{"id":4365,"date":"2024-03-14T12:56:25","date_gmt":"2024-03-14T03:56:25","guid":{"rendered":"https:\/\/www.silicloud.com\/ja\/blog\/pytorch%e3%81%a7%e3%83%86%e3%83%b3%e3%82%bd%e3%83%ab%e3%82%92%e4%bd%9c%e6%88%90%e3%81%97%e3%81%a6%e6%93%8d%e4%bd%9c%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b\/"},"modified":"2025-08-02T20:44:41","modified_gmt":"2025-08-02T11:44:41","slug":"pytorch%e3%81%a7%e3%83%86%e3%83%b3%e3%82%bd%e3%83%ab%e3%82%92%e4%bd%9c%e6%88%90%e3%81%97%e3%81%a6%e6%93%8d%e4%bd%9c%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b","status":"publish","type":"post","link":"https:\/\/www.silicloud.com\/ja\/blog\/pytorch%e3%81%a7%e3%83%86%e3%83%b3%e3%82%bd%e3%83%ab%e3%82%92%e4%bd%9c%e6%88%90%e3%81%97%e3%81%a6%e6%93%8d%e4%bd%9c%e3%81%99%e3%82%8b%e6%96%b9%e6%b3%95%e3%81%af%e4%bd%95%e3%81%a7%e3%81%99%e3%81%8b\/","title":{"rendered":"PyTorch\u3067\u30c6\u30f3\u30bd\u30eb\u3092\u4f5c\u6210\u3057\u3066\u64cd\u4f5c\u3059\u308b\u65b9\u6cd5\u306f\u4f55\u3067\u3059\u304b\uff1f"},"content":{"rendered":"<p>PyTorch\u3067\u30c6\u30f3\u30bd\u30eb\u3092\u4f5c\u6210\u3057\u3066\u64cd\u4f5c\u3059\u308b\u306b\u306f\u3001\u307e\u305atorch\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u4e00\u822c\u7684\u306a\u30c6\u30f3\u30bd\u30eb\u306e\u4f5c\u6210\u3068\u64cd\u4f5c\u65b9\u6cd5\u306e\u3044\u304f\u3064\u304b\u3067\u3059\uff1a<\/p>\n<ol>\n<li>\u30c6\u30f3\u30bd\u30eb\u306e\u751f\u6210:<\/li>\n<\/ol>\n<pre class=\"post-pre\"><code><span class=\"hljs-keyword\">import<\/span> torch\r\n\r\n<span class=\"hljs-comment\"># \u521b\u5efa\u4e00\u4e2a\u7a7a\u7684\u5f20\u91cf<\/span>\r\nempty_tensor = torch.Tensor()\r\n\r\n<span class=\"hljs-comment\"># \u521b\u5efa\u4e00\u4e2a\u5305\u542b\u968f\u673a\u6570\u636e\u7684\u5f20\u91cf<\/span>\r\nrandom_tensor = torch.rand(<span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>)\r\n\r\n<span class=\"hljs-comment\"># \u521b\u5efa\u4e00\u4e2a\u5168\u96f6\u7684\u5f20\u91cf<\/span>\r\nzero_tensor = torch.zeros(<span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>)\r\n\r\n<span class=\"hljs-comment\"># \u521b\u5efa\u4e00\u4e2a\u5168\u4e00\u7684\u5f20\u91cf<\/span>\r\nones_tensor = torch.ones(<span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>)\r\n\r\n<span class=\"hljs-comment\"># \u4ecePython\u5217\u8868\u521b\u5efa\u5f20\u91cf<\/span>\r\nlist_tensor = torch.tensor([<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>])\r\n\r\n<span class=\"hljs-comment\"># \u4eceNumpy\u6570\u7ec4\u521b\u5efa\u5f20\u91cf<\/span>\r\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\r\nnumpy_array = np.array([<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>])\r\nnumpy_tensor = torch.from_numpy(numpy_array)\r\n<\/code><\/pre>\n<ol>\n<li>\u30c6\u30f3\u30bd\u30eb\u306e\u64cd\u4f5c\uff1a<\/li>\n<\/ol>\n<pre class=\"post-pre\"><code><span class=\"hljs-comment\"># \u5f20\u91cf\u7684\u52a0\u6cd5<\/span>\r\ntensor1 = torch.tensor([<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>])\r\ntensor2 = torch.tensor([<span class=\"hljs-number\">4<\/span>, <span class=\"hljs-number\">5<\/span>, <span class=\"hljs-number\">6<\/span>])\r\nresult = tensor1 + tensor2\r\n\r\n<span class=\"hljs-comment\"># \u5f20\u91cf\u7684\u4e58\u6cd5<\/span>\r\nresult = tensor1 * tensor2\r\n\r\n<span class=\"hljs-comment\"># \u5f20\u91cf\u7684\u7d22\u5f15\u548c\u5207\u7247<\/span>\r\ntensor = torch.tensor([[<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">3<\/span>], [<span class=\"hljs-number\">4<\/span>, <span class=\"hljs-number\">5<\/span>, <span class=\"hljs-number\">6<\/span>]])\r\n<span class=\"hljs-built_in\">print<\/span>(tensor[<span class=\"hljs-number\">0<\/span>, <span class=\"hljs-number\">1<\/span>])  <span class=\"hljs-comment\"># \u8f93\u51fa 2<\/span>\r\n<span class=\"hljs-built_in\">print<\/span>(tensor[:, <span class=\"hljs-number\">1<\/span>])  <span class=\"hljs-comment\"># \u8f93\u51fa [2, 5]<\/span>\r\n\r\n<span class=\"hljs-comment\"># \u5f20\u91cf\u7684\u5f62\u72b6\u53d8\u6362<\/span>\r\ntensor = torch.tensor([[<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>], [<span class=\"hljs-number\">3<\/span>, <span class=\"hljs-number\">4<\/span>]])\r\nreshaped_tensor = tensor.view(<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">4<\/span>)\r\n\r\n<span class=\"hljs-comment\"># \u5f20\u91cf\u7684\u8f6c\u7f6e<\/span>\r\ntensor = torch.tensor([[<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>], [<span class=\"hljs-number\">3<\/span>, <span class=\"hljs-number\">4<\/span>]])\r\ntransposed_tensor = tensor.t()\r\n\r\n<span class=\"hljs-comment\"># \u5f20\u91cf\u7684\u6c42\u548c\u548c\u5e73\u5747\u503c<\/span>\r\ntensor = torch.tensor([[<span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>], [<span class=\"hljs-number\">3<\/span>, <span class=\"hljs-number\">4<\/span>]])\r\nsum_tensor = torch.<span class=\"hljs-built_in\">sum<\/span>(tensor)\r\nmean_tensor = torch.mean(tensor)\r\n<\/code><\/pre>\n<p>\u3053\u308c\u3089\u306f\u30c6\u30f3\u30bd\u30eb\u3092\u4f5c\u6210\u304a\u3088\u3073\u64cd\u4f5c\u3059\u308b\u305f\u3081\u306e\u4e00\u822c\u7684\u306a\u65b9\u6cd5\u3067\u3059\u304c\u3001PyTorch\u306b\u306f\u30c6\u30f3\u30bd\u30eb\u3092\u51e6\u7406\u3059\u308b\u305f\u3081\u306e\u591a\u304f\u306e\u4ed6\u306e\u6a5f\u80fd\u3082\u7528\u610f\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u8a73\u7d30\u306a\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u306fPyTorch\u516c\u5f0f\u30a6\u30a7\u30d6\u30b5\u30a4\u30c8\u3067\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"<p>PyTorch\u3067\u30c6\u30f3\u30bd\u30eb\u3092\u4f5c\u6210\u3057\u3066\u64cd\u4f5c\u3059\u308b\u306b\u306f\u3001\u307e\u305atorch\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30dd\u30fc\u30c8\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u4e00\u822c\u7684\u306a\u30c6\u30f3\u30bd\u30eb\u306e\u4f5c\u6210\u3068\u64cd\u4f5c\u65b9\u6cd5\u306e\u3044\u304f\u3064\u304b\u3067\u3059\uff1a \u30c6\u30f3\u30bd\u30eb\u306e\u751f\u6210: import torch # \u521b\u5efa\u4e00\u4e2a\u7a7a\u7684 [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[26,61],"class_list":["post-4365","post","type-post","status-publish","format-standard","hentry","category-uncategorized","tag-26","tag-61"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.5 (Yoast SEO v21.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>PyTorch\u3067\u30c6\u30f3\u30bd\u30eb\u3092\u4f5c\u6210\u3057\u3066\u64cd\u4f5c\u3059\u308b\u65b9\u6cd5\u306f\u4f55\u3067\u3059\u304b\uff1f - Blog - Silicon Cloud<\/title>\n<meta name=\"description\" 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