A fatal error occurred. The required library hostfxr.dll could not be found.错误处理

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原创 最新推荐文章于 2024-04-17 09:55:52 发布 · 4.3k 阅读 · 2 ·
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#windows #microsoft

一个用.NET 6开发的控制台程序，发行版运行时出现找不到hostfxr.dll的错误。提示链接默认转到ASP.NET Core 6.0 Runtime下载页面，但程序是桌面程序，需安装.NET桌面运行时，下载安装后问题解决。

一个可控制台程序使用.NET 6开发，发行版运行出现如下错误：

A fatal error occurred. The required library hostfxr.dll could not be found.

If this is a self-contained application, that library should exist in [D:\xxxServer\].

If this is a framework-dependent application, install the runtime in the global location [C:\Program Files (x86)\dotnet] or use the DOTNET_ROOT environment variable to specify the runtime location or register the runtime location in [HKLM\SOFTWARE\dotnet\Setup\InstalledVersions\x86\InstallLocation].

The .NET runtime can be found at:

- https://aka.ms/dotnet-core-applaunch?missing_runtime=true&arch=x86&rid=win81-x86&apphost_version=6.0.5

根据提示提供的链接直接下载是不行的，因为这个链接默认会转到ASP.NET Core 6.0 Runtime下载页面，而我的程序是桌面程序，需要安装 .NET 桌面运行时：https://dotnet.microsoft.com/zh-cn/download/dotnet/6.0

下载安装后就不会有找不到hostfxr.dll的提示了。

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a fatal error occurred. The required library hostfxr.dll could not be found.
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The required library hostfxr.dll could not be found' 错误的方法”。用户提供了几个引用，我需要基于这些引用来回答。 关键错误是：“A fatal error occurred. The required library hostfxr.dll could not be ...
A fatal error occurred. The required library hostfxr.dll could not be found. If this is a self-contained application, that library should exist in [c:\Users\dyliwz\.vscode\extensions\cl.eide-3.23.14\res\tools\win32\unify_builder\]. If this is a framework-dependent application, install the runtime in the global location [C:\Program Files\dotnet] or use the DOTNET_ROOT environment variable to specify the runtime location or register the runtime location in [HKLM\SOFTWARE\dotnet\Setup\InstalledVersions\x64\InstallLocation]. The .NET runtime can be found at: - https://aka.ms/dotnet-core-applaunch?missing_runtime=true&arch=x64&rid=win10-x64&apphost_version=6.0.5
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我们正在解决在VSCode中配置Keil5环境时出现的.NET运行时错误，具体错误是“hostfxr.dll not found”。这个错误通常意味着系统缺少运行.NET应用程序所需的运行时环境。由于Keil Assistant扩展或其他相关工具可能依赖...
PS C:\Users\Administrator\Desktop> cd E:\PyTorch_Build\pytorch PS E:\PyTorch_Build\pytorch> python -m venv rtx5070_env No pyvenv.cfg file PS E:\PyTorch_Build\pytorch> .\rtx5070_env\Scripts\activate .\rtx5070_env\Scripts\activate: The term '.\rtx5070_env\Scripts\activate' is not recognized as a name of a cmdlet, function, script file, or executable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again. PS E:\PyTorch_Build\pytorch> # 修复 CMake CUDA 路径配置 PS E:\PyTorch_Build\pytorch> $cmakeCachePath = "E:\PyTorch_Build\pytorch\build\CMakeCache.txt" PS E:\PyTorch_Build\pytorch> $fixedCudaPath = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0" PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 使用正斜杠替换反斜杠避免转义问题 PS E:\PyTorch_Build\pytorch> (Get-Content $cmakeCachePath) -replace >> 'CUDA_TOOLKIT_ROOT_DIR:FILEPATH=C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v13\.0', >> "CUDA_TOOLKIT_ROOT_DIR:FILEPATH=$fixedCudaPath" | >> Set-Content $cmakeCachePath -Encoding UTF8 Get-Content: Cannot find path 'E:\PyTorch_Build\pytorch\build\CMakeCache.txt' because it does not exist. PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> Write-Host "✅ 已修复 CUDA 路径配置: $fixedCudaPath" ✅ 已修复 CUDA 路径配置: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 PS E:\PyTorch_Build\pytorch> # 创建虚拟环境激活脚本 PS E:\PyTorch_Build\pytorch> $activateScript = @" >> # E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\activate.ps1 >> param() >> >> # 设置环境变量 >> $env:VIRTUAL_ENV = "E:\PyTorch_Build\pytorch\rtx5070_env" >> $env:PATH = "E:\PyTorch_Build\pytorch\rtx5070_env\Scripts;" + $env:PATH >> >> # 移除旧的环境变量（如果存在） >> if ($env:_OLD_VIRTUAL_PATH) { >> $env:PATH = $env:_OLD_VIRTUAL_PATH >> } >> >> # 保存当前 PATH >> $env:_OLD_VIRTUAL_PATH = $env:PATH >> >> Write-Host "✅ 虚拟环境已激活: $env:VIRTUAL_ENV" -ForegroundColor Green >> "@ PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> $activateScript | Out-File "E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\activate.ps1" -Encoding UTF8 PS E:\PyTorch_Build\pytorch> # 手动配置 CMake 构建 PS E:\PyTorch_Build\pytorch> Set-Location "E:\PyTorch_Build\pytorch" PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 清理无效的构建缓存 PS E:\PyTorch_Build\pytorch> Remove-Item build -Recurse -Force -ErrorAction SilentlyContinue PS E:\PyTorch_Build\pytorch> New-Item -ItemType Directory -Path build | Out-Null PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 使用正确格式的路径变量 PS E:\PyTorch_Build\pytorch> $env:CUDA_PATH = "C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0" PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 配置 CMake PS E:\PyTorch_Build\pytorch> cmake -S . -B build ` >> -GNinja ` >> -DCMAKE_BUILD_TYPE=Release ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON ` >> -DCUDA_TOOLKIT_ROOT_DIR="$env:CUDA_PATH" ` >> -DCUDNN_ROOT="E:/Program Files/NVIDIA/CUDNN/v9.12" ` >> -DTORCH_CUDA_ARCH_LIST="8.6" ` >> -DBUILD_PYTHON=ON CMake Deprecation Warning at CMakeLists.txt:9 (cmake_policy): The OLD behavior for policy CMP0126 will be removed from a future version of CMake. The cmake-policies(7) manual explains that the OLD behaviors of all policies are deprecated and that a policy should be set to OLD only under specific short-term circumstances. Projects should be ported to the NEW behavior and not rely on setting a policy to OLD. -- The CXX compiler identification is GNU 13.2.0 -- The C compiler identification is GNU 13.2.0 -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: C:/ProgramData/mingw64/mingw64/bin/c++.exe - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: C:/ProgramData/mingw64/mingw64/bin/gcc.exe - skipped -- Detecting C compile features -- Detecting C compile features - done -- Not forcing any particular BLAS to be found CMake Warning at CMakeLists.txt:421 (message): TensorPipe cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:423 (message): KleidiAI cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:435 (message): Libuv is not installed in current conda env. Set USE_DISTRIBUTED to OFF. Please run command 'conda install -c conda-forge libuv=1.39' to install libuv. -- Performing Test C_HAS_AVX_1 -- Performing Test C_HAS_AVX_1 - Failed -- Performing Test C_HAS_AVX_2 -- Performing Test C_HAS_AVX_2 - Success -- Performing Test C_HAS_AVX2_1 -- Performing Test C_HAS_AVX2_1 - Failed -- Performing Test C_HAS_AVX2_2 -- Performing Test C_HAS_AVX2_2 - Success -- Performing Test C_HAS_AVX512_1 -- Performing Test C_HAS_AVX512_1 - Failed -- Performing Test C_HAS_AVX512_2 -- Performing Test C_HAS_AVX512_2 - Success -- Performing Test CXX_HAS_AVX_1 -- Performing Test CXX_HAS_AVX_1 - Failed -- Performing Test CXX_HAS_AVX_2 -- Performing Test CXX_HAS_AVX_2 - Success -- Performing Test CXX_HAS_AVX2_1 -- Performing Test CXX_HAS_AVX2_1 - Failed -- Performing Test CXX_HAS_AVX2_2 -- Performing Test CXX_HAS_AVX2_2 - Success -- Performing Test CXX_HAS_AVX512_1 -- Performing Test CXX_HAS_AVX512_1 - Failed -- Performing Test CXX_HAS_AVX512_2 -- Performing Test CXX_HAS_AVX512_2 - Success -- Current compiler supports avx2 extension. Will build perfkernels. -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY - Success -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY - Success -- Performing Test COMPILER_SUPPORTS_RDYNAMIC -- Performing Test COMPILER_SUPPORTS_RDYNAMIC - Failed -- Could not find hardware support for NEON on this machine. -- No OMAP3 processor on this machine. -- No OMAP4 processor on this machine. -- Compiler does not support SVE extension. Will not build perfkernels. CMake Warning at CMakeLists.txt:841 (message): x64 operating system is required for FBGEMM. Not compiling with FBGEMM. Turn this warning off by USE_FBGEMM=OFF. -- Could NOT find CUDA (missing: CUDA_INCLUDE_DIRS CUDA_CUDART_LIBRARY) (found version "13.0") CMake Warning at cmake/public/cuda.cmake:31 (message): PyTorch: CUDA cannot be found. Depending on whether you are building PyTorch or a PyTorch dependent library, the next warning / error will give you more info. Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:869 (include) CMake Warning at cmake/Dependencies.cmake:76 (message): Not compiling with CUDA. Suppress this warning with -DUSE_CUDA=OFF. Call Stack (most recent call first): CMakeLists.txt:869 (include) CMake Warning at cmake/Dependencies.cmake:95 (message): Not compiling with XPU. Could NOT find SYCL. Suppress this warning with -DUSE_XPU=OFF. Call Stack (most recent call first): CMakeLists.txt:869 (include) -- Building using own protobuf under third_party per request. -- Use custom protobuf build. CMake Warning at cmake/ProtoBuf.cmake:37 (message): Ancient protobuf forces CMake compatibility Call Stack (most recent call first): cmake/ProtoBuf.cmake:87 (custom_protobuf_find) cmake/Dependencies.cmake:107 (include) CMakeLists.txt:869 (include) CMake Deprecation Warning at third_party/protobuf/cmake/CMakeLists.txt:2 (cmake_minimum_required): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. -- -- 3.13.0.0 -- Performing Test CMAKE_HAVE_LIBC_PTHREAD -- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success -- Found Threads: TRUE -- Performing Test protobuf_HAVE_BUILTIN_ATOMICS -- Performing Test protobuf_HAVE_BUILTIN_ATOMICS - Success -- Caffe2 protobuf include directory: $<BUILD_INTERFACE:E:/PyTorch_Build/pytorch/third_party/protobuf/src>$<INSTALL_INTERFACE:include> -- Trying to find preferred BLAS backend of choice: MKL -- MKL_THREADING = OMP -- Looking for sys/types.h -- Looking for sys/types.h - found -- Looking for stdint.h -- Looking for stdint.h - found -- Looking for stddef.h -- Looking for stddef.h - found -- Check size of void* -- Check size of void* - done -- MKL_THREADING = OMP CMake Warning at cmake/Dependencies.cmake:213 (message): MKL could not be found. Defaulting to Eigen Call Stack (most recent call first): CMakeLists.txt:869 (include) CMake Warning at cmake/Dependencies.cmake:279 (message): Preferred BLAS (MKL) cannot be found, now searching for a general BLAS library Call Stack (most recent call first): CMakeLists.txt:869 (include) -- MKL_THREADING = OMP -- Checking for [mkl_intel_lp64 - mkl_intel_thread - mkl_core - libiomp5md] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_intel_thread - mkl_core - libiomp5md] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_intel_thread - mkl_core] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_intel_thread - mkl_core] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_sequential - mkl_core] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_sequential - mkl_core] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_core - libiomp5md - pthread] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_core - libiomp5md - pthread] -- Library mkl_intel: not found -- Checking for [mkl_intel_lp64 - mkl_core - pthread] -- Library mkl_intel_lp64: not found -- Checking for [mkl_intel - mkl_core - pthread] -- Library mkl_intel: not found -- Checking for [mkl - guide - pthread - m] -- Library mkl: not found -- MKL library not found -- Checking for [blis] -- Library blis: BLAS_blis_LIBRARY-NOTFOUND -- Checking for [Accelerate] -- Library Accelerate: BLAS_Accelerate_LIBRARY-NOTFOUND -- Checking for [vecLib] -- Library vecLib: BLAS_vecLib_LIBRARY-NOTFOUND -- Checking for [flexiblas] -- Library flexiblas: BLAS_flexiblas_LIBRARY-NOTFOUND -- Checking for [openblas] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [openblas - pthread - m] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [openblas - pthread - m - gomp] -- Library openblas: BLAS_openblas_LIBRARY-NOTFOUND -- Checking for [libopenblas] -- Library libopenblas: BLAS_libopenblas_LIBRARY-NOTFOUND -- Checking for [goto2 - gfortran] -- Library goto2: BLAS_goto2_LIBRARY-NOTFOUND -- Checking for [goto2 - gfortran - pthread] -- Library goto2: BLAS_goto2_LIBRARY-NOTFOUND -- Checking for [acml - gfortran] -- Library acml: BLAS_acml_LIBRARY-NOTFOUND -- Checking for [blis] -- Library blis: BLAS_blis_LIBRARY-NOTFOUND -- Could NOT find Atlas (missing: Atlas_CBLAS_INCLUDE_DIR Atlas_CLAPACK_INCLUDE_DIR Atlas_CBLAS_LIBRARY Atlas_BLAS_LIBRARY Atlas_LAPACK_LIBRARY) -- Checking for [ptf77blas - atlas - gfortran] -- Library ptf77blas: BLAS_ptf77blas_LIBRARY-NOTFOUND -- Checking for [] -- Looking for sgemm_ -- Looking for sgemm_ - not found -- Cannot find a library with BLAS API. Not using BLAS. -- Using pocketfft in directory: E:/PyTorch_Build/pytorch/third_party/pocketfft/ CMake Deprecation Warning at third_party/pthreadpool/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Deprecation Warning at third_party/FXdiv/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Deprecation Warning at third_party/cpuinfo/CMakeLists.txt:1 (CMAKE_MINIMUM_REQUIRED): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. CMake Deprecation Warning at aten/src/ATen/native/quantized/cpu/qnnpack/CMakeLists.txt:7 (cmake_minimum_required): Compatibility with CMake < 3.10 will be removed from a future version of CMake. Update the VERSION argument <min> value. Or, use the <min>...<max> syntax to tell CMake that the project requires at least <min> but has been updated to work with policies introduced by <max> or earlier. -- The ASM compiler identification is GNU -- Found assembler: C:/ProgramData/mingw64/mingw64/bin/gcc.exe CMake Error at aten/src/ATen/native/quantized/cpu/qnnpack/CMakeLists.txt:58 (message): Unrecognized CMAKE_SYSTEM_PROCESSOR = AMD64 -- Configuring incomplete, errors occurred! PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 开始构建 PS E:\PyTorch_Build\pytorch> cmake --build build --config Release --parallel 8 ninja: error: loading 'build.ninja': The system cannot find the file specified. PS E:\PyTorch_Build\pytorch> # 步骤1: 修复虚拟环境激活脚本 PS E:\PyTorch_Build\pytorch> .\create_activate_script.ps1 .\create_activate_script.ps1: The term '.\create_activate_script.ps1' is not recognized as a name of a cmdlet, function, script file, or executable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again. PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 步骤2: 激活虚拟环境 PS E:\PyTorch_Build\pytorch> & "E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\activate.ps1" ParserError: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\activate.ps1:9 Line | 9 | if () { | ~ | Missing condition in if statement after 'if ('. PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 步骤3: 修复 CMake 缓存 PS E:\PyTorch_Build\pytorch> .\fix_cmake_cache.ps1 .\fix_cmake_cache.ps1: The term '.\fix_cmake_cache.ps1' is not recognized as a name of a cmdlet, function, script file, or executable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again. PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 步骤4: 重建 CMake 配置 PS E:\PyTorch_Build\pytorch> Set-Location "E:\PyTorch_Build\pytorch" PS E:\PyTorch_Build\pytorch> .\reconfigure_cmake.ps1 .\reconfigure_cmake.ps1: The term '.\reconfigure_cmake.ps1' is not recognized as a name of a cmdlet, function, script file, or executable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again. PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 步骤5: 构建 PyTorch PS E:\PyTorch_Build\pytorch> Set-Location "E:\PyTorch_Build\pytorch\build" PS E:\PyTorch_Build\pytorch\build> ninja ninja: error: loading 'build.ninja': The system cannot find the file specified. PS E:\PyTorch_Build\pytorch\build> PS E:\PyTorch_Build\pytorch\build> # 步骤6: 安装 PyTorch PS E:\PyTorch_Build\pytorch\build> Set-Location "E:\PyTorch_Build\pytorch" PS E:\PyTorch_Build\pytorch> pip install -v --no-build-isolation . Using pip 25.2 from E:\Python310\lib\site-packages\pip (python 3.10) Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Processing e:\pytorch_build\pytorch Running command Preparing metadata (pyproject.toml) Building wheel torch-2.9.0a0+git2d31c3d E:\Python310\lib\site-packages\setuptools\config\_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated !! ******************************************************************************** Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0). By 2026-Feb-18, you need to update your project and remove deprecated calls or your builds will no longer be supported. See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! corresp(dist, value, root_dir) running dist_info creating C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info writing C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\PKG-INFO writing dependency_links to C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\dependency_links.txt writing entry points to C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\entry_points.txt writing requirements to C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\requires.txt writing top-level names to C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\top_level.txt writing manifest file 'C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\SOURCES.txt' reading manifest file 'C:\Users\Administrator\AppData\Local\Temp\pip-modern-metadata-f_2krmlk\torch.egg-info\SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no files found matching 'BUILD' warning: no files found matching '*.BUILD' warning: no files found matching 'BUCK' warning: no files found matching '[Mm]akefile.*' warning: no files found matching '*.[Dd]ockerfile' warning: no files found matching '[Dd]ockerfile.*' Preparing metadata (pyproject.toml) ... canceled ERROR: Operation cancelled by user PS E:\PyTorch_Build\pytorch>
09-05
message(FATAL_ERROR "Unrecognized CMAKE_SYSTEM_PROCESSOR = ${CMAKE_SYSTEM_PROCESSOR}") endif() ``` 我们可以修改为： ```cmake if(CMAKE_SYSTEM_PROCESSOR MATCHES "^(i[3-6]86|x86_64|amd64|AMD64)$") set...
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> # 创建终极修复脚本: build_absolute_fix.ps1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> @' >> # ------ 初始化 ------ >> $ErrorActionPreference = "Stop" >> Write-Host "=== PyTorch 终极解决方案 ===" -ForegroundColor Cyan >> Write-Host "开始时间: $(Get-Date -Format 'yyyy-MM-dd HH:mm:ss')" >> $logFile = "$PWD\build_log_$(Get-Date -Format 'yyyyMMdd_HHmmss').txt" >> Start-Transcript -Path $logFile -Append >> >> # ------ 强制设置开发环境 ------ >> $env:DeveloperMode = 1 >> $env:CMAKE_GENERATOR = "Ninja" >> >> # ------ 路径配置 ------ >> $pythonEnv = "E:\PyTorch_Build\pytorch\rtx5070_env" >> $cudaPath = "E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0" >> $cudnnBasePath = "E:\Program Files\NVIDIA\CUNND\v9.12" >> $cudaVersion = "13.0" >> $vsPath = "C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools" # 确保正确路径 >> >> # ------ 确保Visual Studio工具在PATH中 ------ >> $env:Path = ` >> "$vsPath\VC\Tools\MSVC\14.44.35207\bin\Hostx64\x64;" + ` >> "$vsPath\Common7\IDE;" + ` >> "$cudaPath\bin;" + ` >> $env:Path >> >> # ------ 修复cuDNN检测 ------ >> function Get-ProperCudnnPath { >> $headerPath = "E:\Program Files\NVIDIA\CUNND\v9.12\include\13.0" >> $libraryPath = "E:\Program Files\NVIDIA\CUNND\v9.12\lib\13.0\x64\cudnn64_9.lib" >> $dllPath = "E:\Program Files\NVIDIA\CUNND\v9.12\bin\13.0\cudnn64_9.dll" >> >> if (-not (Test-Path $headerPath)) { >> throw "cuDNN头文件路径不存在: $headerPath" >> } >> if (-not (Test-Path $libraryPath)) { >> throw "cuDNN库文件路径不存在: $libraryPath" >> } >> if (-not (Test-Path $dllPath)) { >> throw "cuDNN DLL文件路径不存在: $dllPath" >> } >> >> return @{ >> IncludeDir = $headerPath >> Library = $libraryPath >> BinDir = [System.IO.Path]::GetDirectoryName($dllPath) >> } >> } >> >> Write-Host "`n=== 硬编码cuDNN路径 ===" -ForegroundColor Yellow >> $cudnn = Get-ProperCudnnPath >> Write-Host "cuDNN头文件: $($cudnn.IncludeDir)" >> Write-Host "cuDNN库文件: $($cudnn.Library)" >> Write-Host "cuDNN DLL目录: $($cudnn.BinDir)" >> >> # ------ 环境配置 ------ >> Write-Host "`n=== 配置环境变量 ===" -ForegroundColor Green >> $env:CUDA_PATH = $cudaPath >> $env:Path = "$cudaPath\bin;$($cudnn.BinDir);$env:Path" >> $env:CUDNN_INCLUDE_DIR = $cudnn.IncludeDir >> $env:CUDNN_LIBRARY = $cudnn.Library >> $env:TORCH_CUDA_ARCH_LIST = "8.9" >> >> # 调试信息 >> Write-Host "环境变量检查:" >> Write-Host "CUDA_PATH: $env:CUDA_PATH" >> Write-Host "CUDNN_INCLUDE_DIR: $env:CUDNN_INCLUDE_DIR" >> Write-Host "CUDNN_LIBRARY: $env:CUDNN_LIBRARY" >> Write-Host "PATH: $($env:Path -split ';' | Select-Object -First 10)..." >> >> # ------ 激活Python环境 ------ >> Write-Host "`n=== 激活Python环境 ===" -ForegroundColor Magenta >> . "$pythonEnv\Scripts\Activate.ps1" >> Write-Host "✅ Python虚拟环境已激活" -ForegroundColor Green >> Write-Host "Python版本: $(python --version)" >> Write-Host "Pip版本: $(pip --version)" >> >> # ------ 强制清理 ------ >> Write-Host "`n=== 深度清理构建缓存 ===" -ForegroundColor Red >> python setup.py clean >> Remove-Item -Recurse -Force build, dist, torch\lib, cmake_build -ErrorAction SilentlyContinue >> Remove-Item -Force *.ncb, *.sdf, *.suo -ErrorAction SilentlyContinue >> >> # ------ 安装依赖 ------ >> Write-Host "`n=== 安装核心依赖 ===" -ForegroundColor Yellow >> pip install -U pip setuptools wheel ninja cmake==3.28.7 # 使用稳定版本 >> pip install -r requirements.txt >> >> # ------ 方法4: 直接CMake+Ninja构建 ------ >> Write-Host "`n=== 方法4: 纯CMake+Ninja构建 ===" -ForegroundColor Green >> $buildDir = "$PWD\cmake_release" >> New-Item -ItemType Directory -Path $buildDir -Force | Out-Null >> Set-Location $buildDir >> >> cmake .. -GNinja ` >> -DCMAKE_BUILD_TYPE=Release ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON ` >> -DCUDNN_INCLUDE_DIR="$($cudnn.IncludeDir)" ` >> -DCUDNN_LIBRARY="$($cudnn.Library)" ` >> -DPYTHON_EXECUTABLE="$pythonEnv\Scripts\python.exe" ` >> -DCMAKE_INSTALL_PREFIX="$PWD/install" ` >> -DTORCH_CUDA_ARCH_LIST="8.9" ` >> -DCMAKE_MSVC_RESPONSE_FILE=OFF # 解决Windows路径问题 >> >> if ($LASTEXITCODE -ne 0) { >> Write-Host "❌ CMake配置失败" -ForegroundColor Red >> exit 1 >> } >> >> ninja install >> $buildExitCode = $LASTEXITCODE >> Set-Location .. >> >> if ($buildExitCode -eq 0) { >> # ------ 修复运行时依赖 ------ >> $torchLibDir = "$PWD\torch\lib" >> New-Item -ItemType Directory -Path $torchLibDir -Force | Out-Null >> >> # 1. 复制所有CUDA DLL >> Get-ChildItem -Path "$cudaPath\bin\*.dll" | ForEach-Object { >> Copy-Item $_.FullName $torchLibDir -Force >> Write-Host "✅ 复制CUDA DLL: $($_.Name)" >> } >> >> # 2. 复制cuDNN DLL >> Copy-Item "$($cudnn.BinDir)\*.dll" $torchLibDir -Force >> >> # 3. 复制构建生成的DLL >> $buildDlls = Get-ChildItem -Path "$buildDir\lib", "$buildDir\bin" -Recurse -Include *.dll >> foreach ($dll in $buildDlls) { >> Copy-Item $dll.FullName $torchLibDir -Force >> Write-Host "✅ 复制构建DLL: $($dll.Name)" >> } >> >> # 4. 设置Python软链接 >> $installDir = "$buildDir\install" >> $env:PYTHONPATH = "$installDir;$env:PYTHONPATH" >> } >> >> # ------ 验证结果 ------ >> if ($buildExitCode -eq 0) { >> Write-Host "`n=== 验证构建结果 ===" -ForegroundColor Cyan >> $env:Path = "$torchLibDir;$env:Path" >> >> python -c @" >> import os, torch >> print(f'PyTorch版本: {torch.__version__}') >> print(f'CUDA可用: {torch.cuda.is_available()}') >> >> if torch.cuda.is_available(): >> print(f'CUDA版本: {torch.version.cuda}') >> print(f'cuDNN版本: {torch.backends.cudnn.version()}') >> print(f'检测到的GPU: {torch.cuda.get_device_name(0)}') >> >> # 测试基础计算 >> a = torch.randn(1000, 1000, device='cuda') >> b = torch.randn(1000, 1000, device='cuda') >> c = a @ b >> print(f'GPU计算验证: 矩阵乘法成功 (结果形状: {c.shape})') >> >> # 检查关键DLL >> from ctypes import WinDLL >> try: >> WinDLL(os.path.join(torch.__file__, 'lib', 'aoti_custom_ops.dll')) >> print('✅ aoti_custom_ops.dll 加载成功') >> except Exception as e: >> print(f'❌ aoti_custom_ops.dll 加载失败: {str(e)}') >> "@ >> $buildExitCode = $LASTEXITCODE >> } >> >> # ------ 完成报告 ------ >> Write-Host "`n=== 构建报告 ===" -ForegroundColor Cyan >> Write-Host "构建状态: $(if ($buildExitCode -eq 0) {'成功!'} else {'失败'})" -ForegroundColor $(if ($buildExitCode -eq 0) {'Green'} else {'Red'}) >> Write-Host "完成时间: $(Get-Date -Format 'yyyy-MM-dd HH:mm:ss')" >> >> Stop-Transcript >> exit $buildExitCode >> '@ | Set-Content -Path "build_absolute_fix.ps1" -Encoding UTF8 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 运行脚本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> Set-ExecutionPolicy Bypass -Scope Process -Force (rtx5070_env) PS E:\PyTorch_Build\pytorch> .\build_absolute_fix.ps1 === PyTorch 终极解决方案 === 开始时间: 2025-09-03 14:24:16 Transcript started, output file is E:\PyTorch_Build\pytorch\build_log_20250903_142416.txt === 硬编码cuDNN路径 === cuDNN头文件: E:\Program Files\NVIDIA\CUNND\v9.12\include\13.0 cuDNN库文件: E:\Program Files\NVIDIA\CUNND\v9.12\lib\13.0\x64\cudnn64_9.lib cuDNN DLL目录: E:\Program Files\NVIDIA\CUNND\v9.12\bin\13.0 === 配置环境变量 === 环境变量检查: CUDA_PATH: E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0 CUDNN_INCLUDE_DIR: E:\Program Files\NVIDIA\CUNND\v9.12\include\13.0 CUDNN_LIBRARY: E:\Program Files\NVIDIA\CUNND\v9.12\lib\13.0\x64\cudnn64_9.lib PATH: E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0\bin E:\Program Files\NVIDIA\CUNND\v9.12\bin\13.0 C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\VC\Tools\MSVC\14.44.35207\bin\Hostx64\x64 C:\Program Files (x86)\Microsoft Visual Studio\2022\BuildTools\Common7\IDE E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0\bin E:\PyTorch_Build\pytorch\rtx5070_env\Scripts C:\Program Files\PowerShell\7 C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\bin C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\libnvvp C:\Miniconda3\condabin... === 激活Python环境 === ✅ Python虚拟环境已激活 Python版本: Python 3.10.10 Pip版本: pip 25.2 from E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\pip (python 3.10) === 深度清理构建缓存 === Building wheel torch-2.9.0a0+git2d31c3d E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\setuptools\config\_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated !! ******************************************************************************** Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0). By 2026-Feb-18, you need to update your project and remove deprecated calls or your builds will no longer be supported. See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! corresp(dist, value, root_dir) running clean === 安装核心依赖 === Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (25.2) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (79.0.1) Collecting setuptools Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dc/17031897dae0efacfea57dfd3a82fdd2a2aeb58e0ff71b77b87e44edc772/setuptools-80.9.0-py3-none-any.whl (1.2 MB) Requirement already satisfied: wheel in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (0.45.1) Requirement already satisfied: ninja in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (1.13.0) ERROR: Ignored the following yanked versions: 3.27.4, 3.28.0, 3.29.0, 3.29.1, 3.31.0 ERROR: Could not find a version that satisfies the requirement cmake==3.28.7 (from versions: 0.1.0, 0.2.0, 0.4.0, 0.5.0, 0.6.0, 0.7.0, 0.7.1, 0.8.0, 0.9.0, 3.6.3, 3.6.3.post1, 3.7.2, 3.8.2, 3.9.6, 3.10.3, 3.11.0, 3.11.4, 3.11.4.post1, 3.12.0, 3.13.0, 3.13.1, 3.13.2, 3.13.2.post1, 3.14.3, 3.14.3.post1, 3.14.4, 3.14.4.post1, 3.15.3, 3.15.3.post1, 3.16.3, 3.16.3.post1, 3.16.5, 3.16.6, 3.16.7, 3.16.8, 3.17.0, 3.17.1, 3.17.2, 3.17.3, 3.18.0, 3.18.2, 3.18.2.post1, 3.18.4, 3.18.4.post1, 3.20.2, 3.20.3, 3.20.4, 3.20.5, 3.21.0, 3.21.1, 3.21.1.post1, 3.21.2, 3.21.3, 3.21.4, 3.22.0, 3.22.1, 3.22.2, 3.22.3, 3.22.4, 3.22.5, 3.22.6, 3.23.3, 3.24.0, 3.24.1, 3.24.1.1, 3.24.2, 3.24.3, 3.25.0, 3.25.2, 3.26.0, 3.26.1, 3.26.3, 3.26.4, 3.27.0, 3.27.1, 3.27.2, 3.27.4.1, 3.27.5, 3.27.6, 3.27.7, 3.27.9, 3.28.1, 3.28.3, 3.28.4, 3.29.0.1, 3.29.2, 3.29.3, 3.29.5, 3.29.5.1, 3.29.6, 3.30.0, 3.30.1, 3.30.2, 3.30.3, 3.30.4, 3.30.5, 3.30.9, 3.31.0.1, 3.31.1, 3.31.2, 3.31.4, 3.31.6, 4.0.0, 4.0.2, 4.0.3, 4.1.0) ERROR: No matching distribution found for cmake==3.28.7 Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: setuptools<80.0,>=70.1.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 2)) (79.0.1) Requirement already satisfied: cmake>=3.27 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 3)) (4.1.0) Requirement already satisfied: ninja in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 4)) (1.13.0) Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 5)) (2.2.6) Requirement already satisfied: packaging in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 6)) (25.0) Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 7)) (6.0.2) Requirement already satisfied: requests in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 8)) (2.32.5) Requirement already satisfied: six in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 9)) (1.17.0) Requirement already satisfied: typing-extensions>=4.10.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r E:\PyTorch_Build\pytorch\requirements-build.txt (line 10)) (4.15.0) Requirement already satisfied: expecttest>=0.3.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 8)) (0.3.0) Requirement already satisfied: filelock in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 9)) (3.19.1) Requirement already satisfied: fsspec>=0.8.5 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 10)) (2025.7.0) Requirement already satisfied: hypothesis in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 11)) (6.138.13) Requirement already satisfied: jinja2 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 12)) (3.1.6) Requirement already satisfied: lintrunner in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 13)) (0.12.7) Requirement already satisfied: networkx>=2.5.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 14)) (3.4.2) Requirement already satisfied: optree>=0.13.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 15)) (0.17.0) Requirement already satisfied: psutil in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 16)) (7.0.0) Requirement already satisfied: sympy>=1.13.3 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 17)) (1.14.0) Requirement already satisfied: wheel in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 19)) (0.45.1) Requirement already satisfied: build[uv] in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from -r requirements.txt (line 7)) (1.3.0) Requirement already satisfied: charset_normalizer<4,>=2 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from requests->-r E:\PyTorch_Build\pytorch\requirements-build.txt (line 8)) (3.4.3) Requirement already satisfied: idna<4,>=2.5 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from requests->-r E:\PyTorch_Build\pytorch\requirements-build.txt (line 8)) (3.10) Requirement already satisfied: urllib3<3,>=1.21.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from requests->-r E:\PyTorch_Build\pytorch\requirements-build.txt (line 8)) (2.5.0) Requirement already satisfied: certifi>=2017.4.17 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from requests->-r E:\PyTorch_Build\pytorch\requirements-build.txt (line 8)) (2025.8.3) Requirement already satisfied: pyproject_hooks in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from build[uv]->-r requirements.txt (line 7)) (1.2.0) Requirement already satisfied: colorama in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from build[uv]->-r requirements.txt (line 7)) (0.4.6) Requirement already satisfied: tomli>=1.1.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from build[uv]->-r requirements.txt (line 7)) (2.2.1) Requirement already satisfied: uv>=0.1.18 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from build[uv]->-r requirements.txt (line 7)) (0.8.14) Requirement already satisfied: attrs>=22.2.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from hypothesis->-r requirements.txt (line 11)) (25.3.0) Requirement already satisfied: exceptiongroup>=1.0.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from hypothesis->-r requirements.txt (line 11)) (1.3.0) Requirement already satisfied: sortedcontainers<3.0.0,>=2.1.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from hypothesis->-r requirements.txt (line 11)) (2.4.0) Requirement already satisfied: MarkupSafe>=2.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from jinja2->-r requirements.txt (line 12)) (3.0.2) Requirement already satisfied: mpmath<1.4,>=1.1.0 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from sympy>=1.13.3->-r requirements.txt (line 17)) (1.3.0) === 方法4: 纯CMake+Ninja构建 === CMake Deprecation Warning at CMakeLists.txt:9 (cmake_policy): The OLD behavior for policy CMP0126 will be removed from a future version of CMake. The cmake-policies(7) manual explains that the OLD behaviors of all policies are deprecated and that a policy should be set to OLD only under specific short-term circumstances. Projects should be ported to the NEW behavior and not rely on setting a policy to OLD. -- The CXX compiler identification is GNU 13.2.0 -- The C compiler identification is GNU 13.2.0 -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: C:/ProgramData/mingw64/mingw64/bin/c++.exe - skipped -- Detecting CXX compile features -- Detecting CXX compile features - done -- Detecting C compiler ABI info -- Detecting C compiler ABI info - done -- Check for working C compiler: C:/ProgramData/mingw64/mingw64/bin/gcc.exe - skipped -- Detecting C compile features -- Detecting C compile features - done -- Not forcing any particular BLAS to be found CMake Warning at CMakeLists.txt:421 (message): TensorPipe cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:423 (message): KleidiAI cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:435 (message): Libuv is not installed in current conda env. Set USE_DISTRIBUTED to OFF. Please run command 'conda install -c conda-forge libuv=1.39' to install libuv. -- Performing Test C_HAS_AVX_1 -- Performing Test C_HAS_AVX_1 - Failed -- Performing Test C_HAS_AVX_2 -- Performing Test C_HAS_AVX_2 - Success -- Performing Test C_HAS_AVX2_1 -- Performing Test C_HAS_AVX2_1 - Failed -- Performing Test C_HAS_AVX2_2 -- Performing Test C_HAS_AVX2_2 - Success -- Performing Test C_HAS_AVX512_1 -- Performing Test C_HAS_AVX512_1 - Failed -- Performing Test C_HAS_AVX512_2 -- Performing Test C_HAS_AVX512_2 - Success -- Performing Test CXX_HAS_AVX_1 -- Performing Test CXX_HAS_AVX_1 - Failed -- Performing Test CXX_HAS_AVX_2 -- Performing Test CXX_HAS_AVX_2 - Success -- Performing Test CXX_HAS_AVX2_1 -- Performing Test CXX_HAS_AVX2_1 - Failed -- Performing Test CXX_HAS_AVX2_2 -- Performing Test CXX_HAS_AVX2_2 - Success -- Performing Test CXX_HAS_AVX512_1 -- Performing Test CXX_HAS_AVX512_1 - Failed -- Performing Test CXX_HAS_AVX512_2 -- Performing Test CXX_HAS_AVX512_2 - Success -- Current compiler supports avx2 extension. Will build perfkernels. -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY - Success -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY - Success -- Performing Test COMPILER_SUPPORTS_RDYNAMIC -- Performing Test COMPILER_SUPPORTS_RDYNAMIC - Failed -- Could not find hardware support for NEON on this machine. -- No OMAP3 processor on this machine. -- No OMAP4 processor on this machine. -- Compiler does not support SVE extension. Will not build perfkernels. CMake Warning at CMakeLists.txt:841 (message): x64 operating system is required for FBGEMM. Not compiling with FBGEMM. Turn this warning off by USE_FBGEMM=OFF. -- Found CUDA: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 (found version "13.0") CMake Error at rtx5070_env/Lib/site-packages/cmake/data/share/cmake-4.1/Modules/CMakeDetermineCompilerId.cmake:928 (message): Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed. Compiler: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe Build flags: Id flags: --keep;--keep-dir;tmp -v The output was: 1 nvcc fatal : Cannot find compiler 'cl.exe' in PATH Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed. Compiler: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe Build flags: -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS;-Xfatbin;-compress-all Id flags: --keep;--keep-dir;tmp -v The output was: 1 nvcc fatal : Cannot find compiler 'cl.exe' in PATH Call Stack (most recent call first): rtx5070_env/Lib/site-packages/cmake/data/share/cmake-4.1/Modules/CMakeDetermineCompilerId.cmake:8 (CMAKE_DETERMINE_COMPILER_ID_BUILD) rtx5070_env/Lib/site-packages/cmake/data/share/cmake-4.1/Modules/CMakeDetermineCompilerId.cmake:53 (__determine_compiler_id_test) rtx5070_env/Lib/site-packages/cmake/data/share/cmake-4.1/Modules/CMakeDetermineCUDACompiler.cmake:162 (CMAKE_DETERMINE_COMPILER_ID) cmake/public/cuda.cmake:47 (enable_language) cmake/Dependencies.cmake:44 (include) CMakeLists.txt:869 (include) -- Configuring incomplete, errors occurred! ❌ CMake配置失败 为啥一直失败呢 我们现在缺的是什么 你能解释给我听吗
09-04
ERROR: No matching distribution found for cmake==3.28.7 ``` - PyTorch 需要特定 CMake 版本（3.18+），但脚本指定版本不可用 3. **环境变量污染**： - MinGW 编译器优先级高于 MSVC，导致 CUDA 工具链配置...
【虚幻引擎】UE5 C++编译和打包失败的原因
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虚幻引擎5安装遇到的错误
linux dotnet后台,linux netcore dotnet command
weixin_39959505的博客
05-15 431
执行dotnet aspnet-codegenerator controller -name TodoItemsController -async -api -m TodoItem -dc TodoContext -outDir Controllers报错：A fatal error occurred. The required library libhostfxr.so could not b...
net core 程序运行报错，需要kb2533623补丁
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.NET 6 运行在Win7 SP1上出错
08-05 7530
错误信息： Failed to load the dll from [C:\Program Files\dotnet\host\fxr\6.0.0-preview.6.21 352.12\hostfxr.dll], HRESULT: 0x80070057 The library hostfxr.dll was found, but loading it from C:\Program Files\dotnet\h ost\fxr\6.0.0-preview.6.21352.12\hostfxr.dll fa
.NET Core SDK在Windows系统安装后出现Failed to load the hostfxr.dll等问题的解决方法
weixin_38386235的博客
08-03 3468
这次无论如何也要记录下，原因是今天在一台Windows2008R2的电脑上安装.NET Core SDK后再命令行执行dotnet --info 居然爆出了“Failed to load the hostfxr.dll”的问题，之前也遇到过，但是解决了，却没有做记录，害的这里又google了一把！所以写篇文章记录下。额外说一句，部分500.25问题也是这个原因导致的！ 作者：依乐祝 原文地址：https://www.cnblogs.com/yilezhu/p/10057789.html 具体的错误信息如下：
PowerShell运行dotnet --info报错（Failed to load the dll from[...\hostfxr.dll],HRESULT:0x80070057)
weixin_43596442的博客
08-19 1770
故障描述：windows7系统运行在.NET5环境下制作的exe程序无反应。PowerShell查询dotnet信息报错。
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