C++ Libtorch与g+合作+；，但是英特尔编译器失败了

我想在Fortran程序中使用Python开发的神经网络（PyTorch）。我的操作系统是Ubuntu 18.04

我在做什么：

另存为torchscript:TurbNN.pt

从C++程序调用它：Call T.S.CPP，CalqTys.H

从FORTRAN程序调用B++程序（使用BIN）：MF.F90

我使用CMake（3.19.4）和g++（7.5.0）成功地编译了代码。但是，我无法使用英特尔编译器（HPCKit 2021.1.0.2684）编译它们：

在“cmake”之后，一切看起来都很好（就像g++）：

然而，在“制造”之后，我得到：

Scanning dependencies of target call_ts_cpp
[ 25%] Building CXX object CMakeFiles/call_ts_cpp.dir/src/call_ts.cpp.o
[ 50%] Linking CXX shared library lib/libcall_ts_cpp.so
[ 50%] Built target call_ts_cpp
Scanning dependencies of target fortran_calls_ts.x
[ 75%] Building Fortran object CMakeFiles/fortran_calls_ts.x.dir/src/main.f90.o
[100%] Linking Fortran executable bin/fortran_calls_ts.x
lib/libcall_ts_cpp.so: undefined reference to `c10::Error::Error(c10::SourceLocation, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)'
lib/libcall_ts_cpp.so: undefined reference to `torch::jit::load(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, c10::optional<c10::Device>, std::unordered_map<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > > > >&)'
lib/libcall_ts_cpp.so: undefined reference to `c10::DeviceTypeName[abi:cxx11](c10::DeviceType, bool)'
lib/libcall_ts_cpp.so: undefined reference to `torch::jit::Object::find_method(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) const'
lib/libcall_ts_cpp.so: undefined reference to `torch::jit::Method::operator()(std::vector<c10::IValue, std::allocator<c10::IValue> >, std::unordered_map<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, c10::IValue, std::hash<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::equal_to<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > >, std::allocator<std::pair<std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const, c10::IValue> > > const&)'
CMakeFiles/fortran_calls_ts.x.dir/build.make:106: recipe for target 'bin/fortran_calls_ts.x' failed
make[2]: *** [bin/fortran_calls_ts.x] Error 1
CMakeFiles/Makefile2:123: recipe for target 'CMakeFiles/fortran_calls_ts.x.dir/all' failed
make[1]: *** [CMakeFiles/fortran_calls_ts.x.dir/all] Error 2
Makefile:148: recipe for target 'all' failed
make: *** [all] Error 2

梅因。f90

! fortran program main
!
! calls c++ function invariant_nn, which calls a torchscript with
! a neural network
!

program main

    ! define interface to interact with c++
    use, intrinsic :: iso_c_binding, only: c_float
    implicit none
    interface invariant_nn
        subroutine invariant_nn(I, G) bind (c)
            import :: c_float
            real(c_float) :: I(5)
            real(c_float) :: G(10)
        end subroutine
    end interface

    ! fortran program
    real(4) I(5), G(10)

    ! invariants
    I(1) = 1.01
    I(2) = 1.01
    I(3) = 1.01
    I(4) = 1.01
    I(5) = 1.01
    print *, "Tensor invariants ", I

    ! tensor basis coefficients
    call invariant_nn(I, G)    
    print *, "Tensor basis coefficients ", G

end program main

CMakeLists.txt

# stop configuration if cmake version is below 3.0
cmake_minimum_required(VERSION 3.0 FATAL_ERROR)

# project name and enabled languages
project(fortran_calls_ts CXX Fortran)

# find libtorch
find_package(Torch REQUIRED)

# if CMAKE_BUILD_TYPE undefined, set it to Release
if(NOT CMAKE_BUILD_TYPE)
    set(CMAKE_BUILD_TYPE "Release")
endif()

# compiler flags for release mode
set(CMAKE_CXX_FLAGS_RELEASE "-O3")
set(CMAKE_Fortran_FLAGS_RELEASE "-O3")

# set default build paths
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_BINARY_DIR}/bin)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${PROJECT_BINARY_DIR}/lib)

# generated export header will be placed here
include_directories(${PROJECT_BINARY_DIR})

# c library
add_library(call_ts_cpp SHARED src/call_ts.cpp)

# fortran executable
add_executable(fortran_calls_ts.x src/main.f90)

# linked against c library
target_link_libraries(fortran_calls_ts.x call_ts_cpp)
target_link_libraries(call_ts_cpp "${TORCH_LIBRARIES}")

# we let cmake generate the export header
include(GenerateExportHeader)
generate_export_header(call_ts_cpp BASE_NAME call_ts)

install(TARGETS call_ts_cpp LIBRARY DESTINATION lib ARCHIVE DESTINATION lib)

install(FILES src/call_ts.h ${PROJECT_BINARY_DIR}/call_ts_export.h DESTINATION include)

set_property(TARGET fortran_calls_ts.x PROPERTY CXX_STANDARD 14)

---

您是否在链接器错误中看到

cxx11

？看起来您的

libcall\u ts\u cpp

的编译方式需要新的C++11 ABI for std:：string，但实现这些函数的库可能是用旧的ABI编译的。这里有一篇关于同样问题的PyTorch论坛帖子：

---

解决方案是下载使用新的C++11 ABI构建的PyTorch库的新副本。

在链接器错误中是否看到

cxx11

？看起来您的

libcall\u ts\u cpp

的编译方式需要新的C++11 ABI for std:：string，但实现这些函数的库可能是用旧的ABI编译的。这里有一篇关于同样问题的PyTorch论坛帖子：

---

解决方案是下载使用新的C++11 ABI构建的PyTorch库的新副本。

“我在使用旧的g++时解决了类似的问题”-当时的问题是什么，您是如何解决的？问题是：lib/libcall_ts_cpp.so：对'c10:：Error:：Error（c10:：SourceLocation，std:xx11:：basic_string'）的未定义引用，等等（请参阅“make”命令之后的内容）。对于g++来说，只需更新它即可修复。“我在使用旧的g++时修复了类似的问题”-当时的问题是什么，您是如何解决的？问题是：lib/libcall\u ts\u cpp.so：未定义对`c10:：Error:：Error（c10:：SourceLocation，std:\u cx11:：basic\u string'）的引用，等等（请参阅“make”命令之后的内容）。对于g++来说，它只是通过更新来修复的。谢谢你的回答。我很愚蠢。我尝试使用最新版本的Torchlib和夜间版本。但是，我不知道有两个版本可用：cxx11之前的ABI和cxx11 ABI。我总是下载第一个，但第二个对我有效！@arsen如果这解决了你的问题c单击复选标记并接受it@Yakk-AdamNevraumont谢谢，完成了。我不知道我应该这么做。谢谢你的回答。我很愚蠢。我试图使用最新版本的Torchlib和nightly版本。但是，我不知道有两个版本可用：cxx11之前的ABI和cxx11 ABI。我总是下载第一个版本，但是第二个对我有用！@arsen如果这解决了你的问题，请单击复选标记并接受it@Yakk-AdamNevraumont谢谢，完成了。我不知道我应该这么做。

#include "call_ts.h"
#include <torch/script.h>
#include <iostream>
#include <memory>

// c++ function invariant_nn
//
// takes inputs, reads a neural network TurbNN.pt, do a forward pass
// and returns outputs
//
// inputs: 5 tensor invariants I[0:4] (float)
// outputs: 10 tensor basis coefficients G[0:9] (float)

void invariant_nn(float I[], float G[])
{
    // deserialize scriptmodule from a .pt file
    torch::jit::script::Module module;
    const char *arg;
    arg = "../src/TurbNN.pt";
    module = torch::jit::load(arg);

    // create inputs
    std::vector<torch::jit::IValue> inputs;
    float data[] = {I[0], I[1], I[2], I[3], I[4]};
    inputs.push_back(torch::from_blob(data, {1, 5}));
    //std::cout << "inputs\n" << inputs;
    //std::cout << "\n";

    // do forward pass and turn its output into a tensor
    at::Tensor outputs = module.forward(inputs).toTensor();
    //std::cout << "outputs\n" << outputs;
    //std::cout << "\n";

    // return values
    for (int k = 0; k < 10; k++) {
        G[k] = outputs[0][k].item().to<float>();
        //std::cout << "G\n" << G[k];
    }

    return;
}

#pragma once

/* export macros for library generated by CMake */
#ifndef CALL_TS_API
#include "call_ts_export.h"
#define CALL_TS_API CALL_TS_EXPORT
#endif

#ifdef __cplusplus
extern "C" {
#endif

CALL_TS_API
void invariant_nn(float I[], float G[]);

#ifdef __cplusplus
}
#endif

! fortran program main
!
! calls c++ function invariant_nn, which calls a torchscript with
! a neural network
!

program main

    ! define interface to interact with c++
    use, intrinsic :: iso_c_binding, only: c_float
    implicit none
    interface invariant_nn
        subroutine invariant_nn(I, G) bind (c)
            import :: c_float
            real(c_float) :: I(5)
            real(c_float) :: G(10)
        end subroutine
    end interface

    ! fortran program
    real(4) I(5), G(10)

    ! invariants
    I(1) = 1.01
    I(2) = 1.01
    I(3) = 1.01
    I(4) = 1.01
    I(5) = 1.01
    print *, "Tensor invariants ", I

    ! tensor basis coefficients
    call invariant_nn(I, G)    
    print *, "Tensor basis coefficients ", G

end program main

# stop configuration if cmake version is below 3.0
cmake_minimum_required(VERSION 3.0 FATAL_ERROR)

# project name and enabled languages
project(fortran_calls_ts CXX Fortran)

# find libtorch
find_package(Torch REQUIRED)

# if CMAKE_BUILD_TYPE undefined, set it to Release
if(NOT CMAKE_BUILD_TYPE)
    set(CMAKE_BUILD_TYPE "Release")
endif()

# compiler flags for release mode
set(CMAKE_CXX_FLAGS_RELEASE "-O3")
set(CMAKE_Fortran_FLAGS_RELEASE "-O3")

# set default build paths
set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_BINARY_DIR}/bin)
set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${PROJECT_BINARY_DIR}/lib)

# generated export header will be placed here
include_directories(${PROJECT_BINARY_DIR})

# c library
add_library(call_ts_cpp SHARED src/call_ts.cpp)

# fortran executable
add_executable(fortran_calls_ts.x src/main.f90)

# linked against c library
target_link_libraries(fortran_calls_ts.x call_ts_cpp)
target_link_libraries(call_ts_cpp "${TORCH_LIBRARIES}")

# we let cmake generate the export header
include(GenerateExportHeader)
generate_export_header(call_ts_cpp BASE_NAME call_ts)

install(TARGETS call_ts_cpp LIBRARY DESTINATION lib ARCHIVE DESTINATION lib)

install(FILES src/call_ts.h ${PROJECT_BINARY_DIR}/call_ts_export.h DESTINATION include)

set_property(TARGET fortran_calls_ts.x PROPERTY CXX_STANDARD 14)