AMD C1E SUPPORT

C1E电源管理:节能新策略优化12核处理器
本文探讨了C1E状态在处理器节能上的创新应用,包括降低内存时钟、关闭HT技术,以及如何在电脑空闲时自动调整CPU频率。CIE技术不仅限于倍频调节,还涉及平台整体能耗降低,保持设备待机状态下的高效能。
•C1E是一种电源管理状态,它可以让处理器节能不限于处理器内核。在CIE状态,可以通过降低内存时钟速度、关闭HT技术,来降低处理器能耗。这种新功能对于12核的处理器极其重要,因为这种处理器在设计上既增加了内存通道的支持,又增加了HT连接技术。
•总得来说,它能在电脑不太忙时,自动降低CPU的倍频(把CPU的速度降下来),是一种节能的方法。
•但是CIE技术还不仅限于降低CPU倍频。它还可以把处理器之间、处理器与主板芯片组之间的连接,调至低能耗状态,从而让整个平台减少能耗,但仍然处理处于开机状态。
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>
09-02
root@6bd7645dca4a:/# apt install python3.7 Reading package lists... Done Building dependency tree Reading state information... Done The following packages were automatically installed and are no longer required: cron fontconfig-config fonts-dejavu-core iso-codes java-common kmod libapt-inst2.0 libavahi-client3 libavahi-common-data libavahi-common3 libcups2 libfontconfig1 libjpeg-turbo8 libjpeg8 libkmod2 liblcms2-2 libpcsclite1 librhash0 libx11-6 libx11-data libxau6 libxcb1 libxdmcp6 libxext6 libxi6 libxrender1 libxtst6 powermgmt-base python-apt-common python-six python3-apt python3-dbus python3-gi python3-software-properties unattended-upgrades x11-common Use 'apt autoremove' to remove them. The following additional packages will be installed: libpython3.7-minimal libpython3.7-stdlib python3.7-minimal Suggested packages: python3.7-venv python3.7-doc binfmt-support The following NEW packages will be installed: libpython3.7-minimal libpython3.7-stdlib python3.7 python3.7-minimal 0 upgraded, 4 newly installed, 0 to remove and 1 not upgraded. Need to get 546 kB/4273 kB of archives. After this operation, 22.5 MB of additional disk space will be used. Do you want to continue? [Y/n] y Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 [546 kB] Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 [546 kB] Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 [546 kB] Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 [546 kB] Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 [546 kB] Get:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 [546 kB] Err:1 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 libpython3.7-minimal amd64 3.7.5-2ubuntu1~18.04.2 Hash Sum mismatch Hashes of expected file: - SHA512:63c1a4ca1b3823c4bcae616f55eed5dabfbf3ecf2c5075ce520a16bdb45cae94d80dcade924c6bea9937616f357972800b06f0b0a827f0d69ea4eb62e9becf9e - SHA256:c069fe4c3f03b9e02b85e44ae3c1c6245c4fea165ef3c6dd636039c199d6c767 - SHA1:0bce187d519c5c0ae6347d01cf5cd6d948bb3a94 [weak] - MD5Sum:fd46d39cf52d506906a2e2eda7566ddd [weak] - Filesize:545944 [weak] Hashes of received file: - SHA512:dd586983366c3ff15fe974f24bb3a362d280783b2f945777a0efa3c719dcdf849db52f1f04f52735b6fa66ef17aa300ce754459caa7d7219e361ca4775c7bc13 - SHA256:5c51ad7fc399d4a11ba98837492f2a4e8beb3a2d0afb6ed9556a2ba4746f321b - SHA1:a7f8e9346db9fd91600f0eddb24520e8a385bac7 [weak] - MD5Sum:3634a3af2f2588dd7dfbc029a6edda44 [weak] - Filesize:545944 [weak] Last modification reported: Wed, 15 Dec 2021 21:19:14 +0000 Fetched 415 kB in 9s (47.5 kB/s) E: Failed to fetch http://archive.ubuntu.com/ubuntu/pool/universe/p/python3.7/libpython3.7-minimal_3.7.5-2ubuntu1~18.04.2_amd64.deb Hash Sum mismatch Hashes of expected file: - SHA512:63c1a4ca1b3823c4bcae616f55eed5dabfbf3ecf2c5075ce520a16bdb45cae94d80dcade924c6bea9937616f357972800b06f0b0a827f0d69ea4eb62e9becf9e - SHA256:c069fe4c3f03b9e02b85e44ae3c1c6245c4fea165ef3c6dd636039c199d6c767 - SHA1:0bce187d519c5c0ae6347d01cf5cd6d948bb3a94 [weak] - MD5Sum:fd46d39cf52d506906a2e2eda7566ddd [weak] - Filesize:545944 [weak] Hashes of received file: - SHA512:dd586983366c3ff15fe974f24bb3a362d280783b2f945777a0efa3c719dcdf849db52f1f04f52735b6fa66ef17aa300ce754459caa7d7219e361ca4775c7bc13 - SHA256:5c51ad7fc399d4a11ba98837492f2a4e8beb3a2d0afb6ed9556a2ba4746f321b - SHA1:a7f8e9346db9fd91600f0eddb24520e8a385bac7 [weak] - MD5Sum:3634a3af2f2588dd7dfbc029a6edda44 [weak] - Filesize:545944 [weak] Last modification reported: Wed, 15 Dec 2021 21:19:14 +0000 E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
11-08
error: subprocess-exited-with-error × pip subprocess to install build dependencies did not run successfully. │ exit code: 1 ╰─> [249 lines of output] Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Ignoring numpy: markers 'python_version == "3.6"' don't match your environment Ignoring numpy: markers 'python_version == "3.7"' don't match your environment Ignoring numpy: markers 'python_version == "3.8"' don't match your environment 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 scikit-build Using cached https://pypi.tuna.tsinghua.edu.cn/packages/c3/a3/21b519f58de90d684056c52ec4e45f744cfda7483f082dcc4dd18cc74a93/scikit_build-0.18.1-py3-none-any.whl (85 kB) Collecting cmake Using cached https://pypi.tuna.tsinghua.edu.cn/packages/16/1a/6504170f8cfadde043ed5dabadcca8af50545094428ed74c44c1eac3903f/cmake-4.0.2-py3-none-win_amd64.whl (36.7 MB) Collecting pip Using cached https://pypi.tuna.tsinghua.edu.cn/packages/29/a2/d40fb2460e883eca5199c62cfc2463fd261f760556ae6290f88488c362c0/pip-25.1.1-py3-none-any.whl (1.8 MB) Collecting numpy==1.19.3 Using cached https://pypi.tuna.tsinghua.edu.cn/packages/cb/c0/7b3d69e6ee68bc54c97ba51f8c3c3e43ff1dbc7bd97347cc19a1f944e60a/numpy-1.19.3.zip (7.3 MB) Installing build dependencies: started Installing build dependencies: finished with status 'done' Getting requirements to build wheel: started Getting requirements to build wheel: finished with status 'done' Preparing metadata (pyproject.toml): started Preparing metadata (pyproject.toml): finished with status 'error' error: subprocess-exited-with-error Preparing metadata (pyproject.toml) did not run successfully. exit code: 1 [210 lines of output] setup.py:67: RuntimeWarning: NumPy 1.19.3 may not yet support Python 3.11. warnings.warn( Running from numpy source directory. setup.py:480: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates run_build = parse_setuppy_commands() Processing numpy/random\_bounded_integers.pxd.in Processing numpy/random\bit_generator.pyx Processing numpy/random\mtrand.pyx Processing numpy/random\_bounded_integers.pyx.in Processing numpy/random\_common.pyx Processing numpy/random\_generator.pyx Processing numpy/random\_mt19937.pyx Processing numpy/random\_pcg64.pyx Processing numpy/random\_philox.pyx Processing numpy/random\_sfc64.pyx Cythonizing sources blas_opt_info: blas_mkl_info: No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler libraries mkl_rt not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE blis_info: libraries blis not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE openblas_info: libraries openblas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] get_default_fcompiler: matching types: '['gnu', 'intelv', 'absoft', 'compaqv', 'intelev', 'gnu95', 'g95', 'intelvem', 'intelem', 'flang']' customize GnuFCompiler Could not locate executable g77 Could not locate executable f77 customize IntelVisualFCompiler Could not locate executable ifort Could not locate executable ifl customize AbsoftFCompiler Could not locate executable f90 customize CompaqVisualFCompiler Could not locate executable DF customize IntelItaniumVisualFCompiler Could not locate executable efl customize Gnu95FCompiler Could not locate executable gfortran Could not locate executable f95 customize G95FCompiler Could not locate executable g95 customize IntelEM64VisualFCompiler customize IntelEM64TFCompiler Could not locate executable efort Could not locate executable efc customize PGroupFlangCompiler Could not locate executable flang don't know how to compile Fortran code on platform 'nt' NOT AVAILABLE atlas_3_10_blas_threads_info: Setting PTATLAS=ATLAS libraries tatlas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE atlas_3_10_blas_info: libraries satlas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE atlas_blas_threads_info: Setting PTATLAS=ATLAS libraries ptf77blas,ptcblas,atlas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE atlas_blas_info: libraries f77blas,cblas,atlas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE accelerate_info: NOT AVAILABLE C:\Users\86173\AppData\Local\Temp\pip-install-ypcwxt_7\numpy_f4145497f17344839591dbdeb21803be\numpy\distutils\system_info.py:1914: UserWarning: Optimized (vendor) Blas libraries are not found. Falls back to netlib Blas library which has worse performance. A better performance should be easily gained by switching Blas library. if self._calc_info(blas): blas_info: libraries blas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE C:\Users\86173\AppData\Local\Temp\pip-install-ypcwxt_7\numpy_f4145497f17344839591dbdeb21803be\numpy\distutils\system_info.py:1914: UserWarning: Blas (http://www.netlib.org/blas/) libraries not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [blas]) or by setting the BLAS environment variable. if self._calc_info(blas): blas_src_info: NOT AVAILABLE C:\Users\86173\AppData\Local\Temp\pip-install-ypcwxt_7\numpy_f4145497f17344839591dbdeb21803be\numpy\distutils\system_info.py:1914: UserWarning: Blas (http://www.netlib.org/blas/) sources not found. Directories to search for the sources can be specified in the numpy/distutils/site.cfg file (section [blas_src]) or by setting the BLAS_SRC environment variable. if self._calc_info(blas): NOT AVAILABLE non-existing path in 'numpy\\distutils': 'site.cfg' lapack_opt_info: lapack_mkl_info: libraries mkl_rt not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE openblas_lapack_info: libraries openblas not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE openblas_clapack_info: libraries openblas,lapack not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE flame_info: libraries flame not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE atlas_3_10_threads_info: Setting PTATLAS=ATLAS libraries lapack_atlas not found in E:\anaconda\lib libraries tatlas,tatlas not found in E:\anaconda\lib libraries lapack_atlas not found in C:\ libraries tatlas,tatlas not found in C:\ libraries lapack_atlas not found in E:\anaconda\libs libraries tatlas,tatlas not found in E:\anaconda\libs libraries lapack_atlas not found in E:\anaconda\Library\lib libraries tatlas,tatlas not found in E:\anaconda\Library\lib <class 'numpy.distutils.system_info.atlas_3_10_threads_info'> NOT AVAILABLE atlas_3_10_info: libraries lapack_atlas not found in E:\anaconda\lib libraries satlas,satlas not found in E:\anaconda\lib libraries lapack_atlas not found in C:\ libraries satlas,satlas not found in C:\ libraries lapack_atlas not found in E:\anaconda\libs libraries satlas,satlas not found in E:\anaconda\libs libraries lapack_atlas not found in E:\anaconda\Library\lib libraries satlas,satlas not found in E:\anaconda\Library\lib <class 'numpy.distutils.system_info.atlas_3_10_info'> NOT AVAILABLE atlas_threads_info: Setting PTATLAS=ATLAS libraries lapack_atlas not found in E:\anaconda\lib libraries ptf77blas,ptcblas,atlas not found in E:\anaconda\lib libraries lapack_atlas not found in C:\ libraries ptf77blas,ptcblas,atlas not found in C:\ libraries lapack_atlas not found in E:\anaconda\libs libraries ptf77blas,ptcblas,atlas not found in E:\anaconda\libs libraries lapack_atlas not found in E:\anaconda\Library\lib libraries ptf77blas,ptcblas,atlas not found in E:\anaconda\Library\lib <class 'numpy.distutils.system_info.atlas_threads_info'> NOT AVAILABLE atlas_info: libraries lapack_atlas not found in E:\anaconda\lib libraries f77blas,cblas,atlas not found in E:\anaconda\lib libraries lapack_atlas not found in C:\ libraries f77blas,cblas,atlas not found in C:\ libraries lapack_atlas not found in E:\anaconda\libs libraries f77blas,cblas,atlas not found in E:\anaconda\libs libraries lapack_atlas not found in E:\anaconda\Library\lib libraries f77blas,cblas,atlas not found in E:\anaconda\Library\lib <class 'numpy.distutils.system_info.atlas_info'> NOT AVAILABLE lapack_info: libraries lapack not found in ['E:\\anaconda\\lib', 'C:\\', 'E:\\anaconda\\libs', 'E:\\anaconda\\Library\\lib'] NOT AVAILABLE C:\Users\86173\AppData\Local\Temp\pip-install-ypcwxt_7\numpy_f4145497f17344839591dbdeb21803be\numpy\distutils\system_info.py:1748: UserWarning: Lapack (http://www.netlib.org/lapack/) libraries not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [lapack]) or by setting the LAPACK environment variable. return getattr(self, '_calc_info_{}'.format(name))() lapack_src_info: NOT AVAILABLE C:\Users\86173\AppData\Local\Temp\pip-install-ypcwxt_7\numpy_f4145497f17344839591dbdeb21803be\numpy\distutils\system_info.py:1748: UserWarning: Lapack (http://www.netlib.org/lapack/) sources not found. Directories to search for the sources can be specified in the numpy/distutils/site.cfg file (section [lapack_src]) or by setting the LAPACK_SRC environment variable. return getattr(self, '_calc_info_{}'.format(name))() NOT AVAILABLE numpy_linalg_lapack_lite: FOUND: language = c define_macros = [('HAVE_BLAS_ILP64', None), ('BLAS_SYMBOL_SUFFIX', '64_')] C:\Users\86173\AppData\Local\Temp\pip-build-env-kc9oajwe\overlay\Lib\site-packages\setuptools\_distutils\dist.py:275: UserWarning: Unknown distribution option: 'define_macros' warnings.warn(msg) running dist_info running build_src build_src building py_modules sources creating build creating build\src.win-amd64-3.11 creating build\src.win-amd64-3.11\numpy creating build\src.win-amd64-3.11\numpy\distutils building library "npymath" sources error: Microsoft Visual C++ 14.0 is required. Get it with "Build Tools for Visual Studio": https://visualstudio.microsoft.com/downloads/ [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed Encountered error while generating package metadata. See above for output. note: This is an issue with the package mentioned above, not pip. hint: See above for details. [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. error: subprocess-exited-with-error × pip subprocess to install build dependencies did not run successfully. │ exit code: 1 ╰─> See above for output. note: This error originates from a subprocess, and is likely not a problem with pip.
06-10
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