
option(ENABLE_DEBUGGER "enable debugger" OFF)
option(ENABLE_IBVERBS "enable IBVERBS for parameter server" OFF)
if (CMAKE_CXX_COMPILER_ID STREQUAL "GNU")
if (WIN32)
@ -112,3 +114,7 @@ endif()
if(ENABLE_DUMP_E2E)
add_compile_definitions(ENABLE_DUMP_E2E)
endif()
if(ENABLE_DEBUGGER)
add_compile_definitions(ENABLE_DEBUGGER)
endif()

5
cmake/package.cmake
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@ -128,6 +128,11 @@ if (ENABLE_MPI)
DESTINATION ${INSTALL_BASE_DIR}
COMPONENT mindspore
)
install(
TARGETS mpi_adapter
DESTINATION ${INSTALL_LIB_DIR}
COMPONENT mindspore
)
endif ()
if (ENABLE_GPU)

14
cmake/utils.cmake
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@ -206,7 +206,7 @@ function(mindspore_add_pkg pkg_name )
set(options )
set(oneValueArgs URL MD5 GIT_REPOSITORY GIT_TAG VER EXE DIR HEAD_ONLY CMAKE_PATH RELEASE LIB_PATH CUSTOM_CMAKE)
set(multiValueArgs CMAKE_OPTION LIBS PRE_CONFIGURE_COMMAND CONFIGURE_COMMAND BUILD_OPTION INSTALL_INCS INSTALL_LIBS PATCHES SUBMODULES SOURCEMODULES)
set(multiValueArgs CMAKE_OPTION LIBS PRE_CONFIGURE_COMMAND CONFIGURE_COMMAND BUILD_OPTION INSTALL_INCS INSTALL_LIBS PATCHES SUBMODULES SOURCEMODULES ONLY_MAKE ONLY_MAKE_INCS ONLY_MAKE_LIBS)
cmake_parse_arguments(PKG "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN} )
if (NOT PKG_LIB_PATH)
@ -290,7 +290,7 @@ function(mindspore_add_pkg pkg_name )
foreach(_PATCH_FILE ${PKG_PATCHES})
get_filename_component(_PATCH_FILE_NAME ${_PATCH_FILE} NAME)
set(_LF_PATCH_FILE ${CMAKE_BINARY_DIR}/_ms_patch/${_PATCH_FILE_NAME})
configure_file(${_PATCH_FILE} ${_LF_PATCH_FILE} NEWLINE_STYLE LF)
configure_file(${_PATCH_FILE} ${_LF_PATCH_FILE} NEWLINE_STYLE LF @ONLY)
message("patching ${${pkg_name}_SOURCE_DIR} -p1 < ${_LF_PATCH_FILE}")
execute_process(COMMAND ${Patch_EXECUTABLE} -p1 INPUT_FILE ${_LF_PATCH_FILE}
@ -324,6 +324,16 @@ function(mindspore_add_pkg pkg_name )
target_include_directories(${pkg_name} INTERFACE ${${pkg_name}_INC})
endif ()
elseif (PKG_ONLY_MAKE)
__exec_cmd(COMMAND ${CMAKE_MAKE_PROGRAM} ${${pkg_name}_CXXFLAGS} -j${THNUM}
WORKING_DIRECTORY ${${pkg_name}_SOURCE_DIR})
set(PKG_INSTALL_INCS ${PKG_ONLY_MAKE_INCS})
set(PKG_INSTALL_LIBS ${PKG_ONLY_MAKE_LIBS})
file(GLOB ${pkg_name}_INSTALL_INCS ${${pkg_name}_SOURCE_DIR}/${PKG_INSTALL_INCS})
file(GLOB ${pkg_name}_INSTALL_LIBS ${${pkg_name}_SOURCE_DIR}/${PKG_INSTALL_LIBS})
file(COPY ${${pkg_name}_INSTALL_INCS} DESTINATION ${${pkg_name}_BASE_DIR}/include)
file(COPY ${${pkg_name}_INSTALL_LIBS} DESTINATION ${${pkg_name}_BASE_DIR}/lib)
elseif (PKG_CMAKE_OPTION)
# in cmake
file(MAKE_DIRECTORY ${${pkg_name}_SOURCE_DIR}/_build)

67
docker/mindspore-cpu/0.5.0-beta/Dockerfile
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@ -0,0 +1,67 @@
FROM ubuntu:18.04
MAINTAINER leonwanghui <leon.wanghui@huawei.com>
# Set env
ENV PYTHON_ROOT_PATH /usr/local/python-3.7.5
ENV PATH /usr/local/bin:$PATH
# Install base tools
RUN apt update \
&& DEBIAN_FRONTEND=noninteractive apt install -y \
vim \
wget \
curl \
xz-utils \
net-tools \
openssh-client \
git \
ntpdate \
tzdata \
tcl \
sudo \
bash-completion
# Install compile tools
RUN DEBIAN_FRONTEND=noninteractive apt install -y \
gcc \
g++ \
zlibc \
make \
libgmp-dev \
patch \
autoconf \
libtool \
automake \
flex
# Set bash
RUN echo "dash dash/sh boolean false" | debconf-set-selections
RUN DEBIAN_FRONTEND=noninteractive dpkg-reconfigure dash
# Install python (v3.7.5)
RUN apt install -y libffi-dev libssl-dev zlib1g-dev libbz2-dev libncurses5-dev \
libgdbm-dev libgdbm-compat-dev liblzma-dev libreadline-dev libsqlite3-dev \
&& cd /tmp \
&& wget https://github.com/python/cpython/archive/v3.7.5.tar.gz \
&& tar -xvf v3.7.5.tar.gz \
&& cd /tmp/cpython-3.7.5 \
&& mkdir -p ${PYTHON_ROOT_PATH} \
&& ./configure --prefix=${PYTHON_ROOT_PATH} \
&& make -j4 \
&& make install -j4 \
&& rm -f /usr/local/bin/python \
&& rm -f /usr/local/bin/pip \
&& ln -s ${PYTHON_ROOT_PATH}/bin/python3.7 /usr/local/bin/python \
&& ln -s ${PYTHON_ROOT_PATH}/bin/pip3.7 /usr/local/bin/pip \
&& rm -rf /tmp/cpython-3.7.5 \
&& rm -f /tmp/v3.7.5.tar.gz
# Set pip source
RUN mkdir -pv /root/.pip \
&& echo "[global]" > /root/.pip/pip.conf \
&& echo "trusted-host=mirrors.aliyun.com" >> /root/.pip/pip.conf \
&& echo "index-url=http://mirrors.aliyun.com/pypi/simple/" >> /root/.pip/pip.conf
# Install MindSpore cpu whl package
RUN pip install --no-cache-dir https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.5.0-beta/MindSpore/cpu/ubuntu_x86/mindspore-0.5.0-cp37-cp37m-linux_x86_64.whl

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docker/mindspore-gpu/0.5.0-beta/Dockerfile
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@ -0,0 +1,83 @@
FROM nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04
MAINTAINER leonwanghui <leon.wanghui@huawei.com>
# Set env
ENV PYTHON_ROOT_PATH /usr/local/python-3.7.5
ENV OMPI_ROOT_PATH /usr/local/openmpi-3.1.5
ENV PATH ${OMPI_ROOT_PATH}/bin:/usr/local/bin:$PATH
ENV LD_LIBRARY_PATH ${OMPI_ROOT_PATH}/lib:$LD_LIBRARY_PATH
# Install base tools
RUN apt update \
&& DEBIAN_FRONTEND=noninteractive apt install -y \
vim \
wget \
curl \
xz-utils \
net-tools \
openssh-client \
git \
ntpdate \
tzdata \
tcl \
sudo \
bash-completion
# Install compile tools
RUN DEBIAN_FRONTEND=noninteractive apt install -y \
gcc \
g++ \
zlibc \
make \
libgmp-dev \
patch \
autoconf \
libtool \
automake \
flex \
libnccl2=2.4.8-1+cuda10.1 \
libnccl-dev=2.4.8-1+cuda10.1
# Set bash
RUN echo "dash dash/sh boolean false" | debconf-set-selections
RUN DEBIAN_FRONTEND=noninteractive dpkg-reconfigure dash
# Install python (v3.7.5)
RUN apt install -y libffi-dev libssl-dev zlib1g-dev libbz2-dev libncurses5-dev \
libgdbm-dev libgdbm-compat-dev liblzma-dev libreadline-dev libsqlite3-dev \
&& cd /tmp \
&& wget https://github.com/python/cpython/archive/v3.7.5.tar.gz \
&& tar -xvf v3.7.5.tar.gz \
&& cd /tmp/cpython-3.7.5 \
&& mkdir -p ${PYTHON_ROOT_PATH} \
&& ./configure --prefix=${PYTHON_ROOT_PATH} \
&& make -j4 \
&& make install -j4 \
&& rm -f /usr/local/bin/python \
&& rm -f /usr/local/bin/pip \
&& ln -s ${PYTHON_ROOT_PATH}/bin/python3.7 /usr/local/bin/python \
&& ln -s ${PYTHON_ROOT_PATH}/bin/pip3.7 /usr/local/bin/pip \
&& rm -rf /tmp/cpython-3.7.5 \
&& rm -f /tmp/v3.7.5.tar.gz
# Set pip source
RUN mkdir -pv /root/.pip \
&& echo "[global]" > /root/.pip/pip.conf \
&& echo "trusted-host=mirrors.aliyun.com" >> /root/.pip/pip.conf \
&& echo "index-url=http://mirrors.aliyun.com/pypi/simple/" >> /root/.pip/pip.conf
# Install openmpi (v3.1.5)
RUN cd /tmp \
&& wget https://download.open-mpi.org/release/open-mpi/v3.1/openmpi-3.1.5.tar.gz \
&& tar -xvf openmpi-3.1.5.tar.gz \
&& cd /tmp/openmpi-3.1.5 \
&& mkdir -p ${OMPI_ROOT_PATH} \
&& ./configure --prefix=${OMPI_ROOT_PATH} \
&& make -j4 \
&& make install -j4 \
&& rm -rf /tmp/openmpi-3.1.5 \
&& rm -f /tmp/openmpi-3.1.5.tar.gz
# Install MindSpore cuda-10.1 whl package
RUN pip install --no-cache-dir https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.5.0-beta/MindSpore/gpu/ubuntu_x86/cuda-10.1/mindspore_gpu-0.5.0-cp37-cp37m-linux_x86_64.whl

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example/nlp_to_mindrecord/CLUERNER2020/README.md
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# Guideline to Convert Training Data CLUERNER2020 to MindRecord For Bert Fine Tuning
<!-- TOC -->
- [What does the example do](#what-does-the-example-do)
- [How to use the example to process CLUERNER2020](#how-to-use-the-example-to-process-cluerner2020)
- [Download CLUERNER2020 and unzip](#download-cluerner2020-and-unzip)
- [Generate MindRecord](#generate-mindrecord)
- [Create MindDataset By MindRecord](#create-minddataset-by-mindrecord)
<!-- /TOC -->
## What does the example do
This example is based on [CLUERNER2020](https://www.cluebenchmarks.com/introduce.html) training data, generating MindRecord file, and finally used for Bert Fine Tuning progress.
1. run.sh: generate MindRecord entry script
2. run_read.py: create MindDataset by MindRecord entry script.
- create_dataset.py: use MindDataset to read MindRecord to generate dataset.
## How to use the example to process CLUERNER2020
Download CLUERNER2020, convert it to MindRecord, use MindDataset to read MindRecord.
### Download CLUERNER2020 and unzip
1. Download the training data zip.
> [CLUERNER2020 dataset download address](https://www.cluebenchmarks.com/introduce.html) **-> 任务介绍 -> CLUENER 细粒度命名实体识别 -> cluener下载链接**
2. Unzip the training data to dir example/nlp_to_mindrecord/CLUERNER2020/cluener_public.
```
unzip -d {your-mindspore}/example/nlp_to_mindrecord/CLUERNER2020/data/cluener_public cluener_public.zip
```
### Generate MindRecord
1. Run the run.sh script.
```bash
bash run.sh
```
2. Output like this:
```
...
[INFO] ME(17603:139620983514944,MainProcess):2020-04-28-16:56:12.498.235 [mindspore/mindrecord/filewriter.py:313] The list of mindrecord files created are: ['data/train.mindrecord'], and the list of index files are: ['data/train.mindrecord.db']
...
[INFO] ME(17603,python):2020-04-28-16:56:13.400.175 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.400.863 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.401.534 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.402.179 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
[INFO] ME(17603,python):2020-04-28-16:56:13.402.702 [mindspore/ccsrc/mindrecord/io/shard_writer.cc:667] WriteRawData] Write 1 records successfully.
...
[INFO] ME(17603:139620983514944,MainProcess):2020-04-28-16:56:13.431.208 [mindspore/mindrecord/filewriter.py:313] The list of mindrecord files created are: ['data/dev.mindrecord'], and the list of index files are: ['data/dev.mindrecord.db']
```
3. Generate files like this:
```bash
$ ls output/
dev.mindrecord dev.mindrecord.db README.md train.mindrecord train.mindrecord.db
```
### Create MindDataset By MindRecord
1. Run the run_read.sh script.
```bash
bash run_read.sh
```
2. Output like this:
```
...
example 1340: input_ids: [ 101 3173 1290 4852 7676 3949 122 3299 123 126 3189 4510 8020 6381 5442 7357 2590 3636 8021 7676 3949 4294 1166 6121 3124 1277 6121 3124 7270 2135 3295 5789 3326 123 126 3189 1355 6134 1093 1325 3173 2399 6590 6791 8024 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1340: input_mask: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1340: segment_ids: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1340: label_ids: [ 0 18 19 20 2 4 0 0 0 0 0 0 0 34 36 26 27 28 0 34 35 35 35 35 35 35 35 35 35 36 26 27 28 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1341: input_ids: [ 101 1728 711 4293 3868 1168 2190 2150 3791 934 3633 3428 4638 6237 7025 8024 3297 1400 5310 3362 6206 5023 5401 1744 3297 7770 3791 7368 976 1139 1104 2137 511 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1341: input_mask: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1341: segment_ids: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 1341: label_ids: [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 18 19 19 19 19 20 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
...
```

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@ -1,36 +0,0 @@
# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
"""create MindDataset by MindRecord"""
import mindspore.dataset as ds
def create_dataset(data_file):
"""create MindDataset"""
num_readers = 4
data_set = ds.MindDataset(dataset_file=data_file, num_parallel_workers=num_readers, shuffle=True)
index = 0
for item in data_set.create_dict_iterator():
# print("example {}: {}".format(index, item))
print("example {}: input_ids: {}".format(index, item['input_ids']))
print("example {}: input_mask: {}".format(index, item['input_mask']))
print("example {}: segment_ids: {}".format(index, item['segment_ids']))
print("example {}: label_ids: {}".format(index, item['label_ids']))
index += 1
if index % 1000 == 0:
print("read rows: {}".format(index))
print("total rows: {}".format(index))
if __name__ == '__main__':
create_dataset('output/train.mindrecord')
create_dataset('output/dev.mindrecord')

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@ -1 +0,0 @@
cluener_public

1
example/nlp_to_mindrecord/CLUERNER2020/output/README.md
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@ -1 +0,0 @@
## output dir

40
example/nlp_to_mindrecord/CLUERNER2020/run.sh
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@ -1,40 +0,0 @@
#!/bin/bash
# Copyright 2020 Huawei Technologies Co., Ltd
#
# 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.
# ============================================================================
rm -f output/train.mindrecord*
rm -f output/dev.mindrecord*
if [ ! -d "../../../third_party/to_mindrecord/CLUERNER2020" ]; then
echo "The patch base dir ../../../third_party/to_mindrecord/CLUERNER2020 is not exist."
exit 1
fi
if [ ! -f "../../../third_party/patch/to_mindrecord/CLUERNER2020/data_processor_seq.patch" ]; then
echo "The patch file ../../../third_party/patch/to_mindrecord/CLUERNER2020/data_processor_seq.patch is not exist."
exit 1
fi
# patch for data_processor_seq.py
patch -p0 -d ../../../third_party/to_mindrecord/CLUERNER2020/ -o data_processor_seq_patched.py < ../../../third_party/patch/to_mindrecord/CLUERNER2020/data_processor_seq.patch
if [ $? -ne 0 ]; then
echo "Patch ../../../third_party/to_mindrecord/CLUERNER2020/data_processor_seq.py failed"
exit 1
fi
# use patched script
python ../../../third_party/to_mindrecord/CLUERNER2020/data_processor_seq_patched.py \
--vocab_file=../../../third_party/to_mindrecord/CLUERNER2020/vocab.txt \
--label2id_file=../../../third_party/to_mindrecord/CLUERNER2020/label2id.json

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@ -1 +0,0 @@
## The input dataset

173
example/nlp_to_mindrecord/enwiki/README.md
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@ -1,173 +0,0 @@
# Guideline to Convert Training Data enwiki to MindRecord For Bert Pre Training
<!-- TOC -->
- [What does the example do](#what-does-the-example-do)
- [How to use the example to process enwiki](#how-to-use-the-example-to-process-enwiki)
- [Download enwiki training data](#download-enwiki-training-data)
- [Process the enwiki](#process-the-enwiki)
- [Generate MindRecord](#generate-mindrecord)
- [Create MindDataset By MindRecord](#create-minddataset-by-mindrecord)
<!-- /TOC -->
## What does the example do
This example is based on [enwiki](https://dumps.wikimedia.org/enwiki) training data, generating MindRecord file, and finally used for Bert network training.
1. run.sh: generate MindRecord entry script.
2. run_read.py: create MindDataset by MindRecord entry script.
- create_dataset.py: use MindDataset to read MindRecord to generate dataset.
## How to use the example to process enwiki
Download enwiki data, process it, convert it to MindRecord, use MindDataset to read MindRecord.
### Download enwiki training data
> [enwiki dataset download address](https://dumps.wikimedia.org/enwiki) **-> 20200501 -> enwiki-20200501-pages-articles-multistream.xml.bz2**
### Process the enwiki
1. Please follow the steps in [process enwiki](https://github.com/mlperf/training/tree/master/language_model/tensorflow/bert)
- All permissions of this step belong to the link address website.
### Generate MindRecord
1. Run the run.sh script.
```
bash run.sh input_dir output_dir vocab_file
```
- input_dir: the directory which contains files like 'part-00251-of-00500'.
- output_dir: which will store the output mindrecord files.
- vocab_file: the vocab file which you can download from other opensource project.
2. The output like this:
```
...
Begin preprocess Wed Jun 10 09:21:23 CST 2020
Begin preprocess input file: /mnt/data/results/part-00000-of-00500
Begin output file: part-00000-of-00500.mindrecord
Total task: 510, processing: 1
Begin preprocess input file: /mnt/data/results/part-00001-of-00500
Begin output file: part-00001-of-00500.mindrecord
Total task: 510, processing: 2
Begin preprocess input file: /mnt/data/results/part-00002-of-00500
Begin output file: part-00002-of-00500.mindrecord
Total task: 510, processing: 3
Begin preprocess input file: /mnt/data/results/part-00003-of-00500
Begin output file: part-00003-of-00500.mindrecord
Total task: 510, processing: 4
Begin preprocess input file: /mnt/data/results/part-00004-of-00500
Begin output file: part-00004-of-00500.mindrecord
Total task: 510, processing: 4
...
```
3. Generate files like this:
```bash
$ ls {your_output_dir}/
part-00000-of-00500.mindrecord part-00000-of-00500.mindrecord.db part-00001-of-00500.mindrecord part-00001-of-00500.mindrecord.db part-00002-of-00500.mindrecord part-00002-of-00500.mindrecord.db ...
```
### Create MindDataset By MindRecord
1. Run the run_read.sh script.
```bash
bash run_read.sh input_dir
```
- input_dir: the directory which contains mindrecord files.
2. The output like this:
```
...
example 633: input_ids: [ 101 2043 19781 4305 2140 4520 2041 1010 103 2034 2455 2002
7879 2003 1996 2455 1997 103 26378 4160 1012 102 7291 2001
1996 103 1011 2343 1997 6327 1010 3423 1998 103 4262 2005
1996 2118 1997 2329 3996 103 102 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0]
example 633: input_mask: [1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 633: segment_ids: [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
example 633: masked_lm_positions: [ 8 17 20 25 33 41 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0]
example 633: masked_lm_ids: [ 1996 16137 1012 3580 2451 1012 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0]
example 633: masked_lm_weights: [1. 1. 1. 1. 1. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.
0. 0. 0. 0.]
example 633: next_sentence_labels: [1]
...
```

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