卫星轨道的计算是利用计算机的,计算机简介 - Online typing test (en.kukuw.com)

本文概述了计算机的广泛用途,涵盖了科学计算、数据处理、过程控制、CAD/CAM/CAI/CAT、人工智能、计算机通信网络、办公自动化,强调了信息技术在各领域的深远影响。

计算机简介

Contributor:游客3049299 Type:简体中文 Date time:2015-06-29 16:03:22 Favorite:28 Score:0

返回上页

Report

请选择举报理由:

Advertising

Politically

Pornographic

Garbage article

Other

Collection

Modify the typo

计算机具有高速精确的计算能力,以及由此产生的超凡的数据处理能力、逻辑判断能力,

决定了计算机的应用相当广泛,涉及到科学研究、军事技术、工农业生产、文化教育、

日常生活等方面。

1、科学计算。也称数值计算,是利用计算机解决科学研究和工程设计等方面的数学计算问题。

科学计算的特点是计算量大,要求精度高,结果可靠。利用计算机高速性、大存储容量、连续

运算能力,可以处理人无法实现的各种科学计算问题。例如,人造卫星轨道的计算、宇宙飞船

的制导、气象预报等。

2、数据处理。数据处理指的是对信息进行采集、加工、存储、传递,并进行综合分析,常泛指

非科学计算方面的以管理为主的所有应用。例如,财务管理、统计分析、企业管理、商品销售

管理、档案管理、图书检索等。数据处理的特点是原始数据量大,算术运算较简单,有大量的

逻辑运算与判断,结果要求以表格或文件的形式存储或输出等。

3、过程控制。将计算机用来控制各种自动装置、自动仪表、生产过程等,都称为过程控制或实时控制。

例如,交通运输方面的行车调度,农业方面人工气候箱的温、湿度控制;工业生产自动化方面的巡回检测、

自动记录、监视报警、自动启停、自动调控等内容;家用电器中的某些自动功能等,都是计算机在过程控制

方面的应用。

4、计算机辅助系统。计算机辅助系统包括计算机辅助设计(CAD)、计算机辅助制造(CAM)、

计算机辅助教学(CAI)、计算机辅助测试(CAT)等。

5、人工智能。是用计算机执行某些与人的智能活动有关的复杂功能。目前研究的方向有:模式识别、

自然语言理解、自动定理证明、自动程序设计、知识表示、专家系统、数据智能检索等。例如,用计算机

模拟人脑的部分功能进行学习、推理、联想和决策;模拟著名医生给病人诊病的医疗诊断专家系统等等。

6、计算机通信、计算机网络。 利用通信设备和线路将地域不同的计算机系统互联起来,并在网络软件

支持下实现资源共享和传递信息的系统。大到遍及全世界的Internet,小到几台计算机联成的局域网,

计算机网络正在普遍应用。

7、办公自动化。是指用计算机或数据处理系统来处理日常例行的各种工作。是当前最为广泛的一类应用,

它具有完善的文字和表格处理功能,较强的资料、图像处理和网络通信能力,可以进行各种文档的存储、

查询、统计等工作。例如,起草各种文稿,收集、加工、输出各种资料信息等。

总之,计算机已在各个领域、行业中得到广泛的应用,其应用范围已渗透到科研、生产、军事、教学、金融、

交通、农林业、地质勘探、气象预报、邮电通信等各行各业,并且深入到文化、娱乐和家庭生活等各个领域,

其影响涉及社会生活的各个方面。

Last one:心灵捕手

Next one:北仑简介

声明:以上文章均为用户自行添加,仅供打字交流使用,不代表本站观点,本站不承担任何法律责任,特此声明!如果有侵犯到您的权利,请及时联系我们删除。

PowerShell 7 环境已加载 (版本: 7.5.2) 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> .\pytorch_env\Scripts\activate (pytorch_env) PS E:\PyTorch_Build\pytorch> # 退出虚拟环境 (pytorch_env) PS E:\PyTorch_Build\pytorch> deactivate PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 删除旧环境 PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force .\pytorch_env PS E:\PyTorch_Build\pytorch> Remove-Item -Recurse -Force .\cuda_env PS E:\PyTorch_Build\pytorch> PS E:\PyTorch_Build\pytorch> # 创建新虚拟环境 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> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装基础编译工具 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install -U pip setuptools wheel ninja cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (22.3.1) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/3f/945ef7ab14dc4f9d7f40288d2df998d1837ee0888ec3659c813487572faa/pip-25.2-py3-none-any.whl (1.8 MB) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) 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) Collecting wheel Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0b/2c/87f3254fd8ffd29e4c02732eee68a83a1d3c346ae39bc6822dcbcb697f2b/wheel-0.45.1-py3-none-any.whl (72 kB) Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) ERROR: To modify pip, please run the following command: E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe -m pip install -U pip setuptools wheel ninja cmake [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证 CUDA 安装 (rtx5070_env) PS E:\PyTorch_Build\pytorch> nvcc --version # 应显示 CUDA 12.x nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 正确更新 pip 和工具链 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python -m pip install -U pip setuptools wheel ninja cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pip in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (22.3.1) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/3f/945ef7ab14dc4f9d7f40288d2df998d1837ee0888ec3659c813487572faa/pip-25.2-py3-none-any.whl (1.8 MB) Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (65.5.0) 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) Collecting wheel Using cached https://pypi.tuna.tsinghua.edu.cn/packages/0b/2c/87f3254fd8ffd29e4c02732eee68a83a1d3c346ae39bc6822dcbcb697f2b/wheel-0.45.1-py3-none-any.whl (72 kB) Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) Installing collected packages: wheel, setuptools, pip, ninja, cmake Attempting uninstall: setuptools Found existing installation: setuptools 65.5.0 Uninstalling setuptools-65.5.0: Successfully uninstalled setuptools-65.5.0 Attempting uninstall: pip Found existing installation: pip 22.3.1 Uninstalling pip-22.3.1: Successfully uninstalled pip-22.3.1 Successfully installed cmake-4.1.0 ninja-1.13.0 pip-25.2 setuptools-80.9.0 wheel-0.45.1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip --version # 应显示 25.2+ pip 25.2 from E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\pip (python 3.10) (rtx5070_env) PS E:\PyTorch_Build\pytorch> cmake --version # 应显示 4.1.0+ cmake version 4.1.0 CMake suite maintained and supported by Kitware (kitware.com/cmake). (rtx5070_env) PS E:\PyTorch_Build\pytorch> ninja --version # 应显示 1.13.0+ 1.13.0.git.kitware.jobserver-pipe-1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置 CUDA 12.1 环境变量 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDA_PATH = "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:PATH = "$env:CUDA_PATH\bin;" + $env:PATH (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 验证 CUDA 版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> nvcc --version # 应显示 release 12.1 nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置 cuDNN 路径(根据实际安装位置) (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_INCLUDE_DIR = "$env:CUDA_PATH\include" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CUDNN_LIBRARY = "$env:CUDA_PATH\lib\x64\cudnn.lib" (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting pyyaml Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b5/84/0fa4b06f6d6c958d207620fc60005e241ecedceee58931bb20138e1e5776/PyYAML-6.0.2-cp310-cp310-win_amd64.whl (161 kB) Collecting numpy Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a3/dd/4b822569d6b96c39d1215dbae0582fd99954dcbcf0c1a13c61783feaca3f/numpy-2.2.6-cp310-cp310-win_amd64.whl (12.9 MB) Collecting typing_extensions Using cached https://pypi.tuna.tsinghua.edu.cn/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl (44 kB) Installing collected packages: typing_extensions, pyyaml, numpy Successfully installed numpy-2.2.6 pyyaml-6.0.2 typing_extensions-4.15.0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装 GPU 相关依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting mkl Using cached https://pypi.tuna.tsinghua.edu.cn/packages/91/ae/025174ee141432b974f97ecd2aea529a3bdb547392bde3dd55ce48fe7827/mkl-2025.2.0-py2.py3-none-win_amd64.whl (153.6 MB) Collecting mkl-include Using cached https://pypi.tuna.tsinghua.edu.cn/packages/06/87/3eee37bf95c6b820b6394ad98e50132798514ecda1b2584c71c2c96b973c/mkl_include-2025.2.0-py2.py3-none-win_amd64.whl (1.3 MB) Collecting intel-openmp Using cached https://pypi.tuna.tsinghua.edu.cn/packages/89/ed/13fed53fcc7ea17ff84095e89e63418df91d4eeefdc74454243d529bf5a3/intel_openmp-2025.2.1-py2.py3-none-win_amd64.whl (34.0 MB) Collecting tbb==2022.* (from mkl) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/4e/d2/01e2a93f9c644585088188840bf453f23ed1a2838ec51d5ba1ada1ebca71/tbb-2022.2.0-py3-none-win_amd64.whl (420 kB) Collecting intel-cmplr-lib-ur==2025.2.1 (from intel-openmp) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a8/70/938e81f58886fd4e114d5a5480d98c1396e73e40b7650f566ad0c4395311/intel_cmplr_lib_ur-2025.2.1-py2.py3-none-win_amd64.whl (1.2 MB) Collecting umf==0.11.* (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/33/a0/c8d755f08f50ddd99cb4a29a7e950ced7a0903cb72253e57059063609103/umf-0.11.0-py2.py3-none-win_amd64.whl (231 kB) Collecting tcmlib==1.* (from tbb==2022.*->mkl) Using cached https://pypi.tuna.tsinghua.edu.cn/packages/91/7b/e30c461a27b97e0090e4db822eeb1d37b310863241f8c3ee56f68df3e76e/tcmlib-1.4.0-py2.py3-none-win_amd64.whl (370 kB) Installing collected packages: tcmlib, mkl-include, umf, tbb, intel-cmplr-lib-ur, intel-openmp, mkl Successfully installed intel-cmplr-lib-ur-2025.2.1 intel-openmp-2025.2.1 mkl-2025.2.0 mkl-include-2025.2.0 tbb-2022.2.0 tcmlib-1.4.0 umf-0.11.0 (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (6.0.2) Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2.2.6) Requirement already satisfied: typing_extensions in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (4.15.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装 GPU 相关依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: mkl in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: mkl-include in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: intel-openmp in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.1) Requirement already satisfied: tbb==2022.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from mkl) (2022.2.0) Requirement already satisfied: intel-cmplr-lib-ur==2025.2.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-openmp) (2025.2.1) Requirement already satisfied: umf==0.11.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) (0.11.0) Requirement already satisfied: tcmlib==1.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from tbb==2022.*->mkl) (1.4.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:USE_CUDA=1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:USE_CUDNN=1 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:CMAKE_GENERATOR="Ninja" (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:MAX_JOBS=8 # 根据 CPU 核心数设置 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 运行编译 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --cmake-only ` >> --cmake-generator="Ninja" ` >> --verbose ` >> -DCMAKE_CUDA_COMPILER="${env:CUDA_PATH}\bin\nvcc.exe" ` >> -DCUDNN_INCLUDE_DIR="${env:CUDNN_INCLUDE_DIR}" ` >> -DCUDNN_LIBRARY="${env:CUDNN_LIBRARY}" ` >> -DTORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" Building wheel torch-2.9.0a0+git2d31c3d option --cmake-generator not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> python rtx5070_test.py ============================================================ Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\rtx5070_test.py", line 39, in <module> verify_gpu_support() File "E:\PyTorch_Build\pytorch\rtx5070_test.py", line 6, in verify_gpu_support if not torch.cuda.is_available(): AttributeError: module 'torch' has no attribute 'cuda' (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译架构参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:TORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用正确的编译命令 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --verbose ` >> -DCMAKE_CUDA_COMPILER="${env:CUDA_PATH}\bin\nvcc.exe" ` >> -DCUDNN_INCLUDE_DIR="${env:CUDNN_INCLUDE_DIR}" ` >> -DCUDNN_LIBRARY="${env:CUDNN_LIBRARY}" ` >> -DCMAKE_GENERATOR="Ninja" ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON Building wheel torch-2.9.0a0+git2d31c3d option -D not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> python enhanced_test.py ============================================================ Python 版本: 3.10.10 Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\enhanced_test.py", line 64, in <module> verify_installation() File "E:\PyTorch_Build\pytorch\enhanced_test.py", line 11, in verify_installation print(f"\nPyTorch 版本: {torch.__version__}") AttributeError: module 'torch' has no attribute '__version__' (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 清除之前的构建 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py clean --all 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) usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...] or: setup.py --help [cmd1 cmd2 ...] or: setup.py --help-commands or: setup.py cmd --help error: option --all not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 设置编译架构参数 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $env:TORCH_CUDA_ARCH_LIST="8.9;9.0;12.0" (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用正确的编译命令(Windows专用) (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py install ` >> --cmake ` >> --cmake-args="-DCMAKE_CUDA_COMPILER='$env:CUDA_PATH\bin\nvcc.exe' ` >> -DCUDNN_INCLUDE_DIR='$env:CUDNN_INCLUDE_DIR' ` >> -DCUDNN_LIBRARY='$env:CUDNN_LIBRARY' ` >> -DCMAKE_GENERATOR='Ninja' ` >> -DUSE_CUDA=ON ` >> -DUSE_CUDNN=ON" ` >> --verbose ` >> --jobs=$env:MAX_JOBS Building wheel torch-2.9.0a0+git2d31c3d option --cmake-args not recognized (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 使用 PyTorch 官方构建工具 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install -U setuptools wheel Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (80.9.0) Requirement already satisfied: wheel in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (0.45.1) (rtx5070_env) PS E:\PyTorch_Build\pytorch> python setup.py bdist_wheel Building wheel torch-2.9.0a0+git2d31c3d -- Building version 2.9.0a0+git2d31c3d E:\PyTorch_Build\pytorch\rtx5070_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_GENERATOR=Ninja -DCMAKE_INSTALL_PREFIX=E:\PyTorch_Build\pytorch\torch -DCMAKE_PREFIX_PATH=E:\PyTorch_Build\pytorch\rtx5070_env\Lib\site-packages -DCUDNN_INCLUDE_DIR=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\include -DCUDNN_LIBRARY=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.1\lib\x64\cudnn.lib -DPython_EXECUTABLE=E:\PyTorch_Build\pytorch\rtx5070_env\Scripts\python.exe -DPython_NumPy_INCLUDE_DIR=E:\PyTorch_Build\pytorch\rtx5070_env\lib\site-packages\numpy\_core\include -DTORCH_BUILD_VERSION=2.9.0a0+git2d31c3d -DTORCH_CUDA_ARCH_LIST=8.9;9.0;12.0 -DUSE_CUDA=1 -DUSE_CUDNN=1 -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\rtx5070_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 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_89,code=sm_89;-gencode;arch=compute_90,code=sm_90;-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 rtx5070_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\rtx5070_env\Scripts\python.exe (found version "3.10.10") found components: Interpreter Development.Module NumPy -- 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\rtx5070_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/rtx5070_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\rtx5070_env\Lib\site-packages;E:/Program Files/NVIDIA/CUNND/v9.12;E:\Program Files\NVIDIA\CUNND\v9.12;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/rtx5070_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) -- headers outputs: torch\csrc\inductor\aoti_torch\generated\c_shim_cpu.h not found torch\csrc\inductor\aoti_torch\generated\c_shim_cuda.h not found torch\csrc\inductor\aoti_torch\generated\c_shim_aten.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/rtx5070_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 -- NVSHMEM not found, not building with NVSHMEM support. CMake Error at torch/CMakeLists.txt:3 (add_subdirectory): The source directory E:/PyTorch_Build/pytorch/torch/csrc 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/rtx5070_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\rtx5070_env\Lib\site-packages;E:/Program Files/NVIDIA/CUNND/v9.12;E:\Program Files\NVIDIA\CUNND\v9.12;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\rtx5070_env\Scripts\python.exe -- Python library : E:/Python310/libs/python310.lib -- Python includes : E:/Python310/Include -- Python site-package : E:\PyTorch_Build\pytorch\rtx5070_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 : 1 -- 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_89,code=sm_89 -gencode arch=compute_90,code=sm_90 -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 : ON -- 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! (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装生成的包 (rtx5070_env) PS E:\PyTorch_Build\pytorch> $wheelPath = Get-ChildItem dist\*.whl | Select-Object -First 1 Get-ChildItem: Cannot find path 'E:\PyTorch_Build\pytorch\dist' because it does not exist. (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install $wheelPath --force-reinstall --no-deps ERROR: You must give at least one requirement to install (see "pip help install") (rtx5070_env) PS E:\PyTorch_Build\pytorch> python diagnostic_test.py ================================================== CUDA Toolkit 验证: ✅ NVCC 版本: nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 ✅ NVIDIA-SMI 输出: Mon Sep 1 20:54:10 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.97 Driver Version: 580.97 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Driver-Model | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce RTX 5070 WDDM | 00000000:01:00.0 On | N/A | | 0% 35C P3 16W / 250W | 1328MiB / 12227MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 1124 C+G ...yb3d8bbwe\WindowsTerminal.exe N/A | | 0 N/A N/A 1288 C+G ...les\Tencent\Weixin\Weixin.exe N/A | | 0 N/A N/A 1776 C+G C:\Windows\System32\dwm.exe N/A | | 0 N/A N/A 2272 C+G ...t\Edge\Application\msedge.exe N/A | | 0 N/A N/A 3268 C+G ...em32\ApplicationFrameHost.exe N/A | | 0 N/A N/A 7860 C+G C:\Windows\explorer.exe N/A | | 0 N/A N/A 8004 C+G ...indows\System32\ShellHost.exe N/A | | 0 N/A N/A 8156 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 8852 C+G ..._cw5n1h2txyewy\SearchHost.exe N/A | | 0 N/A N/A 8876 C+G ...y\StartMenuExperienceHost.exe N/A | | 0 N/A N/A 10540 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 12380 C+G ...5n1h2txyewy\TextInputHost.exe N/A | | 0 N/A N/A 15340 C+G ...acted\runtime\WeChatAppEx.exe N/A | | 0 N/A N/A 18600 C+G ...ntrolPanel\SystemSettings.exe N/A | +-----------------------------------------------------------------------------------------+ ================================================== ❌ 严重错误发生: Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 116, in <module> check_cuda_toolkit() File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 21, in check_cuda_toolkit cuda_path = os.environ.get('CUDA_PATH', '未设置') NameError: name 'os' is not defined 按 Enter 键退出... (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 卸载现有版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip uninstall -y torch torchvision torchaudio WARNING: Skipping torch as it is not installed. WARNING: Skipping torchvision as it is not installed. WARNING: Skipping torchaudio as it is not installed. (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装支持 RTX 5070 的预编译版本 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install --pre torch torchvision torchaudio ` >> --index-url https://download.pytorch.org/whl/nightly/cu121 ` >> --no-deps Looking in indexes: https://download.pytorch.org/whl/nightly/cu121 Collecting torch Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.6.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (2456.2 MB) Collecting torchvision Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.20.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (6.2 MB) Collecting torchaudio Using cached https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.5.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (4.2 MB) Installing collected packages: torchaudio, torchvision, torch Successfully installed torch-2.6.0.dev20241112+cu121 torchaudio-2.5.0.dev20241112+cu121 torchvision-0.20.0.dev20241112+cu121 (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 安装必要依赖 (rtx5070_env) PS E:\PyTorch_Build\pytorch> pip install pyyaml numpy typing_extensions mkl mkl-include intel-openmp Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Requirement already satisfied: pyyaml in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (6.0.2) Requirement already satisfied: numpy in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2.2.6) Requirement already satisfied: typing_extensions in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (4.15.0) Requirement already satisfied: mkl in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: mkl-include in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.0) Requirement already satisfied: intel-openmp in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (2025.2.1) Requirement already satisfied: tbb==2022.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from mkl) (2022.2.0) Requirement already satisfied: intel-cmplr-lib-ur==2025.2.1 in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-openmp) (2025.2.1) Requirement already satisfied: umf==0.11.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from intel-cmplr-lib-ur==2025.2.1->intel-openmp) (0.11.0) Requirement already satisfied: tcmlib==1.* in e:\pytorch_build\pytorch\rtx5070_env\lib\site-packages (from tbb==2022.*->mkl) (1.4.0) (rtx5070_env) PS E:\PyTorch_Build\pytorch> (rtx5070_env) PS E:\PyTorch_Build\pytorch> # 执行诊断测试 (rtx5070_env) PS E:\PyTorch_Build\pytorch> python diagnostic_test.py ================================================== CUDA Toolkit 验证: ✅ NVCC 版本: nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2025 NVIDIA Corporation Built on Wed_Jul_16_20:06:48_Pacific_Daylight_Time_2025 Cuda compilation tools, release 13.0, V13.0.48 Build cuda_13.0.r13.0/compiler.36260728_0 ✅ NVIDIA-SMI 输出: Mon Sep 1 20:55:52 2025 +-----------------------------------------------------------------------------------------+ | NVIDIA-SMI 580.97 Driver Version: 580.97 CUDA Version: 13.0 | +-----------------------------------------+------------------------+----------------------+ | GPU Name Driver-Model | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |=========================================+========================+======================| | 0 NVIDIA GeForce RTX 5070 WDDM | 00000000:01:00.0 On | N/A | | 0% 35C P3 19W / 250W | 1346MiB / 12227MiB | 0% Default | | | | N/A | +-----------------------------------------+------------------------+----------------------+ +-----------------------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=========================================================================================| | 0 N/A N/A 1124 C+G ...yb3d8bbwe\WindowsTerminal.exe N/A | | 0 N/A N/A 1288 C+G ...les\Tencent\Weixin\Weixin.exe N/A | | 0 N/A N/A 1776 C+G C:\Windows\System32\dwm.exe N/A | | 0 N/A N/A 2272 C+G ...t\Edge\Application\msedge.exe N/A | | 0 N/A N/A 3268 C+G ...em32\ApplicationFrameHost.exe N/A | | 0 N/A N/A 7860 C+G C:\Windows\explorer.exe N/A | | 0 N/A N/A 8004 C+G ...indows\System32\ShellHost.exe N/A | | 0 N/A N/A 8156 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 8852 C+G ..._cw5n1h2txyewy\SearchHost.exe N/A | | 0 N/A N/A 8876 C+G ...y\StartMenuExperienceHost.exe N/A | | 0 N/A N/A 10540 C+G ...0.3405.125\msedgewebview2.exe N/A | | 0 N/A N/A 12380 C+G ...5n1h2txyewy\TextInputHost.exe N/A | | 0 N/A N/A 15340 C+G ...acted\runtime\WeChatAppEx.exe N/A | | 0 N/A N/A 18600 C+G ...ntrolPanel\SystemSettings.exe N/A | +-----------------------------------------------------------------------------------------+ ================================================== ❌ 严重错误发生: Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 116, in <module> check_cuda_toolkit() File "E:\PyTorch_Build\pytorch\diagnostic_test.py", line 21, in check_cuda_toolkit cuda_path = os.environ.get('CUDA_PATH', '未设置') NameError: name 'os' is not defined 按 Enter 键退出... (rtx5070_env) PS E:\PyTorch_Build\pytorch>
最新发布
09-02
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> .\pytorch_env\Scripts\activate (pytorch_env) PS E:\PyTorch_Build\pytorch> # 移除可能导致冲突的镜像源 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --remove-key channels (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --remove-key default_channels CondaKeyError: 'default_channels': undefined in config (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 设置官方通道优先级 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --add channels pytorch-nightly C:\Miniconda3\Lib\site-packages\conda\base\context.py:211: FutureWarning: Adding 'defaults' to channel list implicitly is deprecated and will be removed in 25.9. To remove this warning, please choose a default channel explicitly with conda's regular configuration system, e.g. by adding 'defaults' to the list of channels: conda config --add channels defaults For more information see https://docs.conda.io/projects/conda/en/stable/user-guide/configuration/use-condarc.html deprecated.topic( (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --add channels nvidia (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --add channels conda-forge (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --add channels defaults Warning: 'defaults' already in 'channels' list, moving to the top (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 设置通道优先级为 strict(避免混合来源包) (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --set channel_priority strict (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 验证配置 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --show channels channels: - defaults - conda-forge - nvidia - pytorch-nightly (pytorch_env) PS E:\PyTorch_Build\pytorch> conda config --show channel_priority channel_priority: strict (pytorch_env) PS E:\PyTorch_Build\pytorch> # 1. 安装基础依赖 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda install -y python=3.10 cudatoolkit=12.1 cudnn numpy ninja 3 channel Terms of Service accepted Channels: - defaults - conda-forge - nvidia - pytorch-nightly Platform: win-64 Collecting package metadata (repodata.json): done Solving environment: failed LibMambaUnsatisfiableError: Encountered problems while solving: - unsupported request - package mkl-service-2.5.2-py313haca3b5c_0 requires python_abi 3.13.* *_cp313, but none of the providers can be instd Could not solve for environment specs The following packages are incompatible ├─ cudatoolkit =12.1 * does not exist (perhaps a typo or a missing channel); ├─ mkl-service =* * is installable with the potential options │ ├─ mkl-service 2.5.2 would require │ │ └─ python_abi =3.13 *_cp313 with the potential options │ │ ├─ python_abi 3.13 would require │ │ │ └─ python =3.13 *_cp313, which can be installed; │ │ └─ python_abi 3.13 conflicts with any installable versions previously reported; │ ├─ mkl-service 1.1.2 would require │ │ └─ mkl >=2019.1,<2021.0a0 *, which can be installed; │ ├─ mkl-service 1.1.2 would require │ │ └─ mkl >=2018.0.0,<2019.0a0 *, which can be installed; │ ├─ mkl-service 1.1.2 would require │ │ └─ mkl >=2018.0.3,<2019.0a0 *, which can be installed; │ ├─ mkl-service 2.0.2 would require │ │ └─ mkl >=2019.3,<2021.0a0 *, which can be installed; │ ├─ mkl-service 2.3.0 would require │ │ └─ mkl >=2019.4,<2021.0a0 *, which can be installed; │ ├─ mkl-service [2.3.0|2.4.0] would require │ │ └─ mkl >=2021.2.0,<2022.0a0 *, which can be installed; │ ├─ mkl-service 2.4.0 would require │ │ └─ mkl >=2021.4.0,<2022.0a0 *, which can be installed; │ ├─ mkl-service 2.4.0 would require │ │ └─ mkl >=2023.1.0,<2024.0a0 *, which can be installed; │ ├─ mkl-service 2.4.0 would require │ │ └─ mkl >=2025.0.0,<2026.0a0 *, which can be installed; │ └─ mkl-service [2.0.1|2.0.2|...|2.5.2] conflicts with any installable versions previously reported; ├─ mkl ==2024.2.2 * is not installable because it conflicts with any installable versions previously reported; └─ python =3.10 * is not installable because it conflicts with any installable versions previously reported. (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 2. 单独安装 PyTorch (pytorch_env) PS E:\PyTorch_Build\pytorch> conda install -y pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch-nightly -c nvidia 3 channel Terms of Service accepted Channels: - pytorch-nightly - nvidia - defaults - conda-forge Platform: win-64 Collecting package metadata (repodata.json): done Solving environment: failed LibMambaUnsatisfiableError: Encountered problems while solving: - package torchvision-0.20.0.dev20241112-py310_cu124 requires python >=3.10,<3.11.0a0, but none of the providers can d - package pytorch-2.5.0.dev20240618-py3.11_cuda12.4_cudnn8_0 requires mkl 2021.4.*, but none of the providers can be d - nothing provides pytorch 2.1.0.dev20230523 needed by torchaudio-2.1.0.dev20230523-py311_cu117 Could not solve for environment specs The following packages are incompatible ├─ libuv =1.44 * is requested and can be installed; ├─ mkl ==2024.2.2 * is requested and can be installed; ├─ pin on python 3.13.* =* * is installable and it requires │ └─ python =3.13 *, which can be installed; ├─ pytorch =* * is not installable because there are no viable options │ ├─ pytorch [2.5.0.dev20240618|2.5.0.dev20240619] would require │ │ └─ mkl =2021.4 *, which conflicts with any installable versions previously reported; │ ├─ pytorch [2.5.0.dev20240618|2.5.0.dev20240619|2.5.0.dev20240730|2.5.0.dev20240731|2.6.0.dev20241111] would require │ │ └─ mkl =2023.1 *, which conflicts with any installable versions previously reported; │ ├─ pytorch 2.6.0.dev20241112 would require │ │ ├─ libuv >=1.48.0,<2.0a0 *, which conflicts with any installable versions previously reported; │ │ └─ mkl =2023.1 *, which conflicts with any installable versions previously reported; │ └─ pytorch [1.0.1|1.10.2|...|2.7.1] conflicts with any installable versions previously reported; ├─ torchaudio =* * is not installable because there are no viable options │ ├─ torchaudio 2.1.0.dev20230523 would require │ │ └─ pytorch ==2.1.0.0dev20230523 *, which does not exist (perhaps a missing channel); │ ├─ torchaudio 2.4.0.dev20240729 would require │ │ └─ pytorch ==2.5.0.0dev20240726 *, which does not exist (perhaps a missing channel); │ ├─ torchaudio 2.4.0.dev20240729 would require │ │ └─ pytorch ==2.5.0.0dev20240729 *, which does not exist (perhaps a missing channel); │ ├─ torchaudio 2.4.0.dev20240729 would require │ │ └─ pytorch ==2.5.0.0dev20240728 *, which does not exist (perhaps a missing channel); │ ├─ torchaudio [2.5.0.dev20241112|2.5.0.dev20241113|...|2.5.0.dev20241118] would require │ │ └─ pytorch ==2.6.0.0dev20241112 *, which cannot be installed (as previously explained); │ └─ torchaudio 2.5.1 conflicts with any installable versions previously reported; └─ torchvision =* * is not installable because there are no viable options ├─ torchvision [0.20.0.dev20241112|0.20.0.dev20241113|...|0.20.0.dev20241118] would require │ └─ python >=3.9,<3.10.0a0 *, which conflicts with any installable versions previously reported; ├─ torchvision [0.20.0.dev20241112|0.20.0.dev20241113|...|0.20.0.dev20241118] would require │ └─ python >=3.10,<3.11.0a0 *, which conflicts with any installable versions previously reported; ├─ torchvision [0.20.0.dev20241112|0.20.0.dev20241113|...|0.20.0.dev20241118] would require │ └─ python >=3.11,<3.12.0a0 *, which conflicts with any installable versions previously reported; ├─ torchvision [0.20.0.dev20241112|0.20.0.dev20241113|...|0.20.0.dev20241118] would require │ └─ python >=3.12,<3.13.0a0 *, which conflicts with any installable versions previously reported; └─ torchvision [0.11.3|0.13.1|...|0.22.0] conflicts with any installable versions previously reported. Pins seem to be involved in the conflict. Currently pinned specs: - python=3.13 (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 3. 安装补充依赖 (pytorch_env) PS E:\PyTorch_Build\pytorch> conda install -y pyyaml mkl mkl-include setuptools cmake cffi typing_extensions 3 channel Terms of Service accepted Channels: - defaults - conda-forge - nvidia - pytorch-nightly Platform: win-64 Collecting package metadata (repodata.json): done Solving environment: done ## Package Plan ## environment location: C:\Miniconda3 added / updated specs: - cffi - cmake - mkl - mkl-include - pyyaml - setuptools - typing_extensions The following packages will be downloaded: package | build ---------------------------|----------------- cmake-3.26.4 | h693b641_0 12.0 MB defaults pyyaml-6.0.2 | py313h827c3e9_0 198 KB defaults yaml-0.2.5 | he774522_0 62 KB defaults ------------------------------------------------------------ Total: 12.2 MB The following NEW packages will be INSTALLED: cmake pkgs/main/win-64::cmake-3.26.4-h693b641_0 pyyaml pkgs/main/win-64::pyyaml-6.0.2-py313h827c3e9_0 yaml pkgs/main/win-64::yaml-0.2.5-he774522_0 Downloading and Extracting Packages: Preparing transaction: done Verifying transaction: done Executing transaction: done (pytorch_env) PS E:\PyTorch_Build\pytorch> python cuda_test.py ================================================== PyTorch 版本: 2.6.0.dev20241112+cu121 CUDA 可用: True CUDA 版本: 12.1 cuDNN 版本: 90100 E:\PyTorch_Build\pytorch\pytorch_env\lib\site-packages\torch\cuda\__init__.py:235: UserWarning: NVIDIA GeForce RTX 5070 with CUDA capability sm_120 is not compatible with the current PyTorch installation. The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90. If you want to use the NVIDIA GeForce RTX 5070 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/ warnings.warn( GPU 型号: NVIDIA GeForce RTX 5070 计算能力: (12, 0) Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\cuda_test.py", line 25, in <module> check_cuda() File "E:\PyTorch_Build\pytorch\cuda_test.py", line 16, in check_cuda a = torch.randn(1000, 1000, device='cuda') RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. (pytorch_env) PS E:\PyTorch_Build\pytorch> (pytorch_env) PS E:\PyTorch_Build\pytorch> # 创建新的虚拟环境 (pytorch_env) PS E:\PyTorch_Build\pytorch> python -m venv cuda_env (pytorch_env) PS E:\PyTorch_Build\pytorch> .\cuda_env\Scripts\activate (cuda_env) PS E:\PyTorch_Build\pytorch> (cuda_env) PS E:\PyTorch_Build\pytorch> # 安装基础依赖 (cuda_env) PS E:\PyTorch_Build\pytorch> pip install numpy==1.26.4 ninja pyyaml mkl mkl-include setuptools cmake Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting numpy==1.26.4 Downloading https://pypi.tuna.tsinghua.edu.cn/packages/19/77/538f202862b9183f54108557bfda67e17603fc560c384559e769321c9d92/numpy-1.26.4-cp310-cp310-win_amd64.whl (15.8 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.8/15.8 MB 34.6 MB/s eta 0:00:00 Collecting ninja Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/45/c0adfbfb0b5895aa18cec400c535b4f7ff3e52536e0403602fc1a23f7de9/ninja-1.13.0-py3-none-win_amd64.whl (309 kB) Collecting pyyaml Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b5/84/0fa4b06f6d6c958d207620fc60005e241ecedceee58931bb20138e1e5776/PyYAML-6.0.2-cp310-cp310-win_amd64.whl (161 kB) Collecting mkl Downloading https://pypi.tuna.tsinghua.edu.cn/packages/91/ae/025174ee141432b974f97ecd2aea529a3bdb547392bde3dd55ce48fe7827/mkl-2025.2.0-py2.py3-none-win_amd64.whl (153.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 153.6/153.6 MB 24.2 MB/s eta 0:00:00 Collecting mkl-include Downloading https://pypi.tuna.tsinghua.edu.cn/packages/06/87/3eee37bf95c6b820b6394ad98e50132798514ecda1b2584c71c2c96b973c/mkl_include-2025.2.0-py2.py3-none-win_amd64.whl (1.3 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.3/1.3 MB 87.9 MB/s eta 0:00:00 Requirement already satisfied: setuptools in e:\pytorch_build\pytorch\cuda_env\lib\site-packages (65.5.0) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/7c/d0/73cae88d8c25973f2465d5a4457264f95617c16ad321824ed4c243734511/cmake-4.1.0-py3-none-win_amd64.whl (37.6 MB) Collecting tbb==2022.* Downloading https://pypi.tuna.tsinghua.edu.cn/packages/4e/d2/01e2a93f9c644585088188840bf453f23ed1a2838ec51d5ba1ada1ebca71/tbb-2022.2.0-py3-none-win_amd64.whl (420 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 420.6/420.6 kB ? eta 0:00:00 Collecting intel-openmp<2026,>=2024 Downloading https://pypi.tuna.tsinghua.edu.cn/packages/89/ed/13fed53fcc7ea17ff84095e89e63418df91d4eeefdc74454243d529bf5a3/intel_openmp-2025.2.1-py2.py3-none-win_amd64.whl (34.0 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 34.0/34.0 MB 43.5 MB/s eta 0:00:00 Collecting tcmlib==1.* Downloading https://pypi.tuna.tsinghua.edu.cn/packages/91/7b/e30c461a27b97e0090e4db822eeb1d37b310863241f8c3ee56f68df3e76e/tcmlib-1.4.0-py2.py3-none-win_amd64.whl (370 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 370.3/370.3 kB ? eta 0:00:00 Collecting intel-cmplr-lib-ur==2025.2.1 Downloading https://pypi.tuna.tsinghua.edu.cn/packages/a8/70/938e81f58886fd4e114d5a5480d98c1396e73e40b7650f566ad0c4395311/intel_cmplr_lib_ur-2025.2.1-py2.py3-none-win_amd64.whl (1.2 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.2/1.2 MB 72.4 MB/s eta 0:00:00 Collecting umf==0.11.* Downloading https://pypi.tuna.tsinghua.edu.cn/packages/33/a0/c8d755f08f50ddd99cb4a29a7e950ced7a0903cb72253e57059063609103/umf-0.11.0-py2.py3-none-win_amd64.whl (231 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 231.7/231.7 kB ? eta 0:00:00 Installing collected packages: tcmlib, mkl-include, umf, tbb, pyyaml, numpy, ninja, cmake, intel-cmplr-lib-ur, intel-openmp, mkl Successfully installed cmake-4.1.0 intel-cmplr-lib-ur-2025.2.1 intel-openmp-2025.2.1 mkl-2025.2.0 mkl-include-2025.2.0 ninja-1.13.0 numpy-1.26.4 pyyaml-6.0.2 tbb-2022.2.0 tcmlib-1.4.0 umf-0.11.0 [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (cuda_env) PS E:\PyTorch_Build\pytorch> (cuda_env) PS E:\PyTorch_Build\pytorch> # 安装 PyTorch Nightly (cuda_env) PS E:\PyTorch_Build\pytorch> pip install --pre torch torchvision torchaudio ` >> --index-url https://download.pytorch.org/whl/nightly/cu121 ` >> --no-deps Looking in indexes: https://download.pytorch.org/whl/nightly/cu121 Collecting torch Using cached https://download.pytorch.org/whl/nightly/cu121/torch-2.6.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (2456.2 MB) Collecting torchvision Using cached https://download.pytorch.org/whl/nightly/cu121/torchvision-0.20.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (6.2 MB) Collecting torchaudio Using cached https://download.pytorch.org/whl/nightly/cu121/torchaudio-2.5.0.dev20241112%2Bcu121-cp310-cp310-win_amd64.whl (4.2 MB) Installing collected packages: torchaudio, torchvision, torch Successfully installed torch-2.6.0.dev20241112+cu121 torchaudio-2.5.0.dev20241112+cu121 torchvision-0.20.0.dev20241112+cu121 [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (cuda_env) PS E:\PyTorch_Build\pytorch> (cuda_env) PS E:\PyTorch_Build\pytorch> # 安装补充依赖 (cuda_env) PS E:\PyTorch_Build\pytorch> pip install typing_extensions future six requests dataclasses Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting typing_extensions Using cached https://pypi.tuna.tsinghua.edu.cn/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl (44 kB) Collecting future Downloading https://pypi.tuna.tsinghua.edu.cn/packages/da/71/ae30dadffc90b9006d77af76b393cb9dfbfc9629f339fc1574a1c52e6806/future-1.0.0-py3-none-any.whl (491 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 491.3/491.3 kB 1.5 MB/s eta 0:00:00 Collecting six Using cached https://pypi.tuna.tsinghua.edu.cn/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl (11 kB) Collecting requests Using cached https://pypi.tuna.tsinghua.edu.cn/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl (64 kB) Collecting dataclasses Downloading https://pypi.tuna.tsinghua.edu.cn/packages/26/2f/1095cdc2868052dd1e64520f7c0d5c8c550ad297e944e641dbf1ffbb9a5d/dataclasses-0.6-py3-none-any.whl (14 kB) Collecting charset_normalizer<4,>=2 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/e2/c6/f05db471f81af1fa01839d44ae2a8bfeec8d2a8b4590f16c4e7393afd323/charset_normalizer-3.4.3-cp310-cp310-win_amd64.whl (107 kB) Collecting idna<4,>=2.5 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/76/c6/c88e154df9c4e1a2a66ccf0005a88dfb2650c1dffb6f5ce603dfbd452ce3/idna-3.10-py3-none-any.whl (70 kB) Collecting urllib3<3,>=1.21.1 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/a7/c2/fe1e52489ae3122415c51f387e221dd0773709bad6c6cdaa599e8a2c5185/urllib3-2.5.0-py3-none-any.whl (129 kB) Collecting certifi>=2017.4.17 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/e5/48/1549795ba7742c948d2ad169c1c8cdbae65bc450d6cd753d124b17c8cd32/certifi-2025.8.3-py3-none-any.whl (161 kB) Installing collected packages: dataclasses, urllib3, typing_extensions, six, idna, future, charset_normalizer, certifi, requests ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. torch 2.6.0.dev20241112+cu121 requires filelock, which is not installed. torch 2.6.0.dev20241112+cu121 requires fsspec, which is not installed. torch 2.6.0.dev20241112+cu121 requires jinja2, which is not installed. torch 2.6.0.dev20241112+cu121 requires networkx, which is not installed. torch 2.6.0.dev20241112+cu121 requires sympy==1.13.1; python_version >= "3.9", which is not installed. Successfully installed certifi-2025.8.3 charset_normalizer-3.4.3 dataclasses-0.6 future-1.0.0 idna-3.10 requests-2.32.5 six-1.17.0 typing_extensions-4.15.0 urllib3-2.5.0 [notice] A new release of pip available: 22.3.1 -> 25.2 [notice] To update, run: python.exe -m pip install --upgrade pip (cuda_env) PS E:\PyTorch_Build\pytorch> (cuda_env) PS E:\PyTorch_Build\pytorch> # 运行验证脚本 (cuda_env) PS E:\PyTorch_Build\pytorch> python cuda_test.py ================================================== PyTorch 版本: 2.6.0.dev20241112+cu121 CUDA 可用: True CUDA 版本: 12.1 cuDNN 版本: 90100 E:\PyTorch_Build\pytorch\cuda_env\lib\site-packages\torch\cuda\__init__.py:235: UserWarning: NVIDIA GeForce RTX 5070 with CUDA capability sm_120 is not compatible with the current PyTorch installation. The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90. If you want to use the NVIDIA GeForce RTX 5070 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/ warnings.warn( GPU 型号: NVIDIA GeForce RTX 5070 计算能力: (12, 0) Traceback (most recent call last): File "E:\PyTorch_Build\pytorch\cuda_test.py", line 25, in <module> check_cuda() File "E:\PyTorch_Build\pytorch\cuda_test.py", line 16, in check_cuda a = torch.randn(1000, 1000, device='cuda') RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions. (cuda_env) PS E:\PyTorch_Build\pytorch>
09-02
评论
成就一亿技术人!
拼手气红包6.0元
还能输入1000个字符  | 博主筛选后可见
 
红包 添加红包
表情包 插入表情
 条评论被折叠 查看
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值