CMAKE_step4:安装与测试

CMake构建与测试实践
已于 2022-05-05 22:38:50 修改
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CC 4.0 BY-SA版权
分类专栏： CMAKE QT 文章标签： c++
于 2022-05-05 22:00:50 首次发布
版权声明：本文为博主原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接和本声明。
本文链接：https://blog.youkuaiyun.com/zkmrobot/article/details/124598642
本文详细介绍了CMake在构建库和主程序过程中的应用，包括CMakeLists.txt的配置，以及如何进行编译、安装和测试。通过示例展示了如何添加测试用例，并使用ctest进行测试验证，所有测试均成功通过。

1.安装涉及到两部分：一是库的安装；另一个是主程序的安装；

库函数包括库与头文件；

  • MathFunctions目录下CMakeLists.txt内容

add_library(MathFunctions mysqrt.cxx)

target_include_directories(MathFunctions
          INTERFACE ${CMAKE_CURRENT_SOURCE_DIR}
          )

install(TARGETS MathFunctions DESTINATION lib)
install(FILES MathFunctions.h DESTINATION include)

主程序包含主程序与配置文件

  • 主程序CMakeLists.txt

cmake_minimum_required(VERSION 3.10)

#set the project name and version
project(Tutorial VERSION 1.0)

#specify the C++ standard
set(CMAKE_CXX_STANDARD 11)
set(CMAKE_CXX_STANDARD_REQUIRED True)

option(USE_MYMATH "Use tutorial provided math implementa

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'ADAPTER_OBJ_LIST=$<TARGET_OBJECTS:adap_obj>$<TARGET_OBJECTS:adapter_alarm_obj>$<TARGET_OBJECTS:adapter_ethercat_obj>$<TARGET_OBJECTS:adapter_elabel_obj>' LWIP_ENABLE= STATUS,CMAKE_CURRENT_SOURCE_DIR: D:/THS/Driver-TrackDriver_Platform/uniecp_prj default, AMD64 STATUS,ELF_COMMAND_OUTPUT_FILE: stm32h7_stepper_app -- Configuring done (0.0s) CMake Error at CMakeLists.txt:187 (add_executable): Cannot find source file: src/app/stepper/inc/app_timer_cfg.h Tried extensions .c .C .c++ .cc .cpp .cxx .cu .mpp .m .M .mm .ixx .cppm .ccm .cxxm .c++m .h .hh .h++ .hm .hpp .hxx .in .txx .f .F .for .f77 .f90 .f95 .f03 .hip .ispc CMake Error at CMakeLists.txt:187 (add_executable): No SOURCES given to target: uniecp_elf CMake Generate step failed. Build files cannot be regenerated correctly. Makefile:445: recipe for target 'cmake_check_build_system' failed mingw32-make.exe: *** [cmake_check_build_system] Error 1报错原因
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PowerShell 7 环境已加载 (版本: 7.5.2) PS C:\Users\Administrator\Desktop> cd E:\PyTorch_Build\pytorch PS E:\PyTorch_Build\pytorch> python -m venv rtx5070_env PS E:\PyTorch_Build\pytorch> .\rtx5070_env\Scripts\activate (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 创建虚拟环境 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python -m venv rtx5070_env Error: [Errno 13] Permission denied: 'E:\\PyTorch_Build\\pytorch\\rtx5070_env\\Scripts\\python.exe' (rtx5070_env) PS E:\PyTorch_Build\pytorch> .\rtx5070_env\Scripts\Activate.ps1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装构建依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install numpy ninja pybind11 typing_extensions pyyaml future setuptools Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2.2.6) Requirement already satisfied: ninja in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (1.13.0) Requirement already satisfied: pybind11 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (3.0.1) Requirement already satisfied: typing_extensions in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (4.15.0) Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (6.0.2) Requirement already satisfied: future in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (1.0.0) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # CUDA环境设置 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDA_PATH = "E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:Path = "$env:CUDA_PATH\bin;$env:Path" (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 配置构建 (rtx5070_env) PS E:\PyTorch_Build\pytorch> mkdir build -Force Directory: E:\PyTorch_Build\pytorch Mode LastWriteTime Length Name ---- ------------- ------ ---- da--- 2025/9/3 18:46 build (rtx5070_env) PS E:\PyTorch_Build\pytorch> cd build (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> cmake .. -G "Ninja" ` >> -DBUILD_PYTHON=ON ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON ` >> -DCUDNN_INCLUDE_DIR="E:\Program Files\NVIDIA\CUNND\v9.12\include\13.0" ` >> -DCUDNN_LIBRARY="E:\Program Files\NVIDIA\CUNND\v9.12\lib\13.0\x64\cudnn64_9.lib" ` >> -DTORCH_CUDA_ARCH_LIST="8.9" ` >> -DCMAKE_BUILD_TYPE=Release -- Configuring done (0.0s) CMake Error at CMakeLists.txt:5 (add_library): Cannot find source file: libshm_windows.cpp Tried extensions .c .C .c++ .cc .cpp .cxx .cu .mpp .m .M .mm .ixx .cppm .ccm .cxxm .c++m .h .hh .h++ .hm .hpp .hxx .in .txx .f .F .for .f77 .f90 .f95 .f03 .hip .ispc CMake Error at CMakeLists.txt:5 (add_library): No SOURCES given to target: shm_windows CMake Generate step failed. Build files cannot be regenerated correctly. (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> # 并行构建 (使用8个线程) (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> ninja install -j 8 [0/1] Re-running CMake... FAILED: [code=1] build.ninja E:/PyTorch_Build/pytorch/build/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/protobuf/cmake/cmake_install.cmake E:/PyTorch_Build/pytorch/build/confu-deps/pthreadpool/cmake_install.cmake E:/PyTorch_Build/pytorch/build/FXdiv/cmake_install.cmake E:/PyTorch_Build/pytorch/build/confu-deps/cpuinfo/cmake_install.cmake E:/PyTorch_Build/pytorch/build/confu-deps/XNNPACK/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/googletest/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/googletest/googlemock/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/googletest/googletest/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/benchmark/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/benchmark/src/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ittapi/cmake_install.cmake E:/PyTorch_Build/pytorch/build/confu-deps/FP16/cmake_install.cmake E:/PyTorch_Build/pytorch/build/confu-deps/psimd/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/onnx/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/common/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/cpu/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/cpu/x64/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/interface/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/fake/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/dnnl/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/graph_compiler/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/utils/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/examples/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/tests/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/fmt/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/kineto/libkineto/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/kineto/libkineto/third_party/dynolog/dynolog/src/ipcfabric/cmake_install.cmake E:/PyTorch_Build/pytorch/build/third_party/mimalloc/cmake_install.cmake E:/PyTorch_Build/pytorch/build/torch/headeronly/cmake_install.cmake E:/PyTorch_Build/pytorch/build/c10/cmake_install.cmake E:/PyTorch_Build/pytorch/build/c10/test/cmake_install.cmake E:/PyTorch_Build/pytorch/build/c10/benchmark/cmake_install.cmake E:/PyTorch_Build/pytorch/build/c10/cuda/cmake_install.cmake E:/PyTorch_Build/pytorch/build/c10/cuda/test/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/THC/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/quantized/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/nnapi/cmake_install.cmake E:/PyTorch_Build/pytorch/build/sleef/cmake_install.cmake E:/PyTorch_Build/pytorch/build/sleef/src/cmake_install.cmake E:/PyTorch_Build/pytorch/build/sleef/src/libm/cmake_install.cmake E:/PyTorch_Build/pytorch/build/sleef/src/common/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/test/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/core/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/serialize/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/utils/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/perfkernels/cmake_install.cmake E:/PyTorch_Build/pytorch/build/test_jit/cmake_install.cmake E:/PyTorch_Build/pytorch/build/test_nativert/cmake_install.cmake E:/PyTorch_Build/pytorch/build/test_inductor/cmake_install.cmake E:/PyTorch_Build/pytorch/build/test_api/cmake_install.cmake E:/PyTorch_Build/pytorch/build/test_lazy/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/torch/cmake_install.cmake E:/PyTorch_Build/pytorch/build/caffe2/torch/lib/libshm_windows/cmake_install.cmake E:/PyTorch_Build/pytorch/build/functorch/cmake_install.cmake E:/PyTorch_Build/pytorch/build/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/protobuf/cmake/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/confu-deps/pthreadpool/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/FXdiv/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/confu-deps/cpuinfo/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/confu-deps/XNNPACK/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/googletest/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/googletest/googlemock/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/googletest/googletest/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/benchmark/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/benchmark/src/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ittapi/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/confu-deps/FP16/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/confu-deps/psimd/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/onnx/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/common/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/cpu/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/cpu/x64/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/interface/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/fake/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/dnnl/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/backend/graph_compiler/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/src/graph/utils/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/examples/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/ideep/mkl-dnn/tests/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/fmt/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/kineto/libkineto/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/kineto/libkineto/third_party/dynolog/dynolog/src/ipcfabric/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/third_party/mimalloc/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/torch/headeronly/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/c10/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/c10/test/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/c10/benchmark/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/c10/cuda/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/c10/cuda/test/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/THC/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/quantized/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/nnapi/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/sleef/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/sleef/src/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/sleef/src/libm/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/sleef/src/common/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/aten/src/ATen/test/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/core/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/serialize/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/utils/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/perfkernels/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/test_jit/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/test_nativert/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/test_inductor/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/test_api/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/test_lazy/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/torch/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/caffe2/torch/lib/libshm_windows/CTestTestfile.cmake E:/PyTorch_Build/pytorch/build/functorch/CTestTestfile.cmake E:\PyTorch_Build\pytorch\rtx5070_env\Lib\site-packages\cmake\data\bin\cmake.exe --regenerate-during-build -SE:\PyTorch_Build\pytorch -BE:\PyTorch_Build\pytorch\build CreateProcess failed: The system cannot find the file specified. ninja: error: rebuilding 'build.ninja': subcommand failed (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> # 安装Python包 (rtx5070_env) PS E:\PyTorch_Build\pytorch\build> cd .. (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\setup.py", line 288, in <module> import setuptools.command.bdist_wheel ModuleNotFoundError: No module named 'setuptools.command.bdist_wheel' (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证安装 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python -c "import torch; print(f'PyTorch {torch.__version__} built successfully! CUDA: {torch.cuda.is_available()}'); x = torch.rand(5).cuda(); print(f'GPU Tensor: {x}')" Traceback (most recent call last): File "<string>", line 1, in <module> File "E:\PyTorch_Build\pytorch\torch\__init__.py", line 415, in <module> from torch._C import * # noqa: F403 ImportError: DLL load failed while importing _C: 找不到指定的模块。 (rtx5070_env) PS E:\PyTorch_Build\pytorch>
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4. 在最后验证安装时，出现了DLL加载失败的错误，这通常是因为编译生成的动态链接库有问题，或者环境变量配置不正确。 解决方案： 1. 确保`libshm_windows.cpp`文件被正确创建在`torch/lib/libshm_windows/`目录下...
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第 12 步：打包调试和发布 注意：此示例对单配置生成器有效，不适用于多配置生成器（例如 Visual Studio）。 默认情况下，CMake 的模型是构建目录只包含一个配置，无论是 Debug、Release、MinSizeRel 还是 RelWithDebInfo。但是，可以将 CPack 设置为捆绑多个构建目录并构建一个包含同一项目的多个配置的包。 首先，我们要确保调试和发布版本对将要安装的可执行文件和库使用不同的名称。让我们使用d作为调试可执行文件和库的后缀。 CMAKE_DEBUG_PO
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feng__shuai的博客
06-19 410
在上面的demo中可以看到有个set(CMAKE_CXX_STANDARD 11)的变量设置，不用说也知道这个是要求C++使用-std=c++11。那么如果不设置的话，CMAKE_CXX_STANDARD 默认是多少？实际上CMAKE_CXX_STANDARD如果不设置的话, cmake是不会设定这个变量的，这个变量是cmake预先占用的变量名。只有两个方式分别是add_library和add_execute，生成库目标和可执行目标。项目的名字，同时会生成许多的变量名。生成目标，在cmake中生成。
CMake Day 2 —— 指定C/C++的标准
码上看世界
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我们可以在CMake代码中设置正确的标志，以启动对特定C/C++标准的支持。最简单的是使用`CMAKE_CXX_STANDARD`变量。
cmake 配置文件示例解释
AaronZZH 的博客
11-14 1279
cmake 配置文件 CMakeLists.txt 示例解释，包含可执行程序、链接库、测试及安装的主要功能。
CMake Tutorial 巡礼(10)_添加生成表达式
耳东小白的小笔记本儿
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CMake Tutorial 跟我一起学
在 CMake 中指定使用 C++11 标准进行编译
dengfuma的专栏
12-02 1641
通过警告可以发现，代码需要指定C++11 标准进行编译，在 CMake 中指定使用 C++11 标准进行编译是一个常见的需求。你可以通过修改文件来实现这一点。具体步骤如下：‌‌：使用set命令指定为11，这样 CMake 就会配置编译器使用 C++11 标准。‌‌：你可以要求 CMake 检查编译器是否支持指定的 C++ 标准。下面是一个简单的。
【学习笔记】Mastering CMake （十七）—— CMake 教程
cxsydzn的博客
10-30 936
CMake 教程提供了一个循序渐进的指南，涵盖了 CMake 帮助解决的常见构建系统问题。了解各种主题如何在示例项目中协同工作将非常有帮助。教程文档和示例源代码可以在 CMake 源代码树的 Help/guide/tutorial 目录中找到。每个步骤都有自己的子目录，其中包含可以用作起点的代码。本教程示例是渐进的，因此每一步都为前一步提供完整的解决方案。假设，出于本教程的目的，我们决定不使用平台的 log 和 exp 函数，而是希望生成一个预先计算值的表，以便在 mysqrt 函数中使用。
CMake Tutorial 巡礼(4)_安装与测试
耳东小白的小笔记本儿
09-10 333
CMake Tutorial 跟我一起学
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