• 说明

说明

libtorch使用MSVC编译，需要本机安装，并在IDE中使用MSVC工具链。

下载官方libtorch包，或者本机安装了python环境，并且安装了pytorch。（pytorch核心是c++编写的，pytorch包含了libtorch的所有内容）

编译最好使用与libtorch相同的版本，debug/release，避免各种链接问题。下面的配置中是读取的torch_home环境变量进行获取的libtorch包目录，可以手动配置。

如果是python环境安装的pytorch，可以在python中使用以下方式获取torch_home:

import torch
print(torch.utils.cmake_prefix_path)

配置CMakeLists.txt:

set(torch_home $ENV{torch_home})

find_package(Torch 2.2.1 REQUIRED HINTS ${torch_home})
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")

add_executable(example-app example-app.cpp)
#add_library(example-app SHARED example-app.cpp)
target_link_libraries(example-app "${TORCH_LIBRARIES}")
set_property(TARGET example-app PROPERTY CXX_STANDARD 17)

# The following code block is suggested to be used on Windows.
# According to https://github.com/pytorch/pytorch/issues/25457,
# the DLLs need to be copied to avoid memory errors.
if (MSVC)
    message("MSVC, torch home:" ${TORCH_INSTALL_PREFIX})
    file(GLOB TORCH_DLLS "${TORCH_INSTALL_PREFIX}/lib/*.dll")
    add_custom_command(TARGET example-app
            POST_BUILD
            COMMAND ${CMAKE_COMMAND} -E copy_if_different
            ${TORCH_DLLS}
            $<TARGET_FILE_DIR:example-app>) # 放入目标所在的目录
endif (MSVC)

example-app.cpp

#include <torch/torch.h>
#include <iostream>

int main() {
    torch::Tensor tensor = torch::rand({2, 3});
    std::cout << tensor << std::endl;
}