{"id":65344,"date":"2026-01-24T21:05:08","date_gmt":"2026-01-24T13:05:08","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/65344.html"},"modified":"2026-01-24T21:05:08","modified_gmt":"2026-01-24T13:05:08","slug":"python-%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%ef%bc%9a%e5%ae%89%e8%a3%85-anaconda%e3%80%81pytorch%ef%bc%88gpu-%e7%89%88%ef%bc%89%e5%ba%93%e4%b8%8e-pycharm","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/65344.html","title":{"rendered":"Python \u6df1\u5ea6\u5b66\u4e60\uff1a\u5b89\u88c5 Anaconda\u3001PyTorch\uff08GPU \u7248\uff09\u5e93\u4e0e PyCharm"},"content":{"rendered":"<\/p>\n<h4>\u6587\u7ae0\u76ee\u5f55<\/h4>\n<ul>\n<li>\n<ul>\n<li>\u5907\u6ce8<\/li>\n<li>\u5b89\u88c5 Anaconda<\/li>\n<li>\n<ul>\n<li>\u5378\u8f7d Anaconda&#xff08;\u53ef\u9009&#xff09;<\/li>\n<li>\u5b89\u88c5 Anaconda<\/li>\n<\/ul>\n<\/li>\n<li>\u5b89\u88c5 PyTorch&#xff08;GPU \u7248&#xff09;\u5e93<\/li>\n<li>\n<ul>\n<li>\u5b89\u88c5 CUDA&#xff08;\u53ef\u9009&#xff09;<\/li>\n<li>\u5b89\u88c5 PyTorch<\/li>\n<li>\u68c0\u9a8c cuda \u662f\u5426\u53ef\u7528<\/li>\n<\/ul>\n<\/li>\n<li>Jupyter \u4ee3\u7801\u7f16\u8f91\u5668<\/li>\n<li>\n<ul>\n<li>\u4fee\u6539\u5de5\u4f5c\u8def\u5f84&#xff08;\u53ef\u9009&#xff09;<\/li>\n<li>\u865a\u62df\u73af\u5883\u8fde\u63a5 Jupyter<\/li>\n<\/ul>\n<\/li>\n<li>PyCharm \u4ee3\u7801\u7f16\u8f91\u5668<\/li>\n<li>\n<ul>\n<li>\u5378\u8f7d PyCharm&#xff08;\u53ef\u9009&#xff09;<\/li>\n<li>\u5b89\u88c5 PyCharm<\/li>\n<li>\u865a\u62df\u73af\u5883\u8fde\u63a5 PyCharm<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3>\u5907\u6ce8<\/h3>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130504-6974c380dcc18.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h3>\u5b89\u88c5 Anaconda<\/h3>\n<h4>\u5378\u8f7d Anaconda&#xff08;\u53ef\u9009&#xff09;<\/h4>\n<p>\u4e0b\u8f7deverything\u5c0f\u5de5\u5177<\/p>\n<p>Everything \u53ef\u4ee5\u6839\u636e\u6587\u4ef6\u540d&#xff0c;\u79d2\u641c\u8ba1 \u7b97\u673a\u4e2d\u4efb\u4f55\u4f4d\u7f6e\u7684\u4efb\u4f55\u6587\u4ef6&#xff0c;\u5982\u56fe\u6240\u793a&#xff0c;\u542f\u52a8\u540e\u8fdb\u5165\u72b6\u6001\u9700\u8981\u7b49\u5f85\u7ea6 20 \u79d2\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c3812fc29.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u5728 Everything \u4e2d\u641c\u7d22\u201cUninstall-Anaconda\u201d<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c3814b249.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u53ef\u76f4\u63a5\u53cc\u51fb\u56fe 1-2 \u4e2d\u7684\u5378\u8f7d\u7a0b\u5e8f&#xff0c;\u5bf9 Anaconda \u8fdb\u884c\u5378\u8f7d\u3002 \u5378\u8f7dAnaconda\u540e&#xff0c;\u7528Everything.exe\u67e5\u627e\u5e76\u5220\u9664\u6b8b\u5b58\u5728C\u76d8\u91cc\u5173\u4e8e.condarc\u3001 jupyter\u3001ipython\u3001continuum\u3001matplotlib\u3001anaconda \u4ee5\u53ca conda \u7684\u6587\u4ef6\u3002<\/p>\n<h4>\u5b89\u88c5 Anaconda<\/h4>\n<p>\u7531\u4e8e\u5b98\u65b9\u670d\u52a1\u5668\u5728\u56fd\u5916&#xff0c;\u6211\u4eec\u7528\u7684\u8bdd\u5f88\u6162&#xff0c;\u56e0\u6b64\u53bb\u4e2d\u56fd\u5927\u5b66\u7684\u955c\u50cf\u6e90\u4e0b\u8f7d\u3002 \u955c\u50cf\u6e90\u5730\u5740\u4e3a https:\/\/mirrors.bfsu.edu.cn\/anaconda\/archive\/&#xff0c;\u4e0b\u8f7d 2022.10-Win \u7248 \u672c&#xff0c;\u5982\u56fe 1-3 \u6240\u793a&#xff0c;\u5176\u57fa\u7840\u73af\u5883&#xff08;base \u73af\u5883&#xff09;\u4e0b\u7684 Python \u4e3a 3.9 \u7248\u672c\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c381626c0.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u8003\u8651\u5230\u540e\u9762\u4f1a\u7528\u865a\u62df\u73af\u5883&#xff0c;\u521b\u5efa\u865a\u62df\u73af\u5883\u65f6\u53ef\u4ee5\u8bbe\u7f6e\u6b64\u73af\u5883\u4e2d\u7684 Python \u89e3 \u91ca\u5668\u7248\u672c&#xff0c;\u6240\u4ee5\u8fd9\u91cc\u4e0b\u8f7d\u54ea\u4e00\u7248 Anaconda \u5e76\u4e0d\u91cd\u8981\u3002<\/p>\n<p>\u53cc\u51fb\u521a\u521a\u4e0b\u8f7d\u7684 exe \u6587\u4ef6&#xff0c;\u4f1a\u6709\u4e09\u4e2a\u5206\u5c94\u53e3&#xff0c;\u5206\u522b\u6309\u4e0b\u5217\u89c4\u5219\u9009\u62e9\u3002 \u2460 Just me \u548c All Users&#xff0c;\u9009\u62e9 Just me&#xff1b; \u2461 \u5b89\u88c5\u8def\u5f84\u9009\u62e9\u6700\u5927\u7684\u76d8&#xff08;\u4e00\u822c\u662f D \u76d8&#xff09;&#xff0c;\u653e\u5728\u65b0\u5efa\u7684\u3010D:\\\\Anaconda\u3011\u91cc&#xff1b;<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c3817f784.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u2462 \u6700\u540e\u4e00\u4e2a\u5206\u5c94\u53e3&#xff0c;\u4e0d\u52fe\u9009\u7b2c\u4e00\u4e2a\u65b9\u6846&#xff0c;\u6309\u7167\u56fe\u6240\u793a\u9009\u62e9\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c381a129b.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u5b89\u88c5\u8fc7\u7a0b\u5341\u5206\u6f2b\u957f&#xff0c;\u8fdb\u5ea6\u6761\u4f1a\u505c\u5728\u7ea6 90%\u7684\u4f4d\u7f6e\u5171 20 \u5206\u949f&#xff0c;\u8bf7\u8010\u5fc3\u7b49\u5f85\u3002<\/p>\n<p>\u914d\u7f6e\u73af\u5883\u53d8\u91cf&#xff1a;<\/p>\n<p>\u8fdb\u5165\u201c\u73af\u5883\u53d8\u91cf\u201d&#xff0c;\u70b9\u51fb\u201c\u7f16\u8f91\u7cfb\u7edf\u73af\u5883\u53d8\u91cf\u201d\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c381c425a.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u901a\u8fc7\u53f3\u4fa7\u7684\u201c\u65b0\u5efa\u201d\u6309\u94ae&#xff0c;\u53ef\u65b0\u5efa\u73af\u5883\u53d8\u91cf\u7684\u8def\u5f84&#xff0c;\u5c06\u3010D:\\\\Anaconda\u3011\u3001 \u3010D:\\\\Anaconda\\\\Scripts\u3011\u4e0e\u3010D:\\\\Anaconda\\\\Library\\\\bin\u3011\u6dfb\u52a0\u5230\u73af\u5883\u53d8\u91cf\u3002 \u82e5\u60a8\u7684 Anaconda \u5b89\u88c5\u8def\u5f84\u4e0d\u662f D:\\\\Anaconda&#xff0c;\u800c\u662f E:\\\\Anaconda&#xff0c;\u4ee5\u4e0a\u4e09\u4e2a \u73af\u5883\u53d8\u91cf\u9700\u8981\u5bf9\u5e94\u5730\u8fdb\u884c\u66f4\u6539&#xff0c;\u5373\u6539\u4e3a\u3010E:\\\\Anaconda\u3011\u3001\u3010E:\\\\Anaconda\\\\Scripts\u3011 \u4e0e\u3010E:\\\\Anaconda\\\\Library\\\\bin\u3011\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130505-6974c381f276a.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u8bf7\u6ce8\u610f&#xff0c;\u636e\u6089&#xff0c;\u82e5\u6b64\u524d\u60a8\u4e3a\u5176\u5b83\u5355\u72ec\u7684 Python \u89e3\u91ca\u5668\u6dfb\u52a0\u8fc7\u73af\u5883\u53d8\u91cf&#xff0c;\u8bf7 \u5728\u5220\u9664\u5b83\u7684\u73af\u5883\u53d8\u91cf&#xff0c;\u5426\u5219 Anaconda \u7684\u73af\u5883\u53d8\u91cf\u4f1a\u88ab\u6324\u51fa\u6765&#xff08;\u5373\u70b9\u51fb\u786e\u5b9a\u540e&#xff0c; \u518d\u70b9\u8fdb\u6765\u4f1a\u81ea\u52a8\u6d88\u5931&#xff09;\u3002<\/p>\n<p>\u684c\u9762\u5feb\u6377\u65b9\u5f0f&#xff1a; <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c3821c798.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u627e\u5230 Jupyter \u7684\u4f4d\u7f6e\u540e&#xff0c;\u628a Jupyter \u548c Prompt \u590d\u5236\u5230\u684c\u9762<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c3825031a.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h3>\u5b89\u88c5 PyTorch&#xff08;GPU \u7248&#xff09;\u5e93<\/h3>\n<p>\u5f88\u591a\u65f6\u5019\u6211\u4eec\u9700\u8981\u590d\u523b\u5176\u5b83\u6f14\u793a\u4ee3\u7801\u4e2d\u7684\u73af\u5883&#xff0c;\u56e0\u6b64&#xff0c;\u865a\u62df\u73af\u5883\u5fc5\u987b\u638c\u63e1\u3002 \u521d\u59cb\u7684\u865a\u62df\u73af\u5883\u57fa\u672c\u6ca1\u4ec0\u4e48\u5e93&#xff0c;\u6f14\u793a\u4ee3\u7801\u91cc\u8bf4\u9700\u8981\u5b89\u88c5\u4ec0\u4e48\u7248\u672c\u7684\u5e93&#xff0c;\u6211\u4eec\u5c31\u624b \u52a8\u5b89\u88c5\u4ec0\u4e48\u7248\u672c\u7684\u5e93\u3002\u865a\u62df\u73af\u5883\u8fd8\u6709\u4e00\u4e2a\u66f4\u5927\u7684\u4f18\u70b9&#xff0c;\u5373\u60f3\u521b\u5efa\u591a\u5c11\u4e2a&#xff0c;\u5c31\u521b\u5efa \u591a\u5c11\u3002\u8fd9\u6837\u4e00\u6765&#xff0c;\u5c31\u53ef\u4ee5\u5728\u540c\u4e00\u53f0\u8ba1\u7b97\u673a\u4e2d\u590d\u523b\u591a\u4e2a\u4e0d\u540c\u7684\u73af\u5883\u3002<\/p>\n<p>\u521b\u5efa\u865a\u62df\u73af\u5883 \u70b9\u51fb Prompt \u8fdb\u5165 Anaconda \u7684\u73af\u5883\u4e2d&#xff0c;\u63a5\u4e0b\u6765\u7684\u547d\u4ee4\u5747\u5728 Prompt \u4e2d\u6267\u884c\u3002<\/p>\n<p>&#xff08;<span class=\"token number\">1<\/span>&#xff09;\u6e05\u5c4f<br \/>\n<span class=\"token comment\"># \u6e05\u5c4f<\/span><br \/>\ncls<br \/>\n&#xff08;<span class=\"token number\">2<\/span>&#xff09;base \u73af\u5883\u4e0b\u7684\u64cd\u4f5c<br \/>\n<span class=\"token comment\"># \u5217\u51fa\u6240\u6709\u7684\u73af\u5883<\/span><br \/>\nconda env <span class=\"token builtin\">list<\/span><br \/>\n<span class=\"token comment\"># \u521b\u5efa\u540d\u4e3a\u201c\u73af\u5883\u540d\u201d\u7684\u865a\u62df\u73af\u5883&#xff0c;\u5e76\u6307\u5b9a Python \u7684\u7248\u672c<\/span><br \/>\nconda create <span class=\"token operator\">&#8211;<\/span>n \u73af\u5883\u540d python<span class=\"token operator\">&#061;<\/span><span class=\"token number\">3.9<\/span><br \/>\n<span class=\"token comment\"># \u521b\u5efa\u540d\u4e3a\u201c\u73af\u5883\u540d\u201d\u7684\u865a\u62df\u73af\u5883&#xff0c;\u5e76\u6307\u5b9a Python \u7684\u7248\u672c\u4e0e\u5b89\u88c5\u8def\u5f84<\/span><br \/>\nconda create <span class=\"token operator\">&#8211;<\/span><span class=\"token operator\">&#8211;<\/span>prefix<span class=\"token operator\">&#061;<\/span>\u5b89\u88c5\u8def\u5f84\\\\\u73af\u5883\u540d python<span class=\"token operator\">&#061;<\/span><span class=\"token number\">3.9<\/span><br \/>\n<span class=\"token comment\"># \u5220\u9664\u540d\u4e3a\u201c\u73af\u5883\u540d\u201d\u7684\u865a\u62df\u73af\u5883<\/span><br \/>\nconda remove <span class=\"token operator\">&#8211;<\/span>n \u73af\u5883\u540d <span class=\"token operator\">&#8211;<\/span><span class=\"token operator\">&#8211;<\/span><span class=\"token builtin\">all<\/span><br \/>\n<span class=\"token comment\"># \u8fdb\u5165\u540d\u4e3a\u201c\u73af\u5883\u540d\u201d\u7684\u865a\u62df\u73af\u5883<\/span><br \/>\nconda activate \u73af\u5883\u540d<br \/>\n&#xff08;<span class=\"token number\">3<\/span>&#xff09;\u865a\u62df\u73af\u5883\u5185\u7684\u64cd\u4f5c<br \/>\n<span class=\"token comment\"># \u5217\u51fa\u5f53\u524d\u73af\u5883\u4e0b\u7684\u6240\u6709\u5e93<\/span><br \/>\nconda <span class=\"token builtin\">list<\/span><br \/>\n<span class=\"token comment\"># \u5b89\u88c5 NumPy \u5e93&#xff0c;\u5e76\u6307\u5b9a\u7248\u672c 1.21.5<\/span><br \/>\npip install numpy<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">1.21<\/span><span class=\"token number\">.5<\/span> <span class=\"token operator\">&#8211;<\/span>i https<span class=\"token punctuation\">:<\/span><span class=\"token operator\">\/\/<\/span>pypi<span class=\"token punctuation\">.<\/span>tuna<span class=\"token punctuation\">.<\/span>tsinghua<span class=\"token punctuation\">.<\/span>edu<span class=\"token punctuation\">.<\/span>cn<span class=\"token operator\">\/<\/span>simple<br \/>\n<span class=\"token comment\"># \u5b89\u88c5 Pandas \u5e93&#xff0c;\u5e76\u6307\u5b9a\u7248\u672c 1.2.4<\/span><br \/>\npip install Pandas<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">1.2<\/span><span class=\"token number\">.4<\/span> <span class=\"token operator\">&#8211;<\/span>i https<span class=\"token punctuation\">:<\/span><span class=\"token operator\">\/\/<\/span>pypi<span class=\"token punctuation\">.<\/span>tuna<span class=\"token punctuation\">.<\/span>tsinghua<span class=\"token punctuation\">.<\/span>edu<span class=\"token punctuation\">.<\/span>cn<span class=\"token operator\">\/<\/span>simple<br \/>\n<span class=\"token comment\"># \u5b89\u88c5 Matplotlib \u5e93&#xff0c;\u5e76\u6307\u5b9a\u7248\u672c 3.5.1<\/span><br \/>\npip install Matplotlib<span class=\"token operator\">&#061;&#061;<\/span><span class=\"token number\">3.5<\/span><span class=\"token number\">.1<\/span> <span class=\"token operator\">&#8211;<\/span>i https<span class=\"token punctuation\">:<\/span><span class=\"token operator\">\/\/<\/span>pypi<span class=\"token punctuation\">.<\/span>tuna<span class=\"token punctuation\">.<\/span>tsinghua<span class=\"token punctuation\">.<\/span>edu<span class=\"token punctuation\">.<\/span>cn<span class=\"token operator\">\/<\/span>simple<br \/>\n<span class=\"token comment\"># \u67e5\u770b\u5f53\u524d\u73af\u5883\u4e0b\u67d0\u4e2a\u5e93\u7684\u7248\u672c&#xff08;\u4ee5 numpy \u4e3a\u4f8b&#xff09;<\/span><br \/>\npip show numpy<br \/>\n<span class=\"token comment\"># \u9000\u51fa\u865a\u62df\u73af\u5883<\/span><br \/>\nconda deactivate<\/p>\n<h4>\u5b89\u88c5 CUDA&#xff08;\u53ef\u9009&#xff09;<\/h4>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c38266e42.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u67e5\u770b\u81ea\u5df1\u7684\u8ba1\u7b97\u673a\u7684\u663e\u5361\u7684\u65b9\u6cd5\u662f&#xff1a;\u4efb \u52a1\u7ba1\u7406\u5668\u2014\u2014\u6027\u80fd\u2014\u2014\u5de6\u4fa7\u680f\u5212\u5230\u6700\u4e0b\u9762\u3002<\/p>\n<p>NVIDIA \u663e\u5361\u4e2d\u7684\u8fd0\u7b97\u5e73\u53f0\u662f CUDA&#xff0c;\u4e0d\u8fc7&#xff0c;\u5373\u4f7f\u60a8\u7684\u8ba1\u7b97\u673a\u6709 NVIDIA \u663e \u5361&#xff0c;\u4f46\u60a8\u7684\u663e\u5361\u4e2d\u4e5f\u4e0d\u4e00\u5b9a\u542b\u6709 CUDA&#xff0c;\u6ca1\u6709\u7684\u8bdd\u5c31\u8981\u4e0b\u8f7d CUDA\u3002 \u800c PyTorch \u7684\u4e0b\u8f7d\u7ec4\u4ef6\u91cc\u4e5f\u4f1a\u5305\u542b\u4e00\u4e2a\u5185\u7f6e\u7684 cuda\u3002 \u4e3a\u4e86\u533a\u5206&#xff0c;\u663e\u5361\u5185\u7684 CUDA \u7528\u5927\u5199&#xff0c;PyTorch \u5185\u7f6e\u7684 cuda \u7528\u5c0f\u5199\u3002 \u4e00\u822c\u6765\u8bb2&#xff0c;\u8981\u6ee1\u8db3&#xff1a;CUDA \u7248\u672c\u2265cuda \u7248\u672c\u3002 \u67e5\u770b CUDA \u7248\u672c\u7684\u65b9\u6cd5\u662f&#xff1a;Win&#043;R \u540e\u8f93\u5165 cmd&#xff0c;\u8fdb\u5165\u547d\u4ee4\u63d0\u793a\u7b26&#xff0c;\u6211\u4eec\u9700 \u8981\u8f93\u5165 nvcc -V\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c3827cf41.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u5982\u679c\u663e\u793a\u201cnvcc -V \u4e0d\u662f\u5185\u90e8\u6216\u5916\u90e8\u547d\u4ee4\u201d&#xff0c;\u5219\u8bf4\u660e\u9700\u8981\u5b89\u88c5 CUDA\u3002 \u540e\u9762\u6211\u4eec\u5c06\u5b89\u88c5 torch 1.12.0 \u7248\u672c&#xff0c;\u5176\u53ef\u9009\u7684\u5185\u7f6e cuda \u7248\u672c\u662f 11.3\u3002\u56e0\u6b64&#xff0c; \u5982\u679c\u60a8\u663e\u5361\u91cc\u7684 CUDA \u4f4e\u4e8e\u4e86 11.3&#xff0c;\u9700\u8981\u8fdb\u884c\u5347\u7ea7\u3002<\/p>\n<p>CUDA \u7684\u4e0b\u8f7d\u94fe\u63a5&#xff1a;https:\/\/developer.nvidia.com\/cuda-toolkit-archive&#xff0c;\u4ee5\u5176\u4e2d \u7684 CUDA 11.3 \u4e3a\u4f8b&#xff0c;\u70b9\u51fb\u8fdb\u5165 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c382938f7.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u63a5\u4e0b\u6765\u8981\u9009\u62e9\u5e73\u53f0&#xff0c;\u70b9\u51fb Windows&#xff0c;\u4e4b\u540e\u81ea\u52a8\u5f39\u51fa\u66f4\u591a\u5185\u5bb9&#xff0c;\u6309\u56fe 5-4 \u9009\u62e9&#xff0c; \u6700\u540e\u70b9\u51fb\u53f3\u4e0b\u89d2\u7684 Download&#xff08;2.7GB&#xff09;&#xff0c;\u5efa\u8bae\u5c06\u5176\u653e\u7f6e\u65b0\u5efa\u7684 D:\\\\CUDA \u4e2d\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c382aebe2.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u4e0b\u8f7d\u597d\u4e4b\u540e&#xff0c;\u5c06 exe \u6587\u4ef6\u653e\u7f6e\u5728\u65b0\u5efa\u7684 D:\\\\CUDA \u5185&#xff0c;\u70b9\u51fb exe \u6587\u4ef6&#xff0c;\u5927\u7ea6 \u8981\u7b49\u4e24\u5206\u949f&#xff0c;\u4f1a\u5f39\u51fa\u5982\u56fe 5-5 \u7684\u63d0\u793a\u6846&#xff0c;\u8fd9\u91cc\u8981\u9009\u62e9\u4e34\u65f6\u7684\u89e3\u538b\u6587\u4ef6\u5939&#xff0c;\u8003\u8651\u5230 \u89e3\u538b\u540e\u9700\u8981\u5360\u7528\u5927\u7ea6 7G \u7684\u5185\u5b58&#xff0c;\u56e0\u6b64\u5efa\u8bae\u653e\u5728 D:\\\\CUDA\\\\Tem \u5185&#xff0c;\u5b89\u88c5\u7ed3\u675f\u540e&#xff0c; \u8be5\u4e34\u65f6\u89e3\u538b\u6587\u4ef6\u5939\u4f1a\u81ea\u52a8\u5220\u9664\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c382d8552.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u89e3\u538b\u597d\u540e&#xff0c;\u8fdb\u5165\u5982\u56fe 5-6 \u7684\u5b89\u88c5\u754c\u9762&#xff0c;\u540c\u610f\u5e76\u7ee7\u7eed\u540e&#xff0c;\u70b9\u51fb\u201c\u81ea\u5b9a\u4e49\u201d\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130506-6974c382eed56.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u63a5\u4e0b\u6765&#xff0c;\u4ec5\u4ec5\u9009\u62e9 4 \u5927\u9879\u4e2d\u7684 CUDA&#xff0c;\u5e76\u53d6\u6d88 CUDA \u4e2d\u5173\u4e8e VS \u7684\u9009\u9879\u3002 <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130507-6974c3834ac97.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u5b8c\u6210\u540e&#xff0c;\u6309\u7167\u9ed8\u8ba4\u7684 C \u76d8\u8def\u5f84\u8fdb\u884c\u5b89\u88c5&#xff08;\u5927\u7ea6 7G&#xff09;\u5373\u53ef <img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130507-6974c38398c1e.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u73b0\u5728\u56de\u5934\u67e5\u770b\u4e34\u65f6\u89e3\u538b\u6587\u4ef6\u5939 D:\\\\CUDA\\\\Tem&#xff0c;\u4f1a\u53d1\u73b0\u5df2\u7ecf\u6d88\u5931&#xff0c;\u987a\u4fbf\u53ef\u4ee5 \u5220\u9664 D:\\\\CUDA \u4e86\u3002 \u63a5\u4e0b\u6765\u914d\u7f6e\u73af\u5883\u53d8\u91cf&#xff0c;\u5982\u679c\u4f60\u662f\u6309\u7167\u9ed8\u8ba4\u8def\u5f84 \u7684\u8bdd&#xff0c;\u5176\u8def\u5f84\u5e94\u8be5\u662f&#xff1a; \u26ab C:\\\\Program Files\\\\NVIDIA GPU Computing Toolkit\\\\CUDA \u26ab C:\\\\Program Files\\\\NVIDIA GPU Computing Toolkit\\\\CUDA\\\\v11.3\\\\lib\\\\x64 \u26ab C:\\\\Program Files\\\\NVIDIA GPU Computing Toolkit\\\\CUDA\\\\v11.3\\\\bin \u26ab C:\\\\Program Files\\\\NVIDIA GPU Computing Toolkit\\\\CUDA\\\\v11.3\\\\libnvvp \u5982\u679c\u4f60\u5fd8\u4e86\u4f60\u7684\u8def\u5f84&#xff0c;\u7528 everything \u641c\u7d22\u51fa\u6765\u5373\u53ef\u3002 \u6700\u540e&#xff0c;\u56de\u5934\u68c0\u67e5\u4e00\u4e0b CUDA \u7248\u672c&#xff0c;Win&#043;R \u540e\u8f93\u5165 cmd&#xff0c;\u8fdb\u5165\u547d\u4ee4\u63d0\u793a\u7b26&#xff0c; \u8f93\u5165 nvcc -V<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130507-6974c383b5047.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h4>\u5b89\u88c5 PyTorch<\/h4>\n<p>PyTorch \u4e00\u5206\u4e3a\u4e09&#xff1a;torch\u3001torchvision \u4e0e torchaudio\u3002\u8fd9\u4e09\u4e2a\u5e93\u4e2d&#xff0c;torch \u6709 2G \u5de6\u53f3&#xff0c;\u800c torchvision \u548c torchaudio \u53ea\u6709 2M \u5de6\u53f3&#xff0c;\u56e0\u6b64\u4e00\u822c\u5728\u4ee3\u7801\u91cc\u53ea\u4f1a import torch\u3002\u5f53 torch \u7684\u7248\u672c\u7ed9\u5b9a\u540e&#xff0c;\u53e6\u5916\u4e24\u4e2a\u9644\u4ef6\u7684\u7248\u672c\u4e5f\u552f\u4e00\u786e\u5b9a\u4e86\u3002 \u5b89\u88c5 torch \u524d&#xff0c;\u5148\u7ed9\u51fa\u4e00\u5f20\u5b89\u88c5\u8868&#xff0c;\u5176\u4e2d cu113 \u5373 cuda 11.3&#xff0c;cp39 \u5373 Python \u89e3\u91ca\u5668\u7684\u7248\u672c\u662f Python3.9\u3002\u6ce8&#xff1a;NVIDIA \u663e\u5361 30 \u7cfb\u5217&#xff08;\u5982 NVIDIA GeForce RTX 3050&#xff09;\u53ea\u80fd\u5b89\u88c5 cu110 \u53ca\u5176\u4ee5\u540e\u7684\u7248\u672c\u3002<\/p>\n<p>\u76ee\u524d\u6240\u6709 torch \u7248\u672c\u7684\u5b89\u88c5\u8868<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130504-6974c380dcc18.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u73b0\u5728&#xff0c;\u6309\u7167\u674e\u6c90\u8001\u5e08\u300a\u52a8\u624b\u5b66\u6df1\u5ea6\u5b66\u4e60&#xff08;PyTorch \u7248&#xff09;\u300b\u6559\u7a0b&#xff0c;\u5b89\u88c5 torch 1.12.0\u3002 \u6839\u636e\u8868 5-1&#xff0c;torch 1.12.0 \u652f\u6301\u7684 cuda \u662f 11.3 \u6216 11.6&#xff0c;\u4efb\u610f\u9009\u4e00\u4e2a\u5373\u53ef&#xff1b;\u5176 \u652f\u6301\u7684 Python \u662f 3.7 &#8211; 3.10&#xff0c;\u521a\u521a\u65b0\u5efa\u7684\u865a\u62df\u73af\u5883\u7684 Python \u662f 3.9&#xff0c;\u6ee1\u8db3\u6761\u4ef6\u3002 \u8fdb\u5165 PyTorch \u5b98\u7f51&#xff1a;https:\/\/pytorch.org\/get-started\/previous-versions\/&#xff0c;\u5728\u5176\u4e2d Ctrl &#043; F \u641c\u7d22\u3010 pip install torch&#061;&#061;1.12.0 \u3011&#xff0c;\u8bf7\u6ce8\u610f&#xff0c;\u8fd9\u91cc\u4f7f\u7528 pip \u5b89 \u88c5&#xff0c;\u800c\u4e0d\u662f conda \u5b89\u88c5&#xff08;\u5982\u679c\u7528 conda \u5b89\u88c5&#xff0c;\u6700\u540e\u68c0\u9a8c cuda \u65f6\u662f\u4e0d\u53ef\u7528\u7684&#xff09;\u3002<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/01\/20260124130507-6974c383cb781.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> &#xff08;1&#xff09;\u65b9\u6cd5\u4e00&#xff1a;\u76f4\u63a5\u5b89\u88c5&#xff08;\u4e0d\u5efa\u8bae&#xff0c;\u7f51\u5dee\u7684\u8bdd\u4f1a\u6b7b\u673a&#xff09; \u590d\u5236\u7f51\u9875\u91cc\u7684\u90a3\u6bb5\u4ee3\u7801&#xff0c;\u4e5f\u5373 pip install torch1.12.0&#043;cu113 torchvision0.13.0&#043;cu113 torchaudio0.12.0 &#8211;extra-index-url https:\/\/download.pytorch.org\/whl\/cu113 \u53cc\u51fb Prompt&#xff0c;\u8fdb\u5165 DL \u73af\u5883\u4e0b\u8fd0\u884c&#xff08;\u4e0d\u8981\u5728 base \u73af\u5883\u4e0b\u8fd0\u884c&#xff09; <img decoding=\"async\" src=\"2026-01-24tflhnlivcs5.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u770b\u5230\u6700\u540e\u51e0\u884c\u4ee3\u7801\u91cc\u6709 Successfully installed \u5c31\u7b97\u6210\u529f\u3002 \u5b89\u88c5\u547d\u4ee4\u7684\u610f\u601d\u662f&#xff0c;\u4f7f\u7528 pip \u5b89\u88c5\u4e09\u4e2a\u5e93&#xff0c;\u7b2c\u4e00\u5e93\u662f torch1.12.0&#043;cu113&#xff0c; \u7b2c\u4e8c\u4e2a\u5e93\u662f torchvision0.13.0&#043;cu113&#xff0c;\u7b2c\u4e09\u4e2a\u5e93\u662f torchaudio0.12.0&#xff0c;\u5e93\u7684\u4e0b \u8f7d\u5730\u5740\u662f https:\/\/download.pytorch.org\/whl\/cu113\u3002<\/p>\n<p>&#xff08;2&#xff09;\u65b9\u6cd5\u4e8c&#xff1a;\u5148\u4e0b\u8f6e\u5b50\u518d\u5b89\u88c5 \u9996\u5148&#xff0c;\u6211\u4eec\u8fdb\u5165\u65b9\u6cd5\u4e00\u63d0\u53ca\u7684\u7f51\u7ad9 https:\/\/download.pytorch.org\/whl\/cu113&#xff0c;\u8fdb\u5165 torch\u3001torchvision\u3001torchaudio \u4e09\u5927\u7ec4\u4ef6\u5404\u81ea\u7684\u7f51\u7ad9\u3002<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24vlr0iwxxsck.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> <img decoding=\"async\" src=\"2026-01-245z55zw4h1oj.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u4e0b\u8f7d\u597d\u540e&#xff0c;\u5c06\u4e09\u4e2a whl \u6587\u4ef6\u653e\u5728\u65b0\u5efa\u7684 D:\\\\whl \u6587\u4ef6\u5939\u4e2d\u3002 \u5b89\u88c5\u547d\u4ee4\u4e3a pip install \u8def\u5f84\\\\\u8f6e\u5b50\u540d.whl&#xff0c;\u5373<\/p>\n<p>pip install D:\\\\whl\\\\torch-1.12.0&#043;cu113-cp39-cp39-win_amd64.whl pip install D:\\\\whl\\\\torchvision-0.13.0&#043;cu113-cp39-cp39-win_amd64.whl pip install D:\\\\whl\\\\torchaudio-0.12.0&#043;cu113-cp39-cp39-win_amd64.whl<\/p>\n<p>\u5c06\u4e0a\u8ff0\u4ee3\u7801\u653e\u5728\u865a\u62df\u73af\u5883 DL \u4e0b\u6267\u884c&#xff08;\u800c\u4e0d\u662f base \u73af\u5883&#xff0c;\u5426\u5219\u5c31\u4f1a\u628a\u8fd9\u4e2a\u5e93 \u5b89\u88c5\u8fdb base \u73af\u5883\u4e0b&#xff09;\u3002 \u5b89\u88c5\u5b8c\u6bd5\u540e&#xff0c;\u5373\u53ef\u5220\u9664 D:\\\\whl \u6587\u4ef6\u5939&#xff08;\u4f46\u5efa\u8bae\u7559\u7740&#xff0c;\u4e4b\u540e\u53ef\u80fd\u8fd8\u8981\u5b89\u88c5&#xff09;\u3002<\/p>\n<h4>\u68c0\u9a8c cuda \u662f\u5426\u53ef\u7528<\/h4>\n<p>&#xff08;1&#xff09;\u65b9\u6cd5\u4e00&#xff1a;\u67e5\u770b\u5f53\u524d\u73af\u5883\u7684\u6240\u6709\u5e93 \u8fdb\u5165 DL \u73af\u5883\u540e&#xff0c;\u4f7f\u7528 conda list \u547d\u4ee4\u5217\u51fa\u5f53\u524d\u7684\u6240\u6709\u5e93 <img decoding=\"async\" src=\"2026-01-243vsj5qfanob.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>&#xff08;2&#xff09;\u65b9\u6cd5\u4e8c&#xff1a;\u8fdb\u5165 Python \u89e3\u91ca\u5668\u68c0\u9a8c \u7531\u4e8e\u76ee\u524d\u6ca1\u6709\u4ee3\u7801\u7f16\u8f91\u5668&#xff0c;\u56e0\u6b64\u76f4\u63a5\u8fdb Python \u89e3\u91ca\u5668&#xff0c;\u68c0\u9a8c cuda \u662f\u5426\u53ef\u7528\u3002 \u9996\u5148&#xff0c;\u8fdb\u5165\u865a\u62df\u73af\u5883 DL \u540e&#xff0c;\u8f93\u5165 python \u4ee5\u8fdb\u5165\u89e3\u91ca\u5668 <img decoding=\"async\" src=\"2026-01-24viunojnbl0f.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u8f93\u5165 import torch \u5bfc\u5165 torch \u5e93&#xff0c;\u5982\u56fe\u6240\u793a\u3002\u82e5 torch \u5b89\u88c5\u5931\u8d25&#xff0c;\u5219\u4f1a \u8fd4\u56de No module named \u2018torch\u2019\u3002\u82e5\u5b89\u88c5\u6210\u529f&#xff0c;\u4e0d\u4f1a\u8fd4\u56de\u4efb\u4f55\u8bed\u53e5&#xff0c;\u540c\u65f6\u5728\u4e0b\u4e00\u884c \u51fa\u73b0\u201c&gt;&gt;&gt;\u201d&#xff0c;\u63d0\u793a\u6211\u4eec\u53ef\u4ee5\u7ee7\u7eed\u6572\u4ee3\u7801\u3002<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24iagtxz1mdo5.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u6700\u540e\u4e00\u6b65&#xff0c;\u8f93\u5165 torch.cuda.is_available() <img decoding=\"async\" src=\"2026-01-24or5fhs1jweo.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h3>Jupyter \u4ee3\u7801\u7f16\u8f91\u5668<\/h3>\n<p>\u8ba1\u7b97\u673a\u7528\u6237\u540d&#xff08;\u5373 C:\\\\Users\\\\\u7528\u6237\u540d&#xff09;\u4e3a\u4e2d\u6587&#xff0c;\u65e0\u6cd5\u517c\u5bb9 Jupyter\u3002\u5927\u5bb6\u53ef\u4ee5\u6253 \u5f00 Prompt \u68c0\u67e5\u81ea\u5df1\u7684\u7528\u6237\u540d <img decoding=\"async\" src=\"2026-01-24ne5dut4lgva.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h4>\u4fee\u6539\u5de5\u4f5c\u8def\u5f84&#xff08;\u53ef\u9009&#xff09;<\/h4>\n<p>Jupyter \u521d\u59cb\u7684\u5de5\u4f5c\u8def\u5f84\u4e3a\u3010C:\\\\Users\\\\\u7528\u6237\u540d\u3011&#xff0c;\u9700\u8981\u8fdb\u884c\u4fee\u6b63&#xff0c;\u5c06\u5176\u8f6c\u79fb\u5230 \u65b0\u5efa\u7684\u3010D:\\\\Jupyter\u3011\u4f4d\u7f6e\u3002 \u2460 \u65b0\u5efa D:\\\\Jupyter&#xff1b; \u2461 \u6253\u5f00\u684c\u9762\u5feb\u6377\u65b9\u5f0f\u4e2d\u7684 Prompt&#xff1b; \u2462 \u8f93\u5165 jupyter notebook &#8211;generate-config \u547d\u4ee4\u5e76\u6267\u884c&#xff1b; \u2463 \u6253\u5f00\u4e0a\u4e00\u6b65\u751f\u6210\u7684\u914d\u7f6e\u6587\u4ef6\u5730\u5740&#xff0c;\u5373<\/p>\n<p>C<span class=\"token punctuation\">:<\/span>\\\\Users\\\\\u7528\u6237\u540d\\\\<span class=\"token punctuation\">.<\/span>jupyter<\/p>\n<p>\u2464 \u5728 jupyter_notebook_config.py&#xff08;\u4ee5\u8bb0\u4e8b\u672c\u65b9\u5f0f\u6253\u5f00&#xff09;\u4e2d\u4f7f\u7528 Ctrl &#043; F \u67e5\u627e \u5e76\u4e14\u4fee\u6539\u5982\u4e0b\u914d\u7f6e\u9879&#xff1a;<\/p>\n<p>\u4fee\u6539\u524d&#xff1a;<span class=\"token comment\"># c.NotebookApp.notebook_dir &#061; &#039;&#039;<\/span><br \/>\n\u4fee\u6539\u540e&#xff1a;c<span class=\"token punctuation\">.<\/span>NotebookApp<span class=\"token punctuation\">.<\/span>notebook_dir <span class=\"token operator\">&#061;<\/span> <span class=\"token string\">&#039;D:\\\\Jupyter&#039;<\/span><\/p>\n<p>\u4e5f\u5373\u5220\u9664\u524d\u9762\u7684#\u53f7\u6ce8\u91ca&#xff0c;\u5728\u540e\u9762\u7684\u5355\u5f15\u53f7\u91cc\u8f93\u5165\u8981\u8bbe\u7f6e\u7684\u76ee\u5f55\u8def\u5f84&#xff0c;\u6ce8\u610f&#xff0c; \u2018D:\\\\Jupyter\u2019 \u4e2d\u4e0d\u80fd\u6709\u7a7a\u683c&#xff0c;\u5426\u5219 Jupyter \u6253\u5f00\u5c31\u95ea\u9000\u3002\u4fdd\u5b58\u540e\u5173\u95ed\u3002 \u2465 \u627e\u5230\u684c\u9762\u7684 jupyter notebook \u5feb\u6377\u56fe\u6807&#xff0c;\u9f20\u6807\u53cd\u952e&gt;&gt;\u5c5e\u6027&gt;&gt;\u5feb\u6377\u65b9\u5f0f&gt;&gt; \u76ee\u6807&#xff0c;\u5220\u9664\u6700\u540e\u7684&#034;%USERPROFILE%\/&#034;<\/p>\n<h4>\u865a\u62df\u73af\u5883\u8fde\u63a5 Jupyter<\/h4>\n<p>\u6211\u4eec\u5df2\u7ecf\u5728 Anaconda \u91cc\u521b\u5efa\u4e86\u4e00\u4e2a\u53eb DL \u7684\u865a\u62df\u73af\u5883&#xff0c;\u4f46\u662f\u73b0\u5728\u8fd9\u4e2a\u53eb DL \u7684\u865a\u62df\u73af\u5883\u6ca1\u6709\u8fde\u63a5 Jupyter&#xff0c;\u6362\u53e5\u8bdd\u8bf4&#xff0c;Jupyter \u73b0\u5728\u4ec5\u4ec5\u80fd\u4e0e base \u73af\u5883\u76f8\u8fde\u3002 \u4e3a\u8ba9\u865a\u62df\u73af\u5883\u4e0e Jupyter \u76f8\u8fde&#xff0c;\u8bf7\u5728 Prompt \u7684\u865a\u62df\u73af\u5883\u4e0b\u64cd\u4f5c\u4e0b\u5217\u547d\u4ee4\u3002<\/p>\n<p><span class=\"token comment\"># \u5b89\u88c5 ipykernel<\/span><br \/>\npip install ipykernel <span class=\"token operator\">&#8211;<\/span>i https<span class=\"token punctuation\">:<\/span><span class=\"token operator\">\/\/<\/span>pypi<span class=\"token punctuation\">.<\/span>tuna<span class=\"token punctuation\">.<\/span>tsinghua<span class=\"token punctuation\">.<\/span>edu<span class=\"token punctuation\">.<\/span>cn<span class=\"token operator\">\/<\/span>simple<br \/>\n<span class=\"token comment\"># \u5c06\u865a\u62df\u73af\u5883\u5bfc\u5165 Jupyter \u7684 kernel \u4e2d<\/span><br \/>\npython <span class=\"token operator\">&#8211;<\/span>m ipykernel install <span class=\"token operator\">&#8211;<\/span><span class=\"token operator\">&#8211;<\/span>user <span class=\"token operator\">&#8211;<\/span><span class=\"token operator\">&#8211;<\/span>name<span class=\"token operator\">&#061;<\/span>\u73af\u5883\u540d<br \/>\n<span class=\"token comment\"># \u5220\u9664\u865a\u62df\u73af\u5883\u7684 kernel \u5185\u6838<\/span><br \/>\njupyter kernelspec remove \u73af\u5883\u540d<\/p>\n<p>\u5728 Jupyter \u91cc&#xff0c;\u5207\u6362\u5230 DL \u5185\u6838\u540e&#xff0c;\u70b9\u51fb New&#xff0c;\u65b0\u5efa\u4e00\u4e2a DL \u5185\u6838\u7684\u811a\u672c<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24wr4twz3f3io.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u5728 DL \u5185\u6838\u7684\u811a\u672c\u4e0b&#xff0c;\u8f93\u5165\u4e24\u6bb5\u4ee3\u7801\u540e\u8fd0\u884c <img decoding=\"async\" src=\"2026-01-24xmb3rgwvjmx.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h3>PyCharm \u4ee3\u7801\u7f16\u8f91\u5668<\/h3>\n<p>\u672c\u89c6\u9891\u4e0b\u8f7d PyCharm 2020.1.3-win \u7684\u793e\u533a\u7248<\/p>\n<h4>\u5378\u8f7d PyCharm&#xff08;\u53ef\u9009&#xff09;<\/h4>\n<p>\u627e\u5230 PyCharm \u5b89\u88c5\u5730\u5740&#xff0c;\u5982\u679c\u627e\u4e0d\u5230&#xff0c;\u5219 \u5728 PyCharm \u5feb\u6377\u65b9\u5f0f\u7684\u5c5e\u6027\u4e2d\u627e<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24pr4frtq2ns2.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<p>\u5728\u201cPyCharm \u5b89\u88c5\u5730\u5740\\\\PyCharm Community Edition 2020.1.3\\\\bin\u201d\u4e2d&#xff0c;\u627e\u5230 Uninstall.exe<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24m0o4vrn1p01.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u53cc\u51fb\u8fd0\u884c&#xff0c;\u52fe\u9009\u4e24\u4e2a&#xff0c;\u70b9\u51fb\u786e\u5b9a <img decoding=\"async\" src=\"2026-01-2403uya0yerkf.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h4>\u5b89\u88c5 PyCharm<\/h4>\n<p>\u9996\u5148&#xff0c;\u53bb jetbrains \u516c\u53f8\u7684\u5b98\u7f51\u4e0b\u8f7d PyCharm&#xff0c;\u5730\u5740\u4e3a https:\/\/www.jetbrains.com\/pycharm\/download\/other.html \u63a8\u8350\u4e0b\u8f7d\u793e\u533a\u7248&#xff08;\u8db3\u591f\u4e2a\u4eba\u4f7f\u7528&#xff09;\u7684 2020.1.3-win \u7248\u672c <img decoding=\"async\" src=\"2026-01-24oybofhrln4b.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u5b89\u88c5\u65f6&#xff0c;\u8bf7\u653e\u5728 D \u76d8\u7684\u65b0\u5efa\u6587\u4ef6\u5939&#xff1a;D:\\\\PyCharm \u91cc\u3002\u9009\u597d\u5b89\u88c5\u5730\u5740\u540e&#xff0c;\u8bf7 \u52fe\u9009\u5982\u56fe\u6240\u793a\u3002 <img decoding=\"async\" src=\"2026-01-24lxtr211lvhz.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n<h4>\u865a\u62df\u73af\u5883\u8fde\u63a5 PyCharm<\/h4>\n<p>\u5b8c\u6210\u7b2c\u4e00\u6b21\u914d\u7f6e\u540e&#xff0c;\u9996\u5148\u5728 D:\\\\PyCharm \u4e2d\u521b\u5efa\u6587\u4ef6\u5939 Py_Projects \u5b58\u653e\u5de5\u7a0b\u3002\u63a5\u7740&#xff0c;\u5728 PyCharm \u91cc\u521b\u5efa\u65b0\u5de5\u7a0b<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24aekelogzuwy.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u7b2c\u4e00\u6b65&#xff0c;\u5207\u6362\u65b0\u5de5\u7a0b\u7684\u4f4d\u7f6e\u4e3a\u521a\u521a\u521b\u5efa\u7684\u6587\u4ef6\u5939&#xff1b;\u7b2c\u4e8c\u6b65&#xff0c;\u70b9\u51fb\u201cExisting interpreter\u201d&#xff1b;\u7b2c\u4e09\u6b65&#xff0c;\u7531\u4e8e\u662f\u7b2c\u4e00\u6b21\u8fdb\u5165 PyCharm&#xff0c;\u53ea\u80fd\u70b9\u51fb\u201c\u2026\u201d\u6765\u627e\u89e3\u91ca\u5668\u3002<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24jp0lutgm4wp.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u5728\u5f39\u51fa\u7684\u754c\u9762\u4e2d&#xff0c;\u9996\u5148\u70b9\u51fb\u5de6\u4fa7\u7684 conda \u73af\u5883&#xff0c;\u518d\u5c06\u89e3\u91ca\u5668\u8bbe\u7f6e\u4e3a Anaconda \u865a\u62df\u73af\u5883\u89e3\u91ca\u5668\u7684\u5730\u5740<\/p>\n<p><img decoding=\"async\" src=\"2026-01-24crdl0rexb2q.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u73b0\u5728&#xff0c;\u5728\u6b64\u5de5\u7a0b\u91cc\u521b\u5efa\u4e00\u4e2a\u540d\u4e3a\u201ctest\u201d\u7684.py \u6587\u4ef6 <img decoding=\"async\" src=\"2026-01-24t2hutsnlf0v.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u5148\u968f\u4fbf\u5199\u884c\u4ee3\u7801&#xff0c;\u8fd0\u884c\u4e00\u4e0b&#xff08;Ctrl&#043;Shift&#043;F10&#xff09;&#xff0c;\u518d\u70b9\u51fb\u7f16\u8f91\u914d\u7f6e <img decoding=\"async\" src=\"2026-01-24jwsodpgdtta.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u52fe\u9009\u201c\u4f7f\u7528 Python \u63a7\u5236\u53f0\u8fd0\u884c\u201d&#xff0c;\u5e76\u5e94\u7528 <img decoding=\"async\" src=\"2026-01-24chepa1zjwbi.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u6253\u5f00\u63a7\u5236\u53f0&#xff0c;\u518d\u8fd0\u884c.py \u6587\u4ef6&#xff0c;\u63a7\u5236\u53f0\u53f3\u4fa7\u5373\u53ef\u663e\u793a\u6bcf\u4e2a\u53d8\u91cf\u7684\u6570\u503c\u3002 <img decoding=\"async\" src=\"2026-01-24rhgaaewqyp5.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/> \u6700\u540e&#xff0c;\u68c0\u6d4b PyCharm \u6709\u65e0\u8fde\u63a5 GPU \u7248\u672c\u7684 PyTorch <img decoding=\"async\" src=\"2026-01-24bzvprbloje5.png\" alt=\"\u5728\u8fd9\u91cc\u63d2\u5165\u56fe\u7247\u63cf\u8ff0\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6587\u7ae0\u76ee\u5f55\u5907\u6ce8\u5b89\u88c5 Anaconda\u5378\u8f7d Anaconda&#xff08;\u53ef\u9009&#xff09;\u5b89\u88c5 Anaconda\u5b89\u88c5 PyTorch&#xff08;GPU \u7248&#xff09;\u5e93\u5b89\u88c5 CUDA&#xff08;\u53ef\u9009&#xff09;\u5b89\u88c5 PyTorch\u68c0\u9a8c cuda \u662f\u5426\u53ef\u7528Jupyter \u4ee3\u7801\u7f16\u8f91\u5668\u4fee\u6539\u5de5\u4f5c\u8def\u5f84&#xff08;\u53ef\u9009&#xff09;\u865a\u62df\u73af\u5883\u8fde\u63a5 JupyterPyCharm \u4ee3\u7801\u7f16\u8f91\u5668\u5378\u8f7d PyCharm&#xff08;\u53ef\u9009&#xff09;\u5b89\u88c5 PyCharm\u865a\u62df<\/p>\n","protected":false},"author":2,"featured_media":65324,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[81,152,86],"topic":[],"class_list":["post-65344","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-python","tag-pytorch","tag-86"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python \u6df1\u5ea6\u5b66\u4e60\uff1a\u5b89\u88c5 Anaconda\u3001PyTorch\uff08GPU \u7248\uff09\u5e93\u4e0e PyCharm - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/65344.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" 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