{"id":482,"date":"2025-04-03T18:00:10","date_gmt":"2025-04-03T10:00:10","guid":{"rendered":"https:\/\/www.wunen.com\/index.php\/2025\/04\/03\/pytorch-%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e5%85%a5%e9%97%a8\/"},"modified":"2025-04-03T18:00:10","modified_gmt":"2025-04-03T10:00:10","slug":"pytorch-%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e5%85%a5%e9%97%a8","status":"publish","type":"post","link":"http:\/\/www.wunen.com\/index.php\/2025\/04\/03\/pytorch-%e6%b7%b1%e5%ba%a6%e5%ad%a6%e4%b9%a0%e5%85%a5%e9%97%a8\/","title":{"rendered":"PyTorch \u6df1\u5ea6\u5b66\u4e60\u5165\u95e8"},"content":{"rendered":"<div class=\"article_content clearfix\" id=\"article_content\">\n <link href=\"https:\/\/csdnimg.cn\/release\/blogv2\/dist\/mdeditor\/css\/editerView\/kdoc_html_views-1a98987dfd.css\" rel=\"stylesheet\"\/>\n <link href=\"https:\/\/csdnimg.cn\/release\/blogv2\/dist\/mdeditor\/css\/editerView\/ck_htmledit_views-704d5b9767.css\" rel=\"stylesheet\"\/>\n<div class=\"markdown_views prism-tomorrow-night-eighties\" id=\"content_views\">\n  <svg style=\"display: none;\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n   <path d=\"M5,0 0,2.5 5,5z\" id=\"raphael-marker-block\" stroke-linecap=\"round\" style=\"-webkit-tap-highlight-color: rgba(0, 0, 0, 0);\">\n   <\/path>\n  <\/svg><\/p>\n<blockquote>\n<ul>\n<li>\n     <strong><br \/>\n      \ud83d\udc82 \u4e2a\u4eba\u7f51\u7ad9:\u3010<br \/>\n      <a href=\"https:\/\/haiyong.site\/moyu\" rel=\"nofollow\"><br \/>\n       \u6d77\u62e5<br \/>\n      <\/a><br \/>\n      \u3011\u3010<br \/>\n      <a href=\"https:\/\/code.haiyong.site\" rel=\"nofollow\"><br \/>\n       \u795e\u7ea7\u4ee3\u7801\u8d44\u6e90\u7f51\u7ad9<br \/>\n      <\/a><br \/>\n      \u3011\u3010<br \/>\n      <a href=\"https:\/\/tools.haiyong.site\/\" rel=\"nofollow\"><br \/>\n       \u529e\u516c\u795e\u5668<br \/>\n      <\/a><br \/>\n      \u3011<br \/>\n     <\/strong>\n    <\/li>\n<li>\n     <strong><br \/>\n      \ud83e\udd1f \u57fa\u4e8eWeb\u7aef\u6253\u9020\u7684\uff1a\ud83d\udc49<br \/>\n      <a href=\"https:\/\/sso.mapmost.com\/#\/login?source_inviter=ryIXGCHG\" rel=\"nofollow\"><br \/>\n       \u8f7b\u91cf\u5316\u5de5\u5177\u521b\u4f5c\u5e73\u53f0<br \/>\n      <\/a><br \/>\n     <\/strong>\n    <\/li>\n<li>\n     <strong><br \/>\n      \ud83d\udc85 \u60f3\u5bfb\u627e\u5171\u540c\u5b66\u4e60\u4ea4\u6d41\u7684\u5c0f\u4f19\u4f34\uff0c\u8bf7\u70b9\u51fb\u3010<br \/>\n      <a href=\"https:\/\/haiyong.site\/chat\/\" rel=\"nofollow\"><br \/>\n       \u5168\u6808\u6280\u672f\u4ea4\u6d41\u7fa4<br \/>\n      <\/a><br \/>\n      \u3011<br \/>\n     <\/strong>\n    <\/li>\n<\/ul>\n<\/blockquote>\n<p>\n   <strong><br \/>\n    \u7ed9\u5927\u5bb6\u5b89\u5229\u4e00\u4e2a\u514d\u8d39\u4e14\u5b9e\u7528\u7684\u8f7b\u91cf\u5316\u5de5\u5177\u521b\u4f5c\u5e73\u53f0\uff0c\ud83d\udc49<br \/>\n    <a href=\"https:\/\/sso.mapmost.com\/#\/login?source_inviter=ryIXGCHG\" rel=\"nofollow\"><br \/>\n     \u70b9\u51fb\u8df3\u8f6c\u5230\u7f51\u7ad9<br \/>\n    <\/a><br \/>\n    \u3002<br \/>\n   <\/strong>\n  <\/p>\n<p>\n   <a href=\"#jump99\" rel=\"nofollow\"><br \/>\n    <font color=\"#03a9f4\" size=\"5\"><br \/>\n     <b><br \/>\n      <u><br \/>\n       \u76f4\u63a5\u8df3\u5230\u672b\u5c3e<br \/>\n      <\/u><br \/>\n     <\/b><br \/>\n    <\/font><br \/>\n   <\/a><br \/>\n   <strong><br \/>\n    \u53c2\u4e0e\u8bc4\u8bba\u9001\u4e66<br \/>\n   <\/strong>\n  <\/p>\n<p>\n   \u6df1\u5ea6\u5b66\u4e60\u662f\u673a\u5668\u5b66\u4e60\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u5176\u4e2d\u7f16\u5199\u4e86\u6a21\u4eff\u4eba\u8111\u529f\u80fd\u7684\u7b97\u6cd5\u3002\u6df1\u5ea6\u5b66\u4e60\u4e2d\u6700\u5e38\u7528\u7684\u5e93\u662f Tensorflow \u548c PyTorch\u3002\u7531\u4e8e\u6709\u5404\u79cd\u53ef\u7528\u7684\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u4eba\u4eec\u53ef\u80fd\u60f3\u77e5\u9053\u4f55\u65f6\u4f7f\u7528 PyTorch\u3002\u4ee5\u4e0b\u662f\u4eba\u4eec\u53ef\u80fd\u66f4\u559c\u6b22\u5c06 Pytorch \u7528\u4e8e\u7279\u5b9a\u4efb\u52a1\u7684\u539f\u56e0\u3002\n  <\/p>\n<p>\n   Pytorch \u662f\u4e00\u4e2a\u5f00\u6e90\u6df1\u5ea6\u5b66\u4e60\u6846\u67b6\uff0c\u5e26\u6709 Python \u548c C++ \u63a5\u53e3\u3002Pytorch \u4f4d\u4e8e torch \u6a21\u5757\u4e2d\u3002\u5728 PyTorch \u4e2d\uff0c\u5fc5\u987b\u5904\u7406\u7684\u6570\u636e\u4ee5\u5f20\u91cf\u7684\u5f62\u5f0f\u8f93\u5165\u3002\n  <\/p>\n<h3>\n   <a id=\"_PyTorch_12\"><br \/>\n   <\/a><br \/>\n   \u5b89\u88c5 PyTorch<br \/>\n  <\/h3>\n<p>\n   \u5982\u679c\u60a8\u7684\u7cfb\u7edf\u4e2d\u5b89\u88c5\u4e86 Anaconda Python \u5305\u7ba1\u7406\u5668\uff0c\u90a3\u4e48\u901a\u8fc7\u5728\u7ec8\u7aef\u4e2d\u8fd0\u884c\u4ee5\u4e0b\u547d\u4ee4\u6765\u5b89\u88c5 PyTorch\uff1a\n  <\/p>\n<pre><code class=\"prism language-python\">conda install pytorch torchvision cpuonly <span class=\"token operator\">-<\/span>c pytorch\n<\/code><\/pre>\n<p>\n   \u5982\u679c\u60a8\u60f3\u4f7f\u7528 PyTorch \u800c\u4e0d\u5c06\u5176\u663e\u5f0f\u5b89\u88c5\u5230\u672c\u5730\u8ba1\u7b97\u673a\u4e2d\uff0c\u5219\u53ef\u4ee5\u4f7f\u7528 Google Colab\u3002\n  <\/p>\n<h3>\n   <a id=\"PyTorch__22\"><br \/>\n   <\/a><br \/>\n   PyTorch \u5f20\u91cf<br \/>\n  <\/h3>\n<p>\n   Pytorch \u7528\u4e8e\u5904\u7406\u5f20\u91cf\u3002\u5f20\u91cf\u662f\u591a\u7ef4\u6570\u7ec4\uff0c\u4f8b\u5982 n \u7ef4 NumPy \u6570\u7ec4\u3002\u4f46\u662f\uff0c\u5f20\u91cf\u4e5f\u53ef\u4ee5\u5728 GPU \u4e2d\u4f7f\u7528\uff0c\u4f46\u5728 NumPy \u6570\u7ec4\u7684\u60c5\u51b5\u4e0b\u5219\u4e0d\u7136\u3002PyTorch \u52a0\u901f\u4e86\u5f20\u91cf\u7684\u79d1\u5b66\u8ba1\u7b97\uff0c\u56e0\u4e3a\u5b83\u5177\u6709\u5404\u79cd\u5185\u7f6e\u529f\u80fd\u3002\n  <\/p>\n<p>\n   \u5411\u91cf\u662f\u4e00\u7ef4\u5f20\u91cf\uff0c\u77e9\u9635\u662f\u4e8c\u7ef4\u5f20\u91cf\u3002\u5728 C\u3001C++ \u548c Java \u4e2d\u4f7f\u7528\u7684\u5f20\u91cf\u548c\u591a\u7ef4\u6570\u7ec4\u4e4b\u95f4\u7684\u4e00\u4e2a\u663e\u7740\u533a\u522b\u662f\u5f20\u91cf\u5728\u6240\u6709\u7ef4\u5ea6\u4e0a\u5e94\u8be5\u5177\u6709\u76f8\u540c\u7684\u5217\u5927\u5c0f\u3002\u6b64\u5916\uff0c\u5f20\u91cf\u53ea\u80fd\u5305\u542b\u6570\u5b57\u6570\u636e\u7c7b\u578b\u3002\n  <\/p>\n<p>\n   \u5f20\u91cf\u7684\u4e24\u4e2a\u57fa\u672c\u5c5e\u6027\u662f\uff1a\n  <\/p>\n<p>\n   \u5f62\u72b6\uff1a\u6307\u6570\u7ec4\u6216\u77e9\u9635\u7684\u7ef4\u6570<br \/>\n   <br \/>\n   Rank\uff1a\u6307\u5f20\u91cf\u4e2d\u5b58\u5728\u7684\u7ef4\u6570\n  <\/p>\n<p>\n   \u4ee3\u7801\uff1a\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token comment\"># \u5bfc\u5165 torch<\/span>\n<span class=\"token keyword\">import<\/span> torch\n\n<span class=\"token comment\"># \u521b\u5efa\u5f20\u91cf<\/span>\nt1<span class=\"token operator\">=<\/span>torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">4<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\nt2<span class=\"token operator\">=<\/span>torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">4<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token punctuation\">[<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">6<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">7<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">8<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token punctuation\">[<\/span><span class=\"token number\">9<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">10<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">11<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">12<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u6253\u5370\u5f20\u91cf\uff1a<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Tensor t1: \\n\"<\/span><span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\nTensor t2: \\n\"<\/span><span class=\"token punctuation\">,<\/span> t2<span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u5f20\u91cf\u7684\u79e9<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\nRank of t1: \"<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token builtin\">len<\/span><span class=\"token punctuation\">(<\/span>t1<span class=\"token punctuation\">.<\/span>shape<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Rank of t2: \"<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token builtin\">len<\/span><span class=\"token punctuation\">(<\/span>t2<span class=\"token punctuation\">.<\/span>shape<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u5f20\u91cf\u7684\u5f62\u72b6<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\nRank of t1: \"<\/span><span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">.<\/span>shape<span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Rank of t2: \"<\/span><span class=\"token punctuation\">,<\/span> t2<span class=\"token punctuation\">.<\/span>shape<span class=\"token punctuation\">)<\/span>\n<\/code><\/pre>\n<p>\n   \u8f93\u51fa\uff1a\n  <\/p>\n<\/p>\n<h3>\n   <a id=\"_PyTorch__60\"><br \/>\n   <\/a><br \/>\n   \u5728 PyTorch \u4e2d\u521b\u5efa\u5f20\u91cf<br \/>\n  <\/h3>\n<p>\n   \u5728 PyTorch \u4e2d\u6709\u591a\u79cd\u521b\u5efa\u5f20\u91cf\u7684\u65b9\u6cd5\u3002\u5f20\u91cf\u53ef\u4ee5\u5305\u542b\u5355\u4e00\u6570\u636e\u7c7b\u578b\u7684\u5143\u7d20\u3002\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 python \u5217\u8868\u6216 NumPy \u6570\u7ec4\u521b\u5efa\u5f20\u91cf\u3002Torch \u6709 10 \u79cd\u7528\u4e8e GPU \u548c CPU \u7684\u5f20\u91cf\u53d8\u4f53\u3002\u4ee5\u4e0b\u662f\u5b9a\u4e49\u5f20\u91cf\u7684\u4e0d\u540c\u65b9\u6cd5\u3002\n  <\/p>\n<ul>\n<li>\n    <strong><br \/>\n     torch.Tensor()<br \/>\n    <\/strong><br \/>\n    \uff1a\u5b83\u590d\u5236\u6570\u636e\u5e76\u521b\u5efa\u5176\u5f20\u91cf\u3002\u5b83\u662f torch.FloatTensor \u7684\u522b\u540d\u3002\n   <\/li>\n<li>\n    <strong><br \/>\n     torch.tensor()<br \/>\n    <\/strong><br \/>\n    \uff1a\u5b83\u8fd8\u590d\u5236\u6570\u636e\u4ee5\u521b\u5efa\u5f20\u91cf\uff1b\u4f46\u662f\uff0c\u5b83\u4f1a\u81ea\u52a8\u63a8\u65ad\u6570\u636e\u7c7b\u578b\u3002\n   <\/li>\n<li>\n    <strong><br \/>\n     torch.as_tensor()<br \/>\n    <\/strong><br \/>\n    \uff1a\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6570\u636e\u662f\u5171\u4eab\u7684\uff0c\u5728\u521b\u5efa\u6570\u636e\u65f6\u4e0d\u4f1a\u88ab\u590d\u5236\uff0c\u5e76\u63a5\u53d7\u4efb\u4f55\u7c7b\u578b\u7684\u6570\u7ec4\u6765\u521b\u5efa\u5f20\u91cf\u3002\n   <\/li>\n<li>\n    <strong><br \/>\n     torch.from_numpy()<br \/>\n    <\/strong><br \/>\n    \uff1a\u5b83\u7c7b\u4f3c\u4e8e tensor.as_tensor() \u4f46\u5b83\u53ea\u63a5\u53d7 numpy \u6570\u7ec4\u3002\n   <\/li>\n<\/ul>\n<p>\n   \u4ee3\u7801\uff1a\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token comment\"># \u5bfc\u5165 torch \u6a21\u5757<\/span>\n<span class=\"token keyword\">import<\/span> torch\n<span class=\"token keyword\">import<\/span> numpy <span class=\"token keyword\">as<\/span> np\n\n<span class=\"token comment\"># \u5b58\u50a8\u4e3a\u5f20\u91cf\u7684\u503c\u5217\u8868<\/span>\ndata1 <span class=\"token operator\">=<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">4<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">6<\/span><span class=\"token punctuation\">]<\/span>\ndata2 <span class=\"token operator\">=<\/span> np<span class=\"token punctuation\">.<\/span>array<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">1.5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3.4<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">6.8<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token number\">9.3<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">7.0<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2.8<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u521b\u5efa\u5f20\u91cf\u548c\u6253\u5370<\/span>\nt1 <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span>data1<span class=\"token punctuation\">)<\/span>\nt2 <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>Tensor<span class=\"token punctuation\">(<\/span>data1<span class=\"token punctuation\">)<\/span>\nt3 <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>as_tensor<span class=\"token punctuation\">(<\/span>data2<span class=\"token punctuation\">)<\/span>\nt4 <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>from_numpy<span class=\"token punctuation\">(<\/span>data2<span class=\"token punctuation\">)<\/span>\n\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Tensor: \"<\/span><span class=\"token punctuation\">,<\/span>t1<span class=\"token punctuation\">,<\/span> <span class=\"token string\">\"Data type: \"<\/span><span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">.<\/span>dtype<span class=\"token punctuation\">,<\/span><span class=\"token string\">\"\\n\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Tensor: \"<\/span><span class=\"token punctuation\">,<\/span>t2<span class=\"token punctuation\">,<\/span> <span class=\"token string\">\"Data type: \"<\/span><span class=\"token punctuation\">,<\/span> t2<span class=\"token punctuation\">.<\/span>dtype<span class=\"token punctuation\">,<\/span><span class=\"token string\">\"\\n\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Tensor: \"<\/span><span class=\"token punctuation\">,<\/span>t3<span class=\"token punctuation\">,<\/span> <span class=\"token string\">\"Data type: \"<\/span><span class=\"token punctuation\">,<\/span> t3<span class=\"token punctuation\">.<\/span>dtype<span class=\"token punctuation\">,<\/span><span class=\"token string\">\"\\n\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Tensor: \"<\/span><span class=\"token punctuation\">,<\/span>t4<span class=\"token punctuation\">,<\/span> <span class=\"token string\">\"Data type: \"<\/span><span class=\"token punctuation\">,<\/span> t4<span class=\"token punctuation\">.<\/span>dtype<span class=\"token punctuation\">,<\/span><span class=\"token string\">\"\\n\"<\/span><span class=\"token punctuation\">)<\/span>\n<\/code><\/pre>\n<p>\n   \u8f93\u51fa\uff1a\n  <\/p>\n<\/p>\n<h3>\n   <a id=\"_Pytorch__95\"><br \/>\n   <\/a><br \/>\n   \u5728 Pytorch \u4e2d\u91cd\u6784\u5f20\u91cf<br \/>\n  <\/h3>\n<p>\n   \u6211\u4eec\u53ef\u4ee5\u5728 PyTorch \u4e2d\u6839\u636e\u9700\u8981\u4fee\u6539\u5f20\u91cf\u7684\u5f62\u72b6\u548c\u5927\u5c0f\u3002\u6211\u4eec\u8fd8\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a nd \u5f20\u91cf\u7684\u8f6c\u7f6e\u3002\u4ee5\u4e0b\u662f\u6839\u636e\u9700\u8981\u66f4\u6539\u5f20\u91cf\u7ed3\u6784\u7684\u4e09\u79cd\u5e38\u7528\u65b9\u6cd5\uff1a\n  <\/p>\n<p>\n   <strong><br \/>\n    .reshape(a, b)<br \/>\n   <\/strong><br \/>\n   :\u8fd4\u56de\u4e00\u4e2a\u5927\u5c0f\u4e3a a,b \u7684\u65b0\u5f20\u91cf<br \/>\n   <br \/>\n   <strong><br \/>\n    .resize(a, b)<br \/>\n   <\/strong><br \/>\n   :\u8fd4\u56de\u5927\u5c0f\u4e3a a,b \u7684\u76f8\u540c\u5f20\u91cf<br \/>\n   <br \/>\n   <strong><br \/>\n    .transpose(a, b)<br \/>\n   <\/strong><br \/>\n   \uff1a\u8fd4\u56de\u5728 a \u548c b \u7ef4\u4e2d\u8f6c\u7f6e\u7684\u5f20\u91cf\n  <\/p>\n<\/p>\n<p>\n   \u4ee3\u7801\uff1a\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token comment\"># \u5bfc\u5165 torch \u6a21\u5757<\/span>\n<span class=\"token keyword\">import<\/span> torch\n\n<span class=\"token comment\"># \u5b9a\u4e49\u5f20\u91cf<\/span>\nt <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">4<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token punctuation\">[<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">6<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">7<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">8<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token punctuation\">[<\/span><span class=\"token number\">9<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">10<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">11<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">12<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u91cd\u5851\u5f20\u91cf<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"Reshaping\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>t<span class=\"token punctuation\">.<\/span>reshape<span class=\"token punctuation\">(<\/span><span class=\"token number\">6<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u8c03\u6574\u5f20\u91cf\u7684\u5927\u5c0f<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\nResizing\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>t<span class=\"token punctuation\">.<\/span>resize<span class=\"token punctuation\">(<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">6<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u8f6c\u7f6e\u5f20\u91cf<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\nTransposing\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>t<span class=\"token punctuation\">.<\/span>transpose<span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">0<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n<\/code><\/pre>\n<\/p>\n<h3>\n   <a id=\"PyTorch__132\"><br \/>\n   <\/a><br \/>\n   PyTorch \u4e2d\u5f20\u91cf\u7684\u6570\u5b66\u8fd0\u7b97<br \/>\n  <\/h3>\n<p>\n   \u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 Pytorch \u5bf9\u5f20\u91cf\u6267\u884c\u5404\u79cd\u6570\u5b66\u8fd0\u7b97\u3002\u6267\u884c\u6570\u5b66\u8fd0\u7b97\u7684\u4ee3\u7801\u4e0e NumPy \u6570\u7ec4\u7684\u4ee3\u7801\u76f8\u540c\u3002\u4e0b\u9762\u662f\u5728\u5f20\u91cf\u4e2d\u6267\u884c\u56db\u79cd\u57fa\u672c\u64cd\u4f5c\u7684\u4ee3\u7801\u3002\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token comment\"># \u5bfc\u5165 torch \u6a21\u5757<\/span>\n<span class=\"token keyword\">import<\/span> torch\n\n<span class=\"token comment\"># \u5b9a\u4e49\u4e24\u4e2a\u5f20\u91cf<\/span>\nt1 <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">2<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">3<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">4<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\nt2 <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">6<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">7<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">8<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u6dfb\u52a0\u4e24\u4e2a\u5f20\u91cf<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"tensor2 + tensor1\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>torch<span class=\"token punctuation\">.<\/span>add<span class=\"token punctuation\">(<\/span>t2<span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u51cf\u53bb\u4e24\u4e2a\u5f20\u91cf<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\ntensor2 - tensor1\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>torch<span class=\"token punctuation\">.<\/span>sub<span class=\"token punctuation\">(<\/span>t2<span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u5c06\u4e24\u4e2a\u5f20\u91cf\u76f8\u4e58<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\ntensor2 * tensor1\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>torch<span class=\"token punctuation\">.<\/span>mul<span class=\"token punctuation\">(<\/span>t2<span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u5c06\u4e24\u4e2a\u5f20\u91cf\u76f8\u9664<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"\\ntensor2 \/ tensor1\"<\/span><span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>torch<span class=\"token punctuation\">.<\/span>div<span class=\"token punctuation\">(<\/span>t2<span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n<\/code><\/pre>\n<p>\n   \u8f93\u51fa\uff1a\n  <\/p>\n<\/p>\n<h3>\n   <a id=\"Pytorch__164\"><br \/>\n   <\/a><br \/>\n   Pytorch \u6a21\u5757<br \/>\n  <\/h3>\n<p>\n   PyTorch \u5e93\u6a21\u5757\u5bf9\u4e8e\u521b\u5efa\u548c\u8bad\u7ec3\u795e\u7ecf\u7f51\u7edc\u81f3\u5173\u91cd\u8981\u3002\u4e09\u4e2a\u4e3b\u8981\u7684\u5e93\u6a21\u5757\u662f Autograd\u3001Optim \u548c nn\u3002\n  <\/p>\n<ol>\n<li>\n    Autograd \u6a21\u5757\uff1a autograd \u63d0\u4f9b\u4e86\u8f7b\u677e\u8ba1\u7b97\u68af\u5ea6\u7684\u529f\u80fd\uff0c\u65e0\u9700\u663e\u5f0f\u624b\u52a8\u5b9e\u73b0\u6240\u6709\u5c42\u7684\u524d\u5411\u548c\u540e\u5411\u4f20\u9012\u3002\n   <\/li>\n<\/ol>\n<p>\n   \u4e3a\u4e86\u8bad\u7ec3\u4efb\u4f55\u795e\u7ecf\u7f51\u7edc\uff0c\u6211\u4eec\u6267\u884c\u53cd\u5411\u4f20\u64ad\u6765\u8ba1\u7b97\u68af\u5ea6\u3002\u901a\u8fc7\u8c03\u7528 .backward() \u51fd\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u8ba1\u7b97\u4ece\u6839\u5230\u53f6\u7684\u6bcf\u4e2a\u68af\u5ea6\u3002\n  <\/p>\n<p>\n   \u4ee3\u7801\uff1a\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token comment\"># \u5bfc\u5165 torch<\/span>\n<span class=\"token keyword\">import<\/span> torch\n\n<span class=\"token comment\"># \u521b\u5efa\u5f20\u91cf<\/span>\nt1<span class=\"token operator\">=<\/span>torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token number\">1.0<\/span><span class=\"token punctuation\">,<\/span> requires_grad <span class=\"token operator\">=<\/span> <span class=\"token boolean\">True<\/span><span class=\"token punctuation\">)<\/span>\nt2<span class=\"token operator\">=<\/span>torch<span class=\"token punctuation\">.<\/span>tensor<span class=\"token punctuation\">(<\/span><span class=\"token number\">2.0<\/span><span class=\"token punctuation\">,<\/span> requires_grad <span class=\"token operator\">=<\/span> <span class=\"token boolean\">True<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u521b\u5efa\u53d8\u91cf\u548c\u6e10\u53d8<\/span>\nz<span class=\"token operator\">=<\/span><span class=\"token number\">100<\/span> <span class=\"token operator\">*<\/span> t1 <span class=\"token operator\">*<\/span> t2\nz<span class=\"token punctuation\">.<\/span>backward<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u6253\u5370\u6e10\u53d8<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"dz\/dt1 : \"<\/span><span class=\"token punctuation\">,<\/span> t1<span class=\"token punctuation\">.<\/span>grad<span class=\"token punctuation\">.<\/span>data<span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span><span class=\"token string\">\"dz\/dt2 : \"<\/span><span class=\"token punctuation\">,<\/span> t2<span class=\"token punctuation\">.<\/span>grad<span class=\"token punctuation\">.<\/span>data<span class=\"token punctuation\">)<\/span>\n<\/code><\/pre>\n<p>\n   \u8f93\u51fa\uff1a\n  <\/p>\n<\/p>\n<ol start=\"2\">\n<li>\n    Optim Module\uff1a PyTorch Optium Module\uff0c\u6709\u52a9\u4e8e\u5b9e\u73b0\u5404\u79cd\u4f18\u5316\u7b97\u6cd5\u3002\u8be5\u8f6f\u4ef6\u5305\u5305\u542b\u6700\u5e38\u7528\u7684\u7b97\u6cd5\uff0c\u5982 Adam\u3001SGD \u548c RMS-Prop\u3002\u8981\u4f7f\u7528 torch.optim\uff0c\u6211\u4eec\u9996\u5148\u9700\u8981\u6784\u9020\u4e00\u4e2a Optimizer \u5bf9\u8c61\uff0c\u8be5\u5bf9\u8c61\u5c06\u4fdd\u7559\u53c2\u6570\u5e76\u76f8\u5e94\u5730\u66f4\u65b0\u5b83\u3002\u9996\u5148\uff0c\u6211\u4eec\u901a\u8fc7\u63d0\u4f9b\u6211\u4eec\u60f3\u8981\u4f7f\u7528\u7684\u4f18\u5316\u5668\u7b97\u6cd5\u6765\u5b9a\u4e49\u4f18\u5316\u5668\u3002\u6211\u4eec\u5728\u53cd\u5411\u4f20\u64ad\u4e4b\u524d\u5c06\u68af\u5ea6\u8bbe\u7f6e\u4e3a\u96f6\u3002\u7136\u540e\u4e3a\u4e86\u66f4\u65b0\u53c2\u6570\uff0c\u8c03\u7528 optimizer.step()\u3002\n   <\/li>\n<\/ol>\n<blockquote>\n<p>\n    optimizer = torch.optim.Adam(model.parameters(), lr=0.01) #\u5b9a\u4e49\u4f18\u5316\u5668\n   <\/p>\n<p>\n    optimizer.zero_grad() #\u5c06\u68af\u5ea6\u8bbe\u7f6e\u4e3a\u96f6\n   <\/p>\n<p>\n    optimizer.step() #\u53c2\u6570\u66f4\u65b0\n   <\/p>\n<\/blockquote>\n<ol start=\"3\">\n<li>\n    nn \u6a21\u5757\uff1a\u8fd9\u4e2a\u5305\u6709\u52a9\u4e8e\u6784\u5efa\u795e\u7ecf\u7f51\u7edc\u3002\u5b83\u7528\u4e8e\u6784\u5efa\u56fe\u5c42\u3002\n   <\/li>\n<\/ol>\n<p>\n   \u4e3a\u4e86\u521b\u5efa\u4e00\u4e2a\u5355\u5c42\u6a21\u578b\uff0c\u6211\u4eec\u53ef\u4ee5\u7b80\u5355\u5730\u4f7f\u7528 nn.Sequential() \u6765\u5b9a\u4e49\u5b83\u3002\n  <\/p>\n<blockquote>\n<p>\n    model = nn.Sequential(nn.Linear(in, out), nn.Sigmoid(), nn.Linear(_in,<br \/>\n    <br \/>\n    _out), nn.Sigmoid())\n   <\/p>\n<\/blockquote>\n<p>\n   \u5bf9\u4e8e\u4e0d\u5728\u5355\u4e2a\u5e8f\u5217\u4e2d\u7684\u6a21\u578b\u7684\u5b9e\u73b0\uff0c\u6211\u4eec\u901a\u8fc7\u7ee7\u627f nn.Module \u7c7b\u6765\u5b9a\u4e49\u6a21\u578b\u3002\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token keyword\">class<\/span> <span class=\"token class-name\">Model<\/span> <span class=\"token punctuation\">(<\/span>nn<span class=\"token punctuation\">.<\/span>Module<span class=\"token punctuation\">)<\/span> <span class=\"token punctuation\">:<\/span>\n\n\t\t<span class=\"token keyword\">def<\/span> <span class=\"token function\">__init__<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span>\n\n\t\t\t<span class=\"token builtin\">super<\/span><span class=\"token punctuation\">(<\/span>Model<span class=\"token punctuation\">,<\/span> self<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>__init__<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\n\n\t\t\tself<span class=\"token punctuation\">.<\/span>linear <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>nn<span class=\"token punctuation\">.<\/span>Linear<span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\n\n\t<span class=\"token keyword\">def<\/span> <span class=\"token function\">forward<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> x<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span>\n\n\t\t\ty_pred <span class=\"token operator\">=<\/span> self<span class=\"token punctuation\">.<\/span>linear<span class=\"token punctuation\">(<\/span>x<span class=\"token punctuation\">)<\/span>\n\n\t\t\t<span class=\"token keyword\">return<\/span> y_pred\n<\/code><\/pre>\n<h3>\n   <a id=\"PyTorch__227\"><br \/>\n   <\/a><br \/>\n   PyTorch \u6570\u636e\u96c6\u548c\u6570\u636e\u52a0\u8f7d\u5668<br \/>\n  <\/h3>\n<p>\n   torch.utils.data.Dataset \u7c7b\u5305\u542b\u6240\u6709\u81ea\u5b9a\u4e49\u6570\u636e\u96c6\u3002\u6211\u4eec\u9700\u8981\u5b9e\u73b0\u4e24\u4e2a\u65b9\u6cd5\uff0c<br \/>\n   <code><br \/>\n    __len__()<br \/>\n   <\/code><br \/>\n   \u548c<br \/>\n   <code><br \/>\n    __get_item__()<br \/>\n   <\/code><br \/>\n   \uff0c\u6765\u521b\u5efa\u6211\u4eec\u81ea\u5df1\u7684\u6570\u636e\u96c6\u7c7b\u3002\n  <\/p>\n<p>\n   PyTorch \u6570\u636e\u52a0\u8f7d\u5668\u5177\u6709\u4e00\u4e2a\u60ca\u4eba\u7684\u7279\u6027\uff0c\u5373\u4e0e\u81ea\u52a8\u6279\u5904\u7406\u5e76\u884c\u52a0\u8f7d\u6570\u636e\u96c6\u3002\u56e0\u6b64\uff0c\u5b83\u51cf\u5c11\u4e86\u987a\u5e8f\u52a0\u8f7d\u6570\u636e\u96c6\u7684\u65f6\u95f4\uff0c\u4ece\u800c\u63d0\u9ad8\u4e86\u901f\u5ea6\u3002\n  <\/p>\n<blockquote>\n<p>\n    \u8bed\u6cd5\uff1a DataLoader(dataset, shuffle=True, sampler=None,<br \/>\n    <br \/>\n    batch_sampler=None, batch_size=32)\n   <\/p>\n<\/blockquote>\n<p>\n   PyTorch DataLoader \u652f\u6301\u4e24\u79cd\u7c7b\u578b\u7684\u6570\u636e\u96c6\uff1a\n  <\/p>\n<p>\n   \u5730\u56fe\u6837\u5f0f\u6570\u636e\u96c6\uff1a\u6570\u636e\u9879\u6620\u5c04\u5230\u7d22\u5f15\u3002\u5728\u8fd9\u4e9b\u6570\u636e\u96c6\u4e2d\uff0c<br \/>\n   <code><br \/>\n    __get_item__()<br \/>\n   <\/code><br \/>\n   \u65b9\u6cd5\u7528\u4e8e\u68c0\u7d22\u6bcf\u4e2a\u9879\u76ee\u7684\u7d22\u5f15\u3002<br \/>\n   <br \/>\n   \u53ef\u8fed\u4ee3\u5f0f\u6570\u636e\u96c6\uff1a\u5728\u8fd9\u4e9b\u6570\u636e\u96c6\u4e2d\u5b9e\u73b0\u4e86<br \/>\n   <code><br \/>\n    __iter__()<br \/>\n   <\/code><br \/>\n   \u534f\u8bae\u3002\u6570\u636e\u6837\u672c\u6309\u987a\u5e8f\u68c0\u7d22\u3002\n  <\/p>\n<h3>\n   <a id=\"_PyTorch__242\"><br \/>\n   <\/a><br \/>\n   \u4f7f\u7528 PyTorch \u6784\u5efa\u795e\u7ecf\u7f51\u7edc<br \/>\n  <\/h3>\n<p>\n   \u6211\u4eec\u5c06\u5728\u9010\u6b65\u5b9e\u73b0\u4e2d\u770b\u5230\u8fd9\u4e00\u70b9\uff1a\n  <\/p>\n<p>\n   1.<br \/>\n   <strong><br \/>\n    \u6570\u636e\u96c6\u51c6\u5907<br \/>\n   <\/strong><br \/>\n   \uff1a\u7531\u4e8e PyTorch \u4e2d\u7684\u4e00\u5207\u90fd\u4ee5\u5f20\u91cf\u7684\u5f62\u5f0f\u8868\u793a\uff0c\u6240\u4ee5\u6211\u4eec\u5e94\u8be5\u9996\u5148\u4f7f\u7528\u5f20\u91cf\u3002<br \/>\n   <br \/>\n   2.<br \/>\n   <strong><br \/>\n    \u6784\u5efa\u6a21\u578b<br \/>\n   <\/strong><br \/>\n   \uff1a\u4e3a\u4e86\u6784\u5efa\u4e2d\u6027\u7f51\u7edc\uff0c\u6211\u4eec\u9996\u5148\u5b9a\u4e49\u8f93\u5165\u5c42\u3001\u9690\u85cf\u5c42\u548c\u8f93\u51fa\u5c42\u7684\u6570\u91cf\u3002\u6211\u4eec\u8fd8\u9700\u8981\u5b9a\u4e49\u521d\u59cb\u6743\u91cd\u3002\u6743\u91cd\u77e9\u9635\u7684\u503c\u662f\u4f7f\u7528torch.randn()\u968f\u673a\u9009\u62e9\u7684\u3002Torch.randn() \u8fd4\u56de\u4e00\u4e2a\u7531\u6765\u81ea\u6807\u51c6\u6b63\u6001\u5206\u5e03\u7684\u968f\u673a\u6570\u7ec4\u6210\u7684\u5f20\u91cf\u3002<br \/>\n   <br \/>\n   3.<br \/>\n   <strong><br \/>\n    \u524d\u5411\u4f20\u64ad<br \/>\n   <\/strong><br \/>\n   \uff1a\u5c06\u6570\u636e\u9988\u9001\u5230\u795e\u7ecf\u7f51\u7edc\uff0c\u5e76\u5728\u6743\u91cd\u548c\u8f93\u5165\u4e4b\u95f4\u6267\u884c\u77e9\u9635\u4e58\u6cd5\u3002\u8fd9\u53ef\u4ee5\u4f7f\u7528\u624b\u7535\u7b52\u8f7b\u677e\u5b8c\u6210\u3002<br \/>\n   <br \/>\n   4.<br \/>\n   <strong><br \/>\n    \u635f\u5931\u8ba1\u7b97<br \/>\n   <\/strong><br \/>\n   \uff1a PyTorch.nn \u51fd\u6570\u6709\u591a\u4e2a\u635f\u5931\u51fd\u6570\u3002\u635f\u5931\u51fd\u6570\u7528\u4e8e\u8861\u91cf\u9884\u6d4b\u503c\u4e0e\u76ee\u6807\u503c\u4e4b\u95f4\u7684\u8bef\u5dee\u3002<br \/>\n   <br \/>\n   5.<br \/>\n   <strong><br \/>\n    \u53cd\u5411\u4f20\u64ad<br \/>\n   <\/strong><br \/>\n   \uff1a\u7528\u4e8e\u4f18\u5316\u6743\u91cd\u3002\u66f4\u6539\u6743\u91cd\u4ee5\u4f7f\u635f\u5931\u6700\u5c0f\u5316\u3002\n  <\/p>\n<p>\n   \u73b0\u5728\u8ba9\u6211\u4eec\u4ece\u5934\u5f00\u59cb\u6784\u5efa\u4e00\u4e2a\u795e\u7ecf\u7f51\u7edc\uff1a\n  <\/p>\n<pre><code class=\"prism language-python\"><span class=\"token comment\"># \u5bfc\u5165 torch<\/span>\n<span class=\"token keyword\">import<\/span> torch\n\n<span class=\"token comment\"># \u8bad\u7ec3 input(X) \u548c output(y)<\/span>\nX <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>Tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">2<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">3<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token punctuation\">[<\/span><span class=\"token number\">4<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">6<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\ny <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>Tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">5<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">10<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">15<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span>\n\t\t\t\t<span class=\"token punctuation\">[<\/span><span class=\"token number\">20<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">25<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">30<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token keyword\">class<\/span> <span class=\"token class-name\">Model<\/span><span class=\"token punctuation\">(<\/span>torch<span class=\"token punctuation\">.<\/span>nn<span class=\"token punctuation\">.<\/span>Module<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span>\n\n\t<span class=\"token comment\"># defining layer<\/span>\n\t<span class=\"token keyword\">def<\/span> <span class=\"token function\">__init__<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span>\n\t\t<span class=\"token builtin\">super<\/span><span class=\"token punctuation\">(<\/span>Model<span class=\"token punctuation\">,<\/span> self<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">.<\/span>__init__<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\n\t\tself<span class=\"token punctuation\">.<\/span>linear <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>nn<span class=\"token punctuation\">.<\/span>Linear<span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\n\t\n\t<span class=\"token comment\"># \u5b9e\u65bd\u524d\u5411\u4f20\u9012<\/span>\n\t<span class=\"token keyword\">def<\/span> <span class=\"token function\">forward<\/span><span class=\"token punctuation\">(<\/span>self<span class=\"token punctuation\">,<\/span> x<span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span>\n\t\ty_pred <span class=\"token operator\">=<\/span> self<span class=\"token punctuation\">.<\/span>linear<span class=\"token punctuation\">(<\/span>x<span class=\"token punctuation\">)<\/span>\n\t\t<span class=\"token keyword\">return<\/span> y_pred\n\nmodel <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>nn<span class=\"token punctuation\">.<\/span>Linear<span class=\"token punctuation\">(<\/span><span class=\"token number\">1<\/span> <span class=\"token punctuation\">,<\/span> <span class=\"token number\">1<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u5b9a\u4e49\u635f\u5931\u51fd\u6570\u548c\u4f18\u5316\u5668<\/span>\nloss_fn <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>nn<span class=\"token punctuation\">.<\/span>L1Loss<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\noptimizer <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>optim<span class=\"token punctuation\">.<\/span>Adam<span class=\"token punctuation\">(<\/span>model<span class=\"token punctuation\">.<\/span>parameters<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">,<\/span> lr <span class=\"token operator\">=<\/span> <span class=\"token number\">0.01<\/span> <span class=\"token punctuation\">)<\/span>\n\n<span class=\"token keyword\">for<\/span> epoch <span class=\"token keyword\">in<\/span> <span class=\"token builtin\">range<\/span><span class=\"token punctuation\">(<\/span><span class=\"token number\">1000<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">:<\/span>\n\t\n\t<span class=\"token comment\"># \u4f7f\u7528\u521d\u59cb\u6743\u91cd\u9884\u6d4b y<\/span>\n\ty_pred <span class=\"token operator\">=<\/span> model<span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">.<\/span>requires_grad_<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span><span class=\"token punctuation\">)<\/span>\n\n\t<span class=\"token comment\"># \u635f\u5931\u8ba1\u7b97<\/span>\n\tloss <span class=\"token operator\">=<\/span> loss_fn<span class=\"token punctuation\">(<\/span>y_pred<span class=\"token punctuation\">,<\/span> y<span class=\"token punctuation\">)<\/span>\n\n\t<span class=\"token comment\"># \u8ba1\u7b97\u68af\u5ea6<\/span>\n\tloss<span class=\"token punctuation\">.<\/span>backward<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\n\n\t<span class=\"token comment\"># \u66f4\u65b0\u6743\u91cd<\/span>\n\toptimizer<span class=\"token punctuation\">.<\/span>step<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\n\n\toptimizer<span class=\"token punctuation\">.<\/span>zero_grad<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">)<\/span>\n\n<span class=\"token comment\"># \u6d4b\u8bd5\u65b0\u6570\u636e<\/span>\nX <span class=\"token operator\">=<\/span> torch<span class=\"token punctuation\">.<\/span>Tensor<span class=\"token punctuation\">(<\/span><span class=\"token punctuation\">[<\/span><span class=\"token punctuation\">[<\/span><span class=\"token number\">7<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">,<\/span> <span class=\"token punctuation\">[<\/span><span class=\"token number\">8<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">]<\/span><span class=\"token punctuation\">)<\/span>\npredicted <span class=\"token operator\">=<\/span> model<span class=\"token punctuation\">(<\/span>X<span class=\"token punctuation\">)<\/span>\n<span class=\"token keyword\">print<\/span><span class=\"token punctuation\">(<\/span>predicted<span class=\"token punctuation\">)<\/span>\n\n<\/code><\/pre>\n<p>\n   \u8f93\u51fa\uff1a\n  <\/p>\n<\/p>\n<h3>\n   <a id=\"_309\"><br \/>\n   <\/a><br \/>\n   \ud83c\udf81\u53c2\u4e0e\u8bc4\u8bba\u9001\u4e66<br \/>\n  <\/h3>\n<p>\n   \u672c\u6b21\u9001\u4e66 8 \u672c\uff0c\u4ee5\u540e\u6bcf\u5468\u65b0\u6587\u8bc4\u8bba\u533a\u81f3\u5c11\u62bd\u4e09\u4f4d\u670b\u53cb\u9001\u4e66\uff0c\u5927\u5bb6\u53ef\u6301\u7eed\u5173\u6ce8\u6211\uff1a<br \/>\n   <a href=\"https:\/\/blog.csdn.net\/qq_44273429\"><br \/>\n    \u6d77\u62e5<br \/>\n   <\/a>\n  <\/p>\n<\/p>\n<blockquote>\n<p>\n    \u672c\u4e66\u4e3b\u8981\u4ecb\u7ecd\u4eba\u5de5\u667a\u80fd\u7814\u7a76\u9886\u57df\u4e2d\u795e\u7ecf\u7f51\u7edc\u7684PyTorch\u67b6\u6784\uff0c\u5bf9\u5176\u5728\u591a\u4e2a\u9886\u57df\u7684\u5e94\u7528\u8fdb\u884c\u7cfb\u7edf\u6027\u7684\u5f52\u7eb3\u548c\u68b3\u7406\u3002\u4e66\u4e2d\u7684\u6848\u4f8b\u6709\u98ce\u666f\u56fe\u5206\u7c7b\u3001\u4eba\u50cf\u524d\u666f\u80cc\u666f\u5206\u5272\u3001\u4f4e\u5149\u7167\u56fe\u50cf\u589e\u6cd5\u3001\u52a8\u6f2b\u5934\u50cf\u751f\u6210\u3001\u753b\u98ce\u8fc1\u79fb\u3001\u98ce\u683c\u8f6c\u6362\u7b49\uff0c\u5bf9\u6bcf\u9879\u89c6\u89c9\u4efb\u52a1\u7684\u7814\u7a76\u80cc\u666f\u3001\u5e94\u7528\u4ef7\u503c\u3001\u7b97\u6cd5\u539f\u7406\u3001\u4ee3\u7801\u5b9e\u73b0\u548c\u79fb\u52a8\u7aef\u90e8\u7f72\u6d41\u7a0b\u8fdb\u884c\u4e86\u8be6\u7ec6\u63cf\u8ff0\uff0c\u5e76\u63d0\u4f9b\u76f8\u5e94\u7684\u6e90\u7801\uff0c\u9002\u5408\u8bfb\u8005\u4ece0\u52301\u6784\u5efa\u79fb\u52a8\u7aef\u667a\u80fd\u5e94\u7528\u3002\n   <\/p>\n<\/blockquote>\n<p>\n   \u672c\u4e66\u9002\u5408\u5bf9\u4eba\u5de5\u667a\u80fd\u5b9e\u9645\u5e94\u7528\u611f\u5174\u8da3\u7684\u672c\u79d1\u751f\u3001\u7814\u7a76\u751f\u3001\u6df1\u5ea6\u5b66\u4e60\u7b97\u6cd5\u5de5\u7a0b\u5e08\u3001\u8ba1\u7b97\u673a\u89c6\u89c9\u4ece\u4e1a\u4eba\u5458\u548c\u4eba\u5de5\u667a\u80fd\u7231\u597d\u8005\u9605\u8bfb\uff0c\u4e66\u4e2d\u4ecb\u7ecd\u7684\u5404\u9879\u89c6\u89c9\u4efb\u52a1\u5747\u542b\u6709\u76f8\u5e94\u7684\u5b89\u5353\u5e73\u53f0\u90e8\u7f72\u6848\u4f8b\uff0c\u4e0d\u4ec5\u5bf9\u5b66\u751f\u53c2\u52a0\u6bd4\u8d5b\u3001\u8bfe\u7a0b\u8bbe\u8ba1\u5177\u6709\u53c2\u8003\u610f\u4e49\uff0c\u5bf9\u76f8\u5173\u4ece\u4e1a\u4eba\u5458\u7684\u8f6f\u4ef6\u67b6\u6784\u548c\u7814\u53d1\u4e5f\u5177\u6709\u542f\u53d1\u4ef7\u503c\u3002\n  <\/p>\n<p>\n   \u89c9\u5f97\u81ea\u5df1\u62bd\u4e0d\u5230\uff0c\u60f3\u81ea\u5df1\u4e70\u7684\u4e5f\u53ef\u4ee5\u53c2\u8003\u6b64\u94fe\u63a5\uff1a<br \/>\n   <a href=\"https:\/\/item.jd.com\/13176891.html\" 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