Initializing a Build Environment

Initializing a Build Environment

This section describes how to set up your local work environment to buildthe Android source files. You will need to use Linux or Mac OS. Building underWindows is not currently supported.

For an overview of the entire code-review and code-update process, see Life of a Patch.

Choosing a Branch


Some of the requirements for your build environment are determined by whichversion of the source code you plan to compile. SeeBuild Numbers for a full listing of branches you maychoose from. You may also choose to download and build the latest source code(called "master"), in which case you will simply omit the branch specificationwhen you initialize the repository.

Once you have selected a branch, follow the appropriate instructions below toset up your build environment.

Setting up a Linux build environment


These instructions apply to all branches, including master.

The Android build is routinely tested in house on recent versions ofUbuntu LTS (12.04), but most distributions should have the requiredbuild tools available. Reports of successes or failures on otherdistributions are welcome.

For Gingerbread (2.3.x) and newer versions, including the masterbranch, a 64-bit environment is required. Older versions can becompiled on 32-bit systems.

Note: See the Downloading andBuilding page for the list of hardware and software requirements. Thenfollow the detailed instructions for Ubuntu and Mac OS below.

Installing the JDK

The master branch of Android in the Android Open Source Project (AOSP)requires Java 7. On Ubuntu, use OpenJDK.

Java 7: For the latest version of Android

$ sudo apt-get update
$ sudo apt-get install openjdk-7-jdk

Optionally, update the default Java version by running:

$ sudo update-alternatives --config java
$ sudo update-alternatives --config javac

If you encounter version errors for Java, set itspath as described in the WrongJava Version section.

To develop older versions of Android, download and install the corresponding version of the Java JDK:
Java 6: for Gingerbread through KitKat
Java 5: for Cupcake through Froyo

Note: The lunch command in the build step will ensure that the Sun JDK isused instead of any previously installed JDK.

Installing required packages (Ubuntu 12.04)

You will need a 64-bit version of Ubuntu. Ubuntu 12.04 is recommended.Building using an older version of Ubuntu is not supported on master or recent releases.

$ sudo apt-get install git gnupg flex bison gperf build-essential \
  zip curl libc6-dev libncurses5-dev:i386 x11proto-core-dev \
  libx11-dev:i386 libreadline6-dev:i386 libgl1-mesa-glx:i386 \
  libgl1-mesa-dev g++-multilib mingw32 tofrodos \
  python-markdown libxml2-utils xsltproc zlib1g-dev:i386
$ sudo ln -s /usr/lib/i386-linux-gnu/mesa/libGL.so.1 /usr/lib/i386-linux-gnu/libGL.so

Installing required packages (Ubuntu 14.04)

Building on Ubuntu 14.04 is experimental at the moment but will eventually become the recommendedenvironment.

$ sudo apt-get install bison g++-multilib git gperf libxml2-utils

Installing required packages (Ubuntu 10.04 -- 11.10)

Building on Ubuntu 10.04-11.10 is no longer supported, but may be useful for building olderreleases of AOSP.

$ sudo apt-get install git-core gnupg flex bison gperf build-essential \
  zip curl zlib1g-dev libc6-dev lib32ncurses5-dev ia32-libs \
  x11proto-core-dev libx11-dev lib32readline5-dev lib32z-dev \
  libgl1-mesa-dev g++-multilib mingw32 tofrodos python-markdown \
  libxml2-utils xsltproc

On Ubuntu 10.10:

$ sudo ln -s /usr/lib32/mesa/libGL.so.1 /usr/lib32/mesa/libGL.so

On Ubuntu 11.10:

$ sudo apt-get install libx11-dev:i386

Configuring USB Access

Under GNU/linux systems (and specifically under Ubuntu systems),regular users can't directly access USB devices by default. Thesystem needs to be configured to allow such access.

The recommended approach is to create a file/etc/udev/rules.d/51-android.rules (as the root user) and to copythe following lines in it. <username> must be replaced by theactual username of the user who is authorized to access the phonesover USB.

# adb protocol on passion (Nexus One)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4e12", MODE="0600", OWNER="<username>"
# fastboot protocol on passion (Nexus One)
SUBSYSTEM=="usb", ATTR{idVendor}=="0bb4", ATTR{idProduct}=="0fff", MODE="0600", OWNER="<username>"
# adb protocol on crespo/crespo4g (Nexus S)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4e22", MODE="0600", OWNER="<username>"
# fastboot protocol on crespo/crespo4g (Nexus S)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4e20", MODE="0600", OWNER="<username>"
# adb protocol on stingray/wingray (Xoom)
SUBSYSTEM=="usb", ATTR{idVendor}=="22b8", ATTR{idProduct}=="70a9", MODE="0600", OWNER="<username>"
# fastboot protocol on stingray/wingray (Xoom)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="708c", MODE="0600", OWNER="<username>"
# adb protocol on maguro/toro (Galaxy Nexus)
SUBSYSTEM=="usb", ATTR{idVendor}=="04e8", ATTR{idProduct}=="6860", MODE="0600", OWNER="<username>"
# fastboot protocol on maguro/toro (Galaxy Nexus)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4e30", MODE="0600", OWNER="<username>"
# adb protocol on panda (PandaBoard)
SUBSYSTEM=="usb", ATTR{idVendor}=="0451", ATTR{idProduct}=="d101", MODE="0600", OWNER="<username>"
# adb protocol on panda (PandaBoard ES)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="d002", MODE="0600", OWNER="<username>"
# fastboot protocol on panda (PandaBoard)
SUBSYSTEM=="usb", ATTR{idVendor}=="0451", ATTR{idProduct}=="d022", MODE="0600", OWNER="<username>"
# usbboot protocol on panda (PandaBoard)
SUBSYSTEM=="usb", ATTR{idVendor}=="0451", ATTR{idProduct}=="d00f", MODE="0600", OWNER="<username>"
# usbboot protocol on panda (PandaBoard ES)
SUBSYSTEM=="usb", ATTR{idVendor}=="0451", ATTR{idProduct}=="d010", MODE="0600", OWNER="<username>"
# adb protocol on grouper/tilapia (Nexus 7)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4e42", MODE="0600", OWNER="<username>"
# fastboot protocol on grouper/tilapia (Nexus 7)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4e40", MODE="0600", OWNER="<username>"
# adb protocol on manta (Nexus 10)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4ee2", MODE="0600", OWNER="<username>"
# fastboot protocol on manta (Nexus 10)
SUBSYSTEM=="usb", ATTR{idVendor}=="18d1", ATTR{idProduct}=="4ee0", MODE="0600", OWNER="<username>"

Those new rules take effect the next time a device is plugged in.It might therefore be necessary to unplug the device and plug itback into the computer.

This is known to work on both Ubuntu Hardy Heron (8.04.x LTS) andLucid Lynx (10.04.x LTS). Other versions of Ubuntu or othervariants of GNU/linux might require different configurations.

Setting up ccache

You can optionally tell the build to use the ccache compilation tool.Ccache acts as a compiler cache that can be used to speed-up rebuilds.This works very well if you do "make clean" often, or if you frequentlyswitch between different build products.

Put the following in your .bashrc or equivalent.

export USE_CCACHE=1

By default the cache will be stored in ~/.ccache.If your home directory is on NFS or some other non-local filesystem,you will want to specify the directory in your .bashrc as well.

export CCACHE_DIR=<path-to-your-cache-directory>

The suggested cache size is 50-100GB.You will need to run the following command once you have downloadedthe source code:

prebuilts/misc/linux-x86/ccache/ccache -M 50G

When building Ice Cream Sandwich (4.0.x) or older, ccache is ina different location:

prebuilt/linux-x86/ccache/ccache -M 50G

This setting is stored in the CCACHE_DIR and is persistent.

Using a separate output directory

By default, the output of each build is stored in the out/subdirectory of the matching source tree.

On some machines with multiple storage devices, builds arefaster when storing the source files and the output onseparate volumes. For additional performance, the outputcan be stored on a filesystem optimized for speed insteadof crash robustness, since all files can be re-generatedin case of filesystem corruption.

To set this up, export the OUT_DIR_COMMON_BASE variableto point to the location where your output directorieswill be stored.

export OUT_DIR_COMMON_BASE=<path-to-your-out-directory>

The output directory for each separate source tree will benamed after the directory holding the source tree.

For instance, if you have source trees as /source/master1and /source/master2 and OUT_DIR_COMMON_BASE is set to/output, the output directories will be /output/master1and /output/master2.

It's important in that case to not have multiple sourcetrees stored in directories that have the same name,as those would end up sharing an output directory, withunpredictable results.

This is only supported on Jelly Bean (4.1) and newer,including the master branch.

Setting up a Mac OS build environment


In a default installation, Mac OS runs on a case-preserving but case-insensitivefilesystem. This type of filesystem is not supported by git and will cause somegit commands (such as "git status") to behave abnormally. Because of this, werecommend that you always work with the AOSP source files on a case-sensitivefilesystem. This can be done fairly easily using a disk image, discussed below.

Once the proper filesystem is available, building the master branch in a modernMac OS environment is very straightforward. Earlier branches, including ICS,require some additional tools and SDKs.

Creating a case-sensitive disk image

You can create a case-sensitive filesystem within your existing Mac OS environmentusing a disk image. To create the image, launch DiskUtility and select "New Image". A size of 25GB is the minimum tocomplete the build, larger numbers are more future-proof. Using sparse imagessaves space while allowing to grow later as the need arises. Be sure to select"case sensitive, journaled" as the volume format.

You can also create it from a shell with the following command:

# hdiutil create -type SPARSE -fs 'Case-sensitive Journaled HFS+' -size 40g ~/android.dmg

This will create a .dmg (or possibly a .dmg.sparsefile) file which, once mounted, acts as a drive with the required formatting for Android development. For a disk image named "android.dmg" stored in your home directory, you can add the following to your ~/.bash_profile to mount the image when you execute "mountAndroid":

# mount the android file image
function mountAndroid { hdiutil attach ~/android.dmg -mountpoint /Volumes/android; }

Once mounted, you'll do all your work in the "android" volume. You can eject it (unmount it) just like you would with an external drive.

Installing the JDK

The master and 5.0.x branches of Android in the Android Open Source Project (AOSP)require Java 7. On Mac OS, use jdk-7u71-macosx-x64.dmg.

To develop for versions of Android Gingerbread through KitKat, download andinstall the Java 6 version of the Java JDK.

Master branch

To build the latest source in a Mac OS environment, you will need an Intel/x86machine running MacOS 10.8 (Mountain Lion) or later, along with Xcode4.5.2 or later including the Command Line Tools.

Branch 5.0.x and earlier branches

To build 5.0.x and earlier source in a Mac OS environment, you will need an Intel/x86machine running MacOS 10.8 (Mountain Lion), along with Xcode4.5.2 and Command Line Tools.

Branch 4.4.x and earlier branches

To build 4.2.x and earlier source in a Mac OS environment, you will need an Intel/x86machine running MacOS 10.6 (Snow Leopard) or MacOS 10.7 (Lion), along with Xcode4.2 (Apple's Developer Tools). Although Lion does not come with a JDK, it shouldinstall automatically when you attempt to build the source.

The remaining sections for Mac OS apply only to those who wish to buildearlier branches.

Branch 4.0.x and all earlier branches

To build android-4.0.x and earlier branches in a Mac OS environment, you need anIntel/x86 machine running MacOS 10.5 (Leopard) or MacOS 10.6 (Snow Leopard). Youwill need the MacOS 10.5 SDK.

Installing required packages
  • Install Xcode from the Apple developer site.We recommend version 3.1.4 or newer, i.e. gcc 4.2.Version 4.x could cause difficulties.If you are not already registered as an Apple developer, you will have tocreate an Apple ID in order to download.

  • Install MacPorts from macports.org.

    Note: Make sure that /opt/local/bin appears in your path BEFORE /usr/bin. If not, add

    export PATH=/opt/local/bin:$PATH
    

    to your ~/.bash_profile.

  • Get make, git, and GPG packages from MacPorts:

    $ POSIXLY_CORRECT=1 sudo port install gmake libsdl git-core gnupg
    

    If using Mac OS 10.4, also install bison:

    $ POSIXLY_CORRECT=1 sudo port install bison
    
Reverting from make 3.82

For versions of Android before ICS, there is a bug in gmake 3.82 that prevents android from building. You can install version 3.81 using MacPorts by taking the following steps:

  • Edit /opt/local/etc/macports/sources.conf and add a line that says

    file:///Users/Shared/dports
    

    above the rsync line. Then create this directory:

    $ mkdir /Users/Shared/dports
    
  • In the new dports directory, run

    $ svn co --revision 50980 http://svn.macports.org/repository/macports/trunk/dports/devel/gmake/ devel/gmake/
    
  • Create a port index for your new local repository:

    $ portindex /Users/Shared/dports
    
  • Finally, install the old version of gmake with

    $ sudo port install gmake @3.81
    
Setting a file descriptor limit

On MacOS the default limit on the number of simultaneous file descriptors open is too low and a highly parallel build process may exceed this limit.

To increase the cap, add the following lines to your ~/.bash_profile:

# set the number of open files to be 1024
ulimit -S -n 1024

Next: Download the source


Your build environment is good to go! Proceed to downloading the source.


PS C:\Users\Administrator\Desktop> cd E:\PyTorch_Build\pytorch PS E:\PyTorch_Build\pytorch> # 1. 激活虚拟环境 PS E:\PyTorch_Build\pytorch> .\pytorch_env\Scripts\activate (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 2. 修复conda路径(执行一次即可) (pytorch_env) PS E:\PyTorch_Build\pytorch> $condaPath = "${env:USERPROFILE}\miniconda3\Scripts" (pytorch_env) PS E:\PyTorch_Build\pytorch> $env:PATH += ";$condaPath" (pytorch_env) PS E:\PyTorch_Build\pytorch> [Environment]::SetEnvironmentVariable("PATH", $env:PATH, "Machine") (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 3. 验证修复 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda --version # 应显示conda版本 conda: The term 'conda' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> # 1. 安装正确版本的MKL (pytorch_env) PS E:\PyTorch_Build\pytorch> pip uninstall -y mkl-static mkl-include Found existing installation: mkl-static 2024.1.0 Uninstalling mkl-static-2024.1.0: Successfully uninstalled mkl-static-2024.1.0 Found existing installation: mkl-include 2024.1.0 Uninstalling mkl-include-2024.1.0: Successfully uninstalled mkl-include-2024.1.0 (pytorch_env) PS E:\PyTorch_Build\pytorch> pip install mkl-static==2024.1 mkl-include==2024.1 Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting mkl-static==2024.1 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/d8/f0/3b9976df82906d8f3244213b6d8beb67cda19ab5b0645eb199da3c826127/mkl_static-2024.1.0-py2.py3-none-win_amd64.whl (220.8 MB) Collecting mkl-include==2024.1 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/06/1b/f05201146f7f12bf871fa2c62096904317447846b5d23f3560a89b4bbaae/mkl_include-2024.1.0-py2.py3-none-win_amd64.whl (1.3 MB) Requirement already satisfied: intel-openmp==2024.* in e:\pytorch_build\pytorch\pytorch_env\lib\site-packages (from mkl-static==2024.1) (2024.2.1) Requirement already satisfied: tbb-devel==2021.* in e:\pytorch_build\pytorch\pytorch_env\lib\site-packages (from mkl-static==2024.1) (2021.13.1) Requirement already satisfied: intel-cmplr-lib-ur==2024.2.1 in e:\pytorch_build\pytorch\pytorch_env\lib\site-packages (from intel-openmp==2024.*->mkl-static==2024.1) (2024.2.1) Requirement already satisfied: tbb==2021.13.1 in e:\pytorch_build\pytorch\pytorch_env\lib\site-packages (from tbb-devel==2021.*->mkl-static==2024.1) (2021.13.1) Installing collected packages: mkl-include, mkl-static Successfully installed mkl-include-2024.1.0 mkl-static-2024.1.0 (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 2. 安装libuv (pytorch_env) PS E:\PyTorch_Build\pytorch> conda install -c conda-forge libuv=1.46 conda: The term 'conda' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 3. 安装OpenSSL (pytorch_env) PS E:\PyTorch_Build\pytorch> conda install -c conda-forge openssl=3.1 conda: The term 'conda' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 4. 验证安装 (pytorch_env) PS E:\PyTorch_Build\pytorch> python -c "import mkl; print('MKL版本:', mkl.__version__)" Traceback (most recent call last): File "<string>", line 1, in <module> ModuleNotFoundError: No module named 'mkl' (pytorch_env) PS E:\PyTorch_Build\pytorch> conda list | Select-String "libuv|openssl" conda: The term 'conda' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> # 验证所有关键组件 (pytorch_env) PS E:\PyTorch_Build\pytorch> python -c "import mkl; print('✓ MKL已安装')" Traceback (most recent call last): File "<string>", line 1, in <module> ModuleNotFoundError: No module named 'mkl' (pytorch_env) PS E:\PyTorch_Build\pytorch> conda list | Select-String "libuv|openssl" conda: The term 'conda' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> dir "E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0\bin\cudnn*" (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 验证环境变量 (pytorch_env) PS E:\PyTorch_Build\pytorch> python -c "import os; print('环境变量检查:'); >> print('CUDNN_PATH:', os.getenv('CUDA_PATH')); >> print('CONDA_PREFIX:', os.getenv('CONDA_PREFIX'))" 环境变量检查: CUDNN_PATH: E:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0 CONDA_PREFIX: None (pytorch_env) PS E:\PyTorch_Build\pytorch> # 清理并重建 (pytorch_env) PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force build (pytorch_env) PS E:\PyTorch_Build\pytorch> python setup.py install Building wheel torch-2.9.0a0+git2d31c3d -- Building version 2.9.0a0+git2d31c3d E:\PyTorch_Build\pytorch\pytorch_env\lib\site-packages\setuptools\_distutils\_msvccompiler.py:12: UserWarning: _get_vc_env is private; find an alternative (pypa/distutils#340) warnings.warn( -- Checkout nccl release tag: v2.27.5-1 cmake -GNinja -DBUILD_PYTHON=True -DBUILD_TEST=True -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=E:\PyTorch_Build\pytorch\torch -DCMAKE_PREFIX_PATH=E:\PyTorch_Build\pytorch\pytorch_env\Lib\site-packages -DPython_EXECUTABLE=E:\PyTorch_Build\pytorch\pytorch_env\Scripts\python.exe -DTORCH_BUILD_VERSION=2.9.0a0+git2d31c3d -DUSE_NUMPY=True E:\PyTorch_Build\pytorch CMake Deprecation Warning at CMakeLists.txt:18 (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 MSVC 19.44.35215.0 -- The C compiler identification is MSVC 19.44.35215.0 -- Detecting CXX compiler ABI info -- Detecting CXX compiler ABI info - done -- Check for working CXX compiler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.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:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe - skipped -- Detecting C compile features -- Detecting C compile features - done -- Not forcing any particular BLAS to be found CMake Warning at CMakeLists.txt:425 (message): TensorPipe cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:427 (message): KleidiAI cannot be used on Windows. Set it to OFF CMake Warning at CMakeLists.txt:439 (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 - Success -- Performing Test C_HAS_AVX2_1 -- Performing Test C_HAS_AVX2_1 - Success -- Performing Test C_HAS_AVX512_1 -- Performing Test C_HAS_AVX512_1 - Success -- Performing Test CXX_HAS_AVX_1 -- Performing Test CXX_HAS_AVX_1 - Success -- Performing Test CXX_HAS_AVX2_1 -- Performing Test CXX_HAS_AVX2_1 - Success -- Performing Test CXX_HAS_AVX512_1 -- Performing Test CXX_HAS_AVX512_1 - Success -- Current compiler supports avx2 extension. Will build perfkernels. -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_VISIBILITY - Failed -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY -- Performing Test COMPILER_SUPPORTS_HIDDEN_INLINE_VISIBILITY - 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:845 (message): x64 operating system is required for FBGEMM. Not compiling with FBGEMM. Turn this warning off by USE_FBGEMM=OFF. -- Performing Test HAS/UTF_8 -- Performing Test HAS/UTF_8 - Success -- Found CUDA: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 (found version "13.0") -- The CUDA compiler identification is NVIDIA 13.0.48 with host compiler MSVC 19.44.35215.0 -- Detecting CUDA compiler ABI info -- Detecting CUDA compiler ABI info - done -- Check for working CUDA compiler: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe - skipped -- Detecting CUDA compile features -- Detecting CUDA compile features - done -- Found CUDAToolkit: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/include (found version "13.0.48") -- PyTorch: CUDA detected: 13.0 -- PyTorch: CUDA nvcc is: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe -- PyTorch: CUDA toolkit directory: E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- PyTorch: Header version is: 13.0 -- Found Python: E:\PyTorch_Build\pytorch\pytorch_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter CMake Warning at cmake/public/cuda.cmake:140 (message): Failed to compute shorthash for libnvrtc.so Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Could NOT find CUDNN (missing: CUDNN_LIBRARY_PATH CUDNN_INCLUDE_PATH) CMake Warning at cmake/public/cuda.cmake:201 (message): Cannot find cuDNN library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Could NOT find CUSPARSELT (missing: CUSPARSELT_LIBRARY_PATH CUSPARSELT_INCLUDE_PATH) CMake Warning at cmake/public/cuda.cmake:226 (message): Cannot find cuSPARSELt library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Could NOT find CUDSS (missing: CUDSS_LIBRARY_PATH CUDSS_INCLUDE_PATH) CMake Warning at cmake/public/cuda.cmake:242 (message): Cannot find CUDSS library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- USE_CUFILE is set to 0. Compiling without cuFile support -- Autodetected CUDA architecture(s): 12.0 CMake Warning at cmake/public/cuda.cmake:317 (message): pytorch is not compatible with `CMAKE_CUDA_ARCHITECTURES` and will ignore its value. Please configure `TORCH_CUDA_ARCH_LIST` instead. Call Stack (most recent call first): cmake/Dependencies.cmake:44 (include) CMakeLists.txt:873 (include) -- Added CUDA NVCC flags for: -gencode;arch=compute_120,code=sm_120 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:873 (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:873 (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 - Failed -- Looking for pthread_create in pthreads -- Looking for pthread_create in pthreads - not found -- Looking for pthread_create in pthread -- Looking for pthread_create in pthread - not found -- Found Threads: TRUE -- 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:873 (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:873 (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. -- The ASM compiler identification is MSVC CMake Warning (dev) at pytorch_env/Lib/site-packages/cmake/data/share/cmake-4.1/Modules/CMakeDetermineASMCompiler.cmake:234 (message): Policy CMP194 is not set: MSVC is not an assembler for language ASM. Run "cmake --help-policy CMP194" for policy details. Use the cmake_policy command to set the policy and suppress this warning. Call Stack (most recent call first): third_party/XNNPACK/CMakeLists.txt:18 (PROJECT) This warning is for project developers. Use -Wno-dev to suppress it. -- Found assembler: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- Building for XNNPACK_TARGET_PROCESSOR: x86_64 -- Generating microkernels.cmake Duplicate microkernel definition: src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-avx256vnni.c and src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-avxvnni.c (1th function) Duplicate microkernel definition: src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-avxvnni.c and src\qs8-qc4w-packw\gen\qs8-qc4w-packw-x8c8-gemm-goi-scalar.c No microkernel found in src\reference\binary-elementwise.cc No microkernel found in src\reference\packing.cc No microkernel found in src\reference\unary-elementwise.cc -- Found Git: E:/Program Files/Git/cmd/git.exe (found version "2.51.0.windows.1") -- Google Benchmark version: v1.9.3, normalized to 1.9.3 -- Looking for shm_open in rt -- Looking for shm_open in rt - not found -- Performing Test HAVE_CXX_FLAG_WX -- Performing Test HAVE_CXX_FLAG_WX - Success -- Compiling and running to test HAVE_STD_REGEX -- Performing Test HAVE_STD_REGEX -- success -- Compiling and running to test HAVE_GNU_POSIX_REGEX -- Performing Test HAVE_GNU_POSIX_REGEX -- failed to compile -- Compiling and running to test HAVE_POSIX_REGEX -- Performing Test HAVE_POSIX_REGEX -- failed to compile -- Compiling and running to test HAVE_STEADY_CLOCK -- Performing Test HAVE_STEADY_CLOCK -- success -- Compiling and running to test HAVE_PTHREAD_AFFINITY -- Performing Test HAVE_PTHREAD_AFFINITY -- failed to compile CMake Deprecation Warning at third_party/ittapi/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. CMake Warning at cmake/Dependencies.cmake:749 (message): FP16 is only cmake-2.8 compatible Call Stack (most recent call first): CMakeLists.txt:873 (include) CMake Deprecation Warning at third_party/FP16/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/psimd/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. -- Using third party subdirectory Eigen. -- Found Python: E:\PyTorch_Build\pytorch\pytorch_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter Development.Module missing components: NumPy CMake Warning at cmake/Dependencies.cmake:826 (message): NumPy could not be found. Not building with NumPy. Suppress this warning with -DUSE_NUMPY=OFF Call Stack (most recent call first): CMakeLists.txt:873 (include) -- Using third_party/pybind11. -- pybind11 include dirs: E:/PyTorch_Build/pytorch/cmake/../third_party/pybind11/include -- Could NOT find OpenTelemetryApi (missing: OpenTelemetryApi_INCLUDE_DIRS) -- Using third_party/opentelemetry-cpp. -- opentelemetry api include dirs: E:/PyTorch_Build/pytorch/cmake/../third_party/opentelemetry-cpp/api/include -- Could NOT find MPI_C (missing: MPI_C_LIB_NAMES MPI_C_HEADER_DIR MPI_C_WORKS) -- Could NOT find MPI_CXX (missing: MPI_CXX_LIB_NAMES MPI_CXX_HEADER_DIR MPI_CXX_WORKS) -- Could NOT find MPI (missing: MPI_C_FOUND MPI_CXX_FOUND) CMake Warning at cmake/Dependencies.cmake:894 (message): Not compiling with MPI. Suppress this warning with -DUSE_MPI=OFF Call Stack (most recent call first): CMakeLists.txt:873 (include) -- MKL_THREADING = OMP -- Check OMP with lib C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/lib/x64/libomp.lib and flags -openmp:experimental -- MKL_THREADING = OMP -- Check OMP with lib C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/lib/x64/libomp.lib and flags -openmp:experimental -- Found OpenMP_C: -openmp:experimental -- Found OpenMP_CXX: -openmp:experimental -- Found OpenMP: TRUE -- Adding OpenMP CXX_FLAGS: -openmp:experimental -- Will link against OpenMP libraries: C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/lib/x64/libomp.lib -- Found nvtx3: E:/PyTorch_Build/pytorch/third_party/NVTX/c/include -- ROCM_PATH environment variable is not set and C:/opt/rocm does not exist. Building without ROCm support. -- Found Python3: E:\PyTorch_Build\pytorch\pytorch_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter -- ONNX_PROTOC_EXECUTABLE: $<TARGET_FILE:protobuf::protoc> -- Protobuf_VERSION: Protobuf_VERSION_NOTFOUND Generated: E:/PyTorch_Build/pytorch/build/third_party/onnx/onnx/onnx_onnx_torch-ml.proto Generated: E:/PyTorch_Build/pytorch/build/third_party/onnx/onnx/onnx-operators_onnx_torch-ml.proto Generated: E:/PyTorch_Build/pytorch/build/third_party/onnx/onnx/onnx-data_onnx_torch.proto -- -- ******** Summary ******** -- CMake version : 4.1.0 -- CMake command : E:/PyTorch_Build/pytorch/pytorch_env/Lib/site-packages/cmake/data/bin/cmake.exe -- System : Windows -- C++ compiler : C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- C++ compiler version : 19.44.35215.0 -- CXX flags : /DWIN32 /D_WINDOWS /EHsc /Zc:__cplusplus /bigobj /FS /utf-8 -DUSE_PTHREADPOOL /EHsc /wd26812 -- Build type : Release -- Compile definitions : ONNX_ML=1;ONNXIFI_ENABLE_EXT=1 -- CMAKE_PREFIX_PATH : E:\PyTorch_Build\pytorch\pytorch_env\Lib\site-packages;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CMAKE_INSTALL_PREFIX : E:/PyTorch_Build/pytorch/torch -- CMAKE_MODULE_PATH : E:/PyTorch_Build/pytorch/cmake/Modules;E:/PyTorch_Build/pytorch/cmake/public/../Modules_CUDA_fix -- -- ONNX version : 1.18.0 -- ONNX NAMESPACE : onnx_torch -- ONNX_USE_LITE_PROTO : OFF -- USE_PROTOBUF_SHARED_LIBS : OFF -- ONNX_DISABLE_EXCEPTIONS : OFF -- ONNX_DISABLE_STATIC_REGISTRATION : OFF -- ONNX_WERROR : OFF -- ONNX_BUILD_TESTS : OFF -- BUILD_SHARED_LIBS : OFF -- -- Protobuf compiler : $<TARGET_FILE:protobuf::protoc> -- Protobuf includes : -- Protobuf libraries : -- ONNX_BUILD_PYTHON : OFF -- Found CUDA with FP16 support, compiling with torch.cuda.HalfTensor -- Adding -DNDEBUG to compile flags -- Checking prototype magma_get_sgeqrf_nb for MAGMA_V2 -- Checking prototype magma_get_sgeqrf_nb for MAGMA_V2 - False -- MAGMA not found. Compiling without MAGMA support -- Could not find hardware support for NEON on this machine. -- No OMAP3 processor on this machine. -- No OMAP4 processor on this machine. -- 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 [] -- Cannot find a library with BLAS API. Not using BLAS. -- LAPACK requires BLAS -- Cannot find a library with LAPACK API. Not using LAPACK. disabling ROCM because NOT USE_ROCM is set -- MIOpen not found. Compiling without MIOpen support disabling MKLDNN because USE_MKLDNN is not set -- {fmt} version: 11.2.0 -- Build type: Release -- Using Kineto with CUPTI support -- Configuring Kineto dependency: -- KINETO_SOURCE_DIR = E:/PyTorch_Build/pytorch/third_party/kineto/libkineto -- KINETO_BUILD_TESTS = OFF -- KINETO_LIBRARY_TYPE = static -- CUDA_SOURCE_DIR = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CUDA_INCLUDE_DIRS = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/include -- CUPTI_INCLUDE_DIR = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/extras/CUPTI/include -- CUDA_cupti_LIBRARY = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/extras/CUPTI/lib64/cupti.lib -- Found CUPTI CMake Deprecation Warning at third_party/kineto/libkineto/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. CMake Warning (dev) at third_party/kineto/libkineto/CMakeLists.txt:15 (find_package): Policy CMP0148 is not set: The FindPythonInterp and FindPythonLibs modules are removed. Run "cmake --help-policy CMP0148" for policy details. Use the cmake_policy command to set the policy and suppress this warning. This warning is for project developers. Use -Wno-dev to suppress it. -- Found PythonInterp: E:/PyTorch_Build/pytorch/pytorch_env/Scripts/python.exe (found version "3.10.10") -- ROCM_SOURCE_DIR = -- Kineto: FMT_SOURCE_DIR = E:/PyTorch_Build/pytorch/third_party/fmt -- Kineto: FMT_INCLUDE_DIR = E:/PyTorch_Build/pytorch/third_party/fmt/include -- CUPTI_INCLUDE_DIR = E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/extras/CUPTI/include -- ROCTRACER_INCLUDE_DIR = /include/roctracer -- DYNOLOG_INCLUDE_DIR = E:/PyTorch_Build/pytorch/third_party/kineto/libkineto/third_party/dynolog/ -- IPCFABRIC_INCLUDE_DIR = E:/PyTorch_Build/pytorch/third_party/kineto/libkineto/third_party/dynolog//dynolog/src/ipcfabric/ -- Configured Kineto -- Performing Test HAS/WD4624 -- Performing Test HAS/WD4624 - Success -- Performing Test HAS/WD4068 -- Performing Test HAS/WD4068 - Success -- Performing Test HAS/WD4067 -- Performing Test HAS/WD4067 - Success -- Performing Test HAS/WD4267 -- Performing Test HAS/WD4267 - Success -- Performing Test HAS/WD4661 -- Performing Test HAS/WD4661 - Success -- Performing Test HAS/WD4717 -- Performing Test HAS/WD4717 - Success -- Performing Test HAS/WD4244 -- Performing Test HAS/WD4244 - Success -- Performing Test HAS/WD4804 -- Performing Test HAS/WD4804 - Success -- Performing Test HAS/WD4273 -- Performing Test HAS/WD4273 - Success -- Performing Test HAS_WNO_STRINGOP_OVERFLOW -- Performing Test HAS_WNO_STRINGOP_OVERFLOW - Failed -- -- Architecture: x64 -- Use the C++ compiler to compile (MI_USE_CXX=ON) -- -- Library name : mimalloc -- Version : 2.2.4 -- Build type : release -- C++ Compiler : C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- Compiler flags : /Zc:__cplusplus -- Compiler defines : MI_CMAKE_BUILD_TYPE=release;MI_BUILD_RELEASE -- Link libraries : psapi;shell32;user32;advapi32;bcrypt -- Build targets : static -- CMake Error at CMakeLists.txt:1264 (add_subdirectory): The source directory E:/PyTorch_Build/pytorch/torch/headeronly does not contain a CMakeLists.txt file. -- don't use NUMA -- Looking for backtrace -- Looking for backtrace - not found -- Could NOT find Backtrace (missing: Backtrace_LIBRARY Backtrace_INCLUDE_DIR) -- Autodetected CUDA architecture(s): 12.0 -- Autodetected CUDA architecture(s): 12.0 -- Autodetected CUDA architecture(s): 12.0 -- headers outputs: torch\csrc\inductor\aoti_torch\generated\c_shim_cpu.h not found torch\csrc\inductor\aoti_torch\generated\c_shim_aten.h not found torch\csrc\inductor\aoti_torch\generated\c_shim_cuda.h not found -- sources outputs: -- declarations_yaml outputs: -- Performing Test COMPILER_SUPPORTS_NO_AVX256_SPLIT -- Performing Test COMPILER_SUPPORTS_NO_AVX256_SPLIT - Failed -- Using ATen parallel backend: OMP -- Could NOT find OpenSSL, try to set the path to OpenSSL root folder in the system variable OPENSSL_ROOT_DIR (missing: OPENSSL_CRYPTO_LIBRARY OPENSSL_INCLUDE_DIR) -- Check size of long double -- Check size of long double - done -- Performing Test COMPILER_SUPPORTS_FLOAT128 -- Performing Test COMPILER_SUPPORTS_FLOAT128 - Failed -- Performing Test COMPILER_SUPPORTS_SSE2 -- Performing Test COMPILER_SUPPORTS_SSE2 - Success -- Performing Test COMPILER_SUPPORTS_SSE4 -- Performing Test COMPILER_SUPPORTS_SSE4 - Success -- Performing Test COMPILER_SUPPORTS_AVX -- Performing Test COMPILER_SUPPORTS_AVX - Success -- Performing Test COMPILER_SUPPORTS_FMA4 -- Performing Test COMPILER_SUPPORTS_FMA4 - Success -- Performing Test COMPILER_SUPPORTS_AVX2 -- Performing Test COMPILER_SUPPORTS_AVX2 - Success -- Performing Test COMPILER_SUPPORTS_AVX512F -- Performing Test COMPILER_SUPPORTS_AVX512F - Success -- Found OpenMP_C: -openmp:experimental (found version "2.0") -- Found OpenMP_CXX: -openmp:experimental (found version "2.0") -- Found OpenMP_CUDA: -openmp (found version "2.0") -- Found OpenMP: TRUE (found version "2.0") -- Performing Test COMPILER_SUPPORTS_OPENMP -- Performing Test COMPILER_SUPPORTS_OPENMP - Success -- Performing Test COMPILER_SUPPORTS_OMP_SIMD -- Performing Test COMPILER_SUPPORTS_OMP_SIMD - Failed -- Performing Test COMPILER_SUPPORTS_WEAK_ALIASES -- Performing Test COMPILER_SUPPORTS_WEAK_ALIASES - Failed -- Performing Test COMPILER_SUPPORTS_BUILTIN_MATH -- Performing Test COMPILER_SUPPORTS_BUILTIN_MATH - Failed -- Performing Test COMPILER_SUPPORTS_SYS_GETRANDOM -- Performing Test COMPILER_SUPPORTS_SYS_GETRANDOM - Failed -- Configuring build for SLEEF-v3.8.0 Target system: Windows-10.0.26100 Target processor: AMD64 Host system: Windows-10.0.26100 Host processor: AMD64 Detected C compiler: MSVC @ C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe CMake: 4.1.0 Make program: E:/PyTorch_Build/pytorch/pytorch_env/Scripts/ninja.exe -- Using option `/D_CRT_SECURE_NO_WARNINGS /D_CRT_NONSTDC_NO_DEPRECATE ` to compile libsleef -- Building shared libs : OFF -- Building static test bins: OFF -- MPFR : LIB_MPFR-NOTFOUND -- GMP : LIBGMP-NOTFOUND -- RT : -- FFTW3 : LIBFFTW3-NOTFOUND -- OPENSSL : -- SDE : SDE_COMMAND-NOTFOUND -- COMPILER_SUPPORTS_OPENMP : FALSE AT_INSTALL_INCLUDE_DIR include/ATen/core core header install: E:/PyTorch_Build/pytorch/build/aten/src/ATen/core/aten_interned_strings.h core header install: E:/PyTorch_Build/pytorch/build/aten/src/ATen/core/enum_tag.h core header install: E:/PyTorch_Build/pytorch/build/aten/src/ATen/core/TensorBody.h CMake Error: File E:/PyTorch_Build/pytorch/torch/_utils_internal.py does not exist. CMake Error at caffe2/CMakeLists.txt:241 (configure_file): configure_file Problem configuring file CMake Error: File E:/PyTorch_Build/pytorch/torch/csrc/api/include/torch/version.h.in does not exist. CMake Error at caffe2/CMakeLists.txt:246 (configure_file): configure_file Problem configuring file -- NVSHMEM not found, not building with NVSHMEM support. CMake Error at caffe2/CMakeLists.txt:1398 (add_subdirectory): The source directory E:/PyTorch_Build/pytorch/torch does not contain a CMakeLists.txt file. CMake Warning at CMakeLists.txt:1285 (message): Generated cmake files are only fully tested if one builds with system glog, gflags, and protobuf. Other settings may generate files that are not well tested. -- -- ******** Summary ******** -- General: -- CMake version : 4.1.0 -- CMake command : E:/PyTorch_Build/pytorch/pytorch_env/Lib/site-packages/cmake/data/bin/cmake.exe -- System : Windows -- C++ compiler : C:/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/VC/Tools/MSVC/14.44.35207/bin/Hostx64/x64/cl.exe -- C++ compiler id : MSVC -- C++ compiler version : 19.44.35215.0 -- Using ccache if found : OFF -- CXX flags : /DWIN32 /D_WINDOWS /EHsc /Zc:__cplusplus /bigobj /FS /utf-8 -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE /wd4624 /wd4068 /wd4067 /wd4267 /wd4661 /wd4717 /wd4244 /wd4804 /wd4273 -- Shared LD flags : /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 -- Static LD flags : /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 -- Module LD flags : /machine:x64 /ignore:4049 /ignore:4217 /ignore:4099 -- Build type : Release -- Compile definitions : ONNX_ML=1;ONNXIFI_ENABLE_EXT=1;ONNX_NAMESPACE=onnx_torch;_CRT_SECURE_NO_DEPRECATE=1;USE_EXTERNAL_MZCRC;MINIZ_DISABLE_ZIP_READER_CRC32_CHECKS;EXPORT_AOTI_FUNCTIONS;WIN32_LEAN_AND_MEAN;_UCRT_LEGACY_INFINITY;NOMINMAX;USE_MIMALLOC -- CMAKE_PREFIX_PATH : E:\PyTorch_Build\pytorch\pytorch_env\Lib\site-packages;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CMAKE_INSTALL_PREFIX : E:/PyTorch_Build/pytorch/torch -- USE_GOLD_LINKER : OFF -- -- TORCH_VERSION : 2.9.0 -- BUILD_STATIC_RUNTIME_BENCHMARK: OFF -- BUILD_BINARY : OFF -- BUILD_CUSTOM_PROTOBUF : ON -- Link local protobuf : ON -- BUILD_PYTHON : True -- Python version : 3.10.10 -- Python executable : E:\PyTorch_Build\pytorch\pytorch_env\Scripts\python.exe -- Python library : E:/Python310/libs/python310.lib -- Python includes : E:/Python310/Include -- Python site-package : E:\PyTorch_Build\pytorch\pytorch_env\Lib\site-packages -- BUILD_SHARED_LIBS : ON -- CAFFE2_USE_MSVC_STATIC_RUNTIME : OFF -- BUILD_TEST : True -- BUILD_JNI : OFF -- BUILD_MOBILE_AUTOGRAD : OFF -- BUILD_LITE_INTERPRETER: OFF -- INTERN_BUILD_MOBILE : -- TRACING_BASED : OFF -- USE_BLAS : 0 -- USE_LAPACK : 0 -- USE_ASAN : OFF -- USE_TSAN : OFF -- USE_CPP_CODE_COVERAGE : OFF -- USE_CUDA : ON -- CUDA static link : OFF -- USE_CUDNN : OFF -- USE_CUSPARSELT : OFF -- USE_CUDSS : OFF -- USE_CUFILE : OFF -- CUDA version : 13.0 -- USE_FLASH_ATTENTION : OFF -- USE_MEM_EFF_ATTENTION : ON -- CUDA root directory : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0 -- CUDA library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cuda.lib -- cudart library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cudart.lib -- cublas library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cublas.lib -- cufft library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cufft.lib -- curand library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/curand.lib -- cusparse library : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cusparse.lib -- nvrtc : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/nvrtc.lib -- CUDA include path : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/include -- NVCC executable : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe -- CUDA compiler : E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/bin/nvcc.exe -- CUDA flags : -DLIBCUDACXX_ENABLE_SIMPLIFIED_COMPLEX_OPERATIONS -Xcompiler /Zc:__cplusplus -Xcompiler /w -w -Xcompiler /FS -Xfatbin -compress-all -DONNX_NAMESPACE=onnx_torch --use-local-env -gencode arch=compute_120,code=sm_120 -Xcudafe --diag_suppress=cc_clobber_ignored,--diag_suppress=field_without_dll_interface,--diag_suppress=base_class_has_different_dll_interface,--diag_suppress=dll_interface_conflict_none_assumed,--diag_suppress=dll_interface_conflict_dllexport_assumed,--diag_suppress=bad_friend_decl --Werror cross-execution-space-call --no-host-device-move-forward --expt-relaxed-constexpr --expt-extended-lambda -Xcompiler=/wd4819,/wd4503,/wd4190,/wd4244,/wd4251,/wd4275,/wd4522 -Wno-deprecated-gpu-targets --expt-extended-lambda -DCUB_WRAPPED_NAMESPACE=at_cuda_detail -DCUDA_HAS_FP16=1 -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -- CUDA host compiler : -- CUDA --device-c : OFF -- USE_TENSORRT : -- USE_XPU : OFF -- USE_ROCM : OFF -- BUILD_NVFUSER : -- USE_EIGEN_FOR_BLAS : ON -- USE_EIGEN_FOR_SPARSE : OFF -- USE_FBGEMM : OFF -- USE_KINETO : ON -- USE_GFLAGS : OFF -- USE_GLOG : OFF -- USE_LITE_PROTO : OFF -- USE_PYTORCH_METAL : OFF -- USE_PYTORCH_METAL_EXPORT : OFF -- USE_MPS : OFF -- CAN_COMPILE_METAL : -- USE_MKL : OFF -- USE_MKLDNN : OFF -- USE_UCC : OFF -- USE_ITT : ON -- USE_XCCL : OFF -- USE_NCCL : OFF -- Found NVSHMEM : -- USE_NNPACK : OFF -- USE_NUMPY : OFF -- USE_OBSERVERS : ON -- USE_OPENCL : OFF -- USE_OPENMP : ON -- USE_MIMALLOC : ON -- USE_MIMALLOC_ON_MKL : OFF -- USE_VULKAN : OFF -- USE_PROF : OFF -- USE_PYTORCH_QNNPACK : OFF -- USE_XNNPACK : ON -- USE_DISTRIBUTED : OFF -- Public Dependencies : -- Private Dependencies : Threads::Threads;pthreadpool;cpuinfo;XNNPACK;microkernels-prod;ittnotify;fp16;caffe2::openmp;fmt::fmt-header-only;kineto -- Public CUDA Deps. : -- Private CUDA Deps. : caffe2::curand;caffe2::cufft;caffe2::cublas;fmt::fmt-header-only;E:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v13.0/lib/x64/cudart_static.lib;CUDA::cusparse;CUDA::cufft;CUDA::cusolver;ATEN_CUDA_FILES_GEN_LIB -- USE_COREML_DELEGATE : OFF -- BUILD_LAZY_TS_BACKEND : ON -- USE_ROCM_KERNEL_ASSERT : OFF -- Performing Test HAS_WMISSING_PROTOTYPES -- Performing Test HAS_WMISSING_PROTOTYPES - Failed -- Performing Test HAS_WERROR_MISSING_PROTOTYPES -- Performing Test HAS_WERROR_MISSING_PROTOTYPES - Failed -- Configuring incomplete, errors occurred! (pytorch_env) PS E:\PyTorch_Build\pytorch> # 永久修复conda命令不可用问题 (pytorch_env) PS E:\PyTorch_Build\pytorch> $condaPaths = @( >> "$env:USERPROFILE\miniconda3\Scripts", >> "$env:USERPROFILE\anaconda3\Scripts", >> "C:\ProgramData\miniconda3\Scripts" >> ) (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> foreach ($path in $condaPaths) { >> if (Test-Path $path) { >> $env:PATH = "$path;$env:PATH" >> [Environment]::SetEnvironmentVariable("PATH", $env:PATH, "Machine") >> break >> } >> } (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 验证修复 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda --version conda: The term 'conda' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> # 设置 cuDNN v9.12 路径 (pytorch_env) PS E:\PyTorch_Build\pytorch> $cudnnPath = "E:\Program Files\NVIDIA\CUNND\v9.12" (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 添加到环境变量 (pytorch_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_ROOT_DIR = $cudnnPath (pytorch_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_INCLUDE_DIR = "$cudnnPath\include" (pytorch_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_LIBRARY = "$cudnnPath\lib\x64\cudnn.lib" (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 永久生效 (pytorch_env) PS E:\PyTorch_Build\pytorch> [Environment]::SetEnvironmentVariable("CUDNN_ROOT_DIR", $cudnnPath, "Machine") (pytorch_env) PS E:\PyTorch_Build\pytorch> [Environment]::SetEnvironmentVariable("CUDNN_INCLUDE_DIR", "$cudnnPath\include", "Machine") (pytorch_env) PS E:\PyTorch_Build\pytorch> [Environment]::SetEnvironmentVariable("CUDNN_LIBRARY", "$cudnnPath\lib\x64\cudnn.lib", "Machine") (pytorch_env) PS E:\PyTorch_Build\pytorch> # 原始代码大约在 190 行左右 (pytorch_env) PS E:\PyTorch_Build\pytorch> # 替换为以下内容强制使用 v9.12: (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> set(CUDNN_VERSION "9.12.0") # 手动指定版本 CUDNN_VERSION: The term 'CUDNN_VERSION' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> set(CUDNN_FOUND TRUE) CUDNN_FOUND: The term 'CUDNN_FOUND' 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. (pytorch_env) PS E:\PyTorch_Build\pytorch> set(CUDNN_INCLUDE_DIR $ENV{CUDNN_INCLUDE_DIR}) InvalidOperation: The variable '$ENV' cannot be retrieved because it has not been set. (pytorch_env) PS E:\PyTorch_Build\pytorch> set(CUDNN_LIBRARY $ENV{CUDNN_LIBRARY}) InvalidOperation: The variable '$ENV' cannot be retrieved because it has not been set. (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> message(STATUS "Using manually configured cuDNN v${CUDNN_VERSION}") InvalidOperation: The variable '$CUDNN_VERSION' cannot be retrieved because it has not been set. (pytorch_env) PS E:\PyTorch_Build\pytorch> message(STATUS " Include path: ${CUDNN_INCLUDE_DIR}") InvalidOperation: The variable '$CUDNN_INCLUDE_DIR' cannot be retrieved because it has not been set. (pytorch_env) PS E:\PyTorch_Build\pytorch> message(STATUS " Library path: ${CUDNN_LIBRARY}") InvalidOperation: The variable '$CUDNN_LIBRARY' cannot be retrieved because it has not been set. (pytorch_env) PS E:\PyTorch_Build\pytorch> # 精确查找 conda.bat (pytorch_env) PS E:\PyTorch_Build\pytorch> $condaPath = Get-ChildItem -Path C:\ -Recurse -Filter conda.bat -ErrorAction SilentlyContinue | >> Select-Object -First 1 | >> ForEach-Object { $_.DirectoryName } (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> if ($condaPath) { >> $env:PATH = "$condaPath;$env:PATH" >> [Environment]::SetEnvironmentVariable("PATH", $env:PATH, "Machine") >> Write-Host "Conda found at: $condaPath" -ForegroundColor Green >> } else { >> Write-Host "Conda not found! Installing miniconda..." -ForegroundColor Yellow >> # 自动安装 miniconda >> Invoke-WebRequest -Uri "https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe" -OutFile "$env:TEMP\miniconda.exe" >> Start-Process -FilePath "$env:TEMP\miniconda.exe" -ArgumentList "/S", "/AddToPath=1", "/InstallationType=AllUsers", "/D=C:\Miniconda3" -Wait >> $env:PATH = "C:\Miniconda3\Scripts;$env:PATH" >> } Conda not found! Installing miniconda... /AddToPath=1 is disabled and ignored in 'All Users' installations Welcome to Miniconda3 py313_25.7.0-2 By continuing this installation you are accepting this license agreement: C:\Miniconda3\EULA.txt Please run the installer in GUI mode to read the details. Miniconda3 will now be installed into this location: C:\Miniconda3 Unpacking payload... Setting up the package cache... Setting up the base environment... Installing packages for base, creating shortcuts if necessary... Initializing conda directories... Setting installation directory permissions... Done! (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch>
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