{"id":14974,"date":"2024-01-07T03:25:08","date_gmt":"2024-01-06T23:55:08","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/"},"modified":"2024-01-07T03:25:08","modified_gmt":"2024-01-06T23:55:08","slug":"%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/","title":{"rendered":"\u0628\u0627 PyTorch \u0622\u0631\u0627\u06cc\u0647 Numpy \u0631\u0627 \u0628\u0647 Tensor \u0648 Tensor \u0631\u0627 \u0628\u0647 Numpy Array \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u062f"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\"><p class=\"ez-toc-title\" style=\"cursor:inherit\">\u0633\u0631\u0641\u0635\u0644\u0647\u0627\u06cc \u0645\u0637\u0644\u0628<\/p>\n<\/div><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#%d8%aa%d8%a8%d8%af%db%8c%d9%84_numpy_array_%d8%a8%d9%87_pytorch_tensor\" >\u062a\u0628\u062f\u06cc\u0644 Numpy Array \u0628\u0647 PyTorch Tensor<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#numpy_array_%d8%a8%d9%87_pytorch_tensor_%d8%a8%d8%a7_dtype\" >Numpy Array \u0628\u0647 PyTorch Tensor \u0628\u0627 dtype<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#%d8%aa%d8%a7%d9%86%d8%b3%d9%88%d8%b1_pytorch_%d8%b1%d8%a7_%d8%a8%d9%87_numpy_array_%d8%aa%d8%a8%d8%af%db%8c%d9%84_%da%a9%d9%86%db%8c%d8%af\" >\u062a\u0627\u0646\u0633\u0648\u0631 PyTorch \u0631\u0627 \u0628\u0647 Numpy Array \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u062f<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#cpu_pytorch_tensor_-%3e_cpu_numpy_array\" >CPU PyTorch Tensor -> CPU Numpy Array<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#cpu_pytorch_tensor_%d8%a8%d8%a7_%da%af%d8%b1%d8%a7%d8%af%db%8c%d8%a7%d9%86_-%3e_cpu_numpy_array\" >CPU PyTorch Tensor \u0628\u0627 \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 -> CPU Numpy Array<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#gpu_pytorch_tensor_-%3e_cpu_numpy_array\" >GPU PyTorch Tensor -> CPU Numpy Array<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/rasanegaar.com\/blog\/%d8%a8%d8%a7-pytorch-%d8%a2%d8%b1%d8%a7%db%8c%d9%87-numpy-%d8%b1%d8%a7-%d8%a8%d9%87-tensor-%d9%88-tensor-%d8%b1%d8%a7-%d8%a8%d9%87-numpy-array-%d8%aa%d8%a8%d8%af%db%8c%d9%84-%da%a9%d9%86%db%8c%d8%af\/#%d9%86%d8%aa%db%8c%d8%ac%d9%87\" >\u0646\u062a\u06cc\u062c\u0647<\/a><\/li><\/ul><\/nav><\/div>\n<span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 4<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span><p> <br \/>\n<\/p>\n<div><noscript><\/noscript><\/p>\n<p><strong><em>\u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627<\/em><\/strong>  \u0627\u0634\u06cc\u0627\u0621 \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0648 \u0628\u0644\u0648\u06a9 \u0646\u0645\u0627\u06cc\u0634 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0636\u0631\u0648\u0631\u06cc \u0686\u0627\u0631\u0686\u0648\u0628 \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0645\u0627\u0646\u0646\u062f TensorFlow \u0648 PyTorch \u0647\u0633\u062a\u0646\u062f.<\/p>\n<p>\u0622 <em>\u0627\u0633\u06a9\u0627\u0644\u0631<\/em> \u062f\u0627\u0631\u0627\u06cc \u0627\u0628\u0639\u0627\u062f \u0635\u0641\u0631 \u0627\u0633\u062a\u060c a <em>\u0628\u0631\u062f\u0627\u0631<\/em> \u06cc\u06a9 \u0628\u0639\u062f \u062f\u0627\u0631\u062f\u060c \u0627\u0644\u0641 <em>\u0645\u0627\u062a\u0631\u06cc\u0633<\/em> \u062f\u0627\u0631\u0627\u06cc \u062f\u0648 \u0628\u0639\u062f \u0648 <em>\u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627<\/em> \u0633\u0647 \u06cc\u0627 \u0628\u06cc\u0634\u062a\u0631 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u0646\u062f.  \u062f\u0631 \u0639\u0645\u0644\u060c \u0645\u0627 \u0627\u063a\u0644\u0628 \u0628\u0647 <em>\u0627\u0633\u06a9\u0627\u0644\u0631\u0647\u0627<\/em> \u0648 <em>\u0628\u0631\u062f\u0627\u0631\u0647\u0627<\/em> \u0648 <em>\u0645\u0627\u062a\u0631\u06cc\u0633 \u0647\u0627<\/em> \u0645\u0627\u0646\u0646\u062f <em>\u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627<\/em> \u0648 \u0647\u0645\u0686\u0646\u06cc\u0646 \u0628\u0631\u0627\u06cc \u0631\u0627\u062d\u062a\u06cc.<\/p>\n<div class=\"alert alert-note\">\n<div class=\"flex\">\n<div class=\"flex-shrink-0 mr-3\"><\/div>\n<div class=\"w-full\">\n<p><strong>\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f:<\/strong> \u0622 <em>\u062a\u0627\u0646\u0633\u0648\u0631<\/em> \u0647\u0645\u0686\u0646\u06cc\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0647\u0631 <em>\u0622\u0631\u0627\u06cc\u0647 n \u0628\u0639\u062f\u06cc<\/em>\u060c \u062f\u0631\u0633\u062a \u0645\u0627\u0646\u0646\u062f \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 Numpy.  \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0641\u0631\u06cc\u0645 \u0648\u0631\u06a9 \u0647\u0627 \u0628\u0631\u0627\u06cc \u06a9\u0627\u0631 \u0628\u0627 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc Numpy \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0645\u06cc \u06a9\u0646\u0646\u062f \u0648 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0622\u0646\u0647\u0627 \u0633\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 \u0627\u0646\u062f \u0631\u0648\u06cc \u0628\u0627\u0644\u0627\u06cc Numpy \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0627\u062f\u063a\u0627\u0645 \u0647\u0645 \u0637\u0628\u06cc\u0639\u06cc \u0648 \u0647\u0645 \u06a9\u0627\u0631\u0622\u0645\u062f \u0627\u0633\u062a.<\/p>\n<\/p><\/div><\/div><\/div>\n<p>\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0627\u0644\u0641 <code>torch.Tensor<\/code> \u0642\u0627\u0628\u0644\u06cc\u062a\u200c\u0647\u0627\u06cc \u062f\u0627\u062e\u0644\u06cc \u0628\u06cc\u0634\u062a\u0631\u06cc \u0646\u0633\u0628\u062a \u0628\u0647 \u0622\u0631\u0627\u06cc\u0647\u200c\u0647\u0627\u06cc Numpy \u062f\u0627\u0631\u062f \u0648 \u0627\u06cc\u0646 \u0642\u0627\u0628\u0644\u06cc\u062a\u200c\u0647\u0627 \u0628\u0631\u0627\u06cc \u0628\u0631\u0646\u0627\u0645\u0647\u200c\u0647\u0627\u06cc Deep Learning (\u0645\u0627\u0646\u0646\u062f \u0634\u062a\u0627\u0628 GPU) \u062a\u0646\u0638\u06cc\u0645 \u0634\u062f\u0647\u200c\u0627\u0646\u062f\u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u062a\u0631\u062c\u06cc\u062d \u062f\u0627\u062f\u0646 \u0622\u0646 \u0645\u0646\u0637\u0642\u06cc \u0627\u0633\u062a. <code>torch.Tensor<\/code> \u0646\u0645\u0648\u0646\u0647 \u0647\u0627\u06cc\u06cc \u0631\u0648\u06cc \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc Numpy \u0645\u0639\u0645\u0648\u0644\u06cc \u0647\u0646\u06af\u0627\u0645 \u06a9\u0627\u0631 \u0628\u0627 PyTorch.  \u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646\u060c <code>torch.Tensor<\/code>\u062f\u0627\u0631\u0627\u06cc \u06cc\u06a9 API \u0628\u0633\u06cc\u0627\u0631 \u0634\u0628\u06cc\u0647 NumPy \u0627\u0633\u062a \u06a9\u0647 \u0622\u0646 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u06a9\u062b\u0631 \u0627\u0641\u0631\u0627\u062f \u0628\u0627 \u062a\u062c\u0631\u0628\u0647 \u0642\u0628\u0644\u06cc \u0628\u0635\u0631\u06cc \u0645\u06cc \u06a9\u0646\u062f!<\/p>\n<blockquote>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0631\u0627\u0647\u0646\u0645\u0627\u060c \u0631\u0648\u0634 \u062a\u0628\u062f\u06cc\u0644 \u0628\u06cc\u0646 Numpy Array \u0648 PyTorch Tensor \u0631\u0627 \u06cc\u0627\u062f \u0628\u06af\u06cc\u0631\u06cc\u062f.<\/p>\n<\/blockquote>\n<h2 id=\"convertnumpyarraytopytorchtensor\"><span class=\"ez-toc-section\" id=\"%d8%aa%d8%a8%d8%af%db%8c%d9%84_numpy_array_%d8%a8%d9%87_pytorch_tensor\"><\/span>\u062a\u0628\u062f\u06cc\u0644 Numpy Array \u0628\u0647 PyTorch Tensor<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0628\u0631\u0627\u06cc \u062a\u0628\u062f\u06cc\u0644 \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 Numpy \u0628\u0647 \u06cc\u06a9 \u062a\u0627\u0646\u0633\u0648\u0631 PyTorch &#8211; \u0645\u0627 \u062f\u0648 \u0631\u0648\u06cc\u06a9\u0631\u062f \u0645\u062a\u0645\u0627\u06cc\u0632 \u062f\u0627\u0631\u06cc\u0645 \u06a9\u0647 \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u0645: \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>from_numpy()<\/code> \u062a\u0627\u0628\u0639\u060c \u06cc\u0627 \u0628\u0647 \u0633\u0627\u062f\u06af\u06cc \u0628\u0627 \u0627\u0631\u0627\u0626\u0647 \u0622\u0631\u0627\u06cc\u0647 Numpy \u0628\u0647 <code>torch.Tensor()<\/code> \u0633\u0627\u0632\u0646\u062f\u0647 <em>\u06cc\u0627<\/em> \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>tensor()<\/code> \u062a\u0627\u0628\u0639:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> torch\n<span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n\nnp_array = np.array((<span class=\"hljs-number\">5<\/span>, <span class=\"hljs-number\">7<\/span>, <span class=\"hljs-number\">1<\/span>, <span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">4<\/span>, <span class=\"hljs-number\">4<\/span>))\n\n\ntensor_a = torch.from_numpy(np_array)\ntensor_b = torch.Tensor(np_array)\ntensor_c = torch.tensor(np_array)\n<\/code><\/pre>\n<p>\u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646\u060c \u0686\u0647 \u062a\u0641\u0627\u0648\u062a\u06cc \u062f\u0627\u0631\u062f\u061f  \u0631\u0627 <code>from_numpy()<\/code> \u0648 <code>tensor()<\/code> \u062a\u0648\u0627\u0628\u0639 \u0647\u0633\u062a\u0646\u062f <code>dtype<\/code>-\u0622\u06af\u0627\u0647!  \u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0645\u0627 \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 Numpy \u0627\u0632 \u0627\u0639\u062f\u0627\u062f \u0635\u062d\u06cc\u062d \u0627\u06cc\u062c\u0627\u062f \u06a9\u0631\u062f\u0647 \u0627\u06cc\u0645\u060c <code>dtype<\/code> \u0627\u0632 \u0639\u0646\u0627\u0635\u0631 \u0632\u06cc\u0631\u0628\u0646\u0627\u06cc\u06cc \u0628\u0647 \u0637\u0648\u0631 \u0637\u0628\u06cc\u0639\u06cc \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f <code>int32<\/code>:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-built_in\">print<\/span>(np_array.dtype)\n\n<\/code><\/pre>\n<p>\u0627\u06af\u0631 \u0642\u0631\u0627\u0631 \u0628\u0648\u062f print \u062f\u0648 \u062a\u0627\u0646\u0633\u0648\u0631 \u0645\u0627 \u0631\u0627 \u0628\u06cc\u0631\u0648\u0646 \u0628\u06cc\u0627\u0648\u0631\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-string\">f'tensor_a: <span class=\"hljs-subst\">{tensor_a}<\/span>\\ntensor_b: <span class=\"hljs-subst\">{tensor_b}<\/span>\\ntensor_c: <span class=\"hljs-subst\">{tensor_c}<\/span>'<\/span>)\n<\/code><\/pre>\n<p><code>tensor_a<\/code>  \u0648 <code>tensor_c<\/code> \u0646\u0648\u0639 \u062f\u0627\u062f\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0634\u062f\u0647 \u062f\u0631 \u0622\u0646 \u0631\u0627 \u062d\u0641\u0638 \u06a9\u0646\u06cc\u062f <code>np_array<\/code>\u060c \u062f\u0631 \u06af\u0648\u0646\u0647 PyTorch (<code>torch.int32<\/code>)\u060c \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 <code>tensor_b<\/code> \u0628\u0647 \u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0645\u0642\u0627\u062f\u06cc\u0631 \u0631\u0627 \u0628\u0647 <em>\u0634\u0646\u0627\u0648\u0631 \u0627\u0633\u062a<\/em>:<\/p>\n<pre><code class=\"hljs\">tensor_a: tensor((5, 7, 1, 2, 4, 4), dtype=torch.int32)\ntensor_b: tensor((5., 7., 1., 2., 4., 4.))\ntensor_c: tensor((5, 7, 1, 2, 4, 4), dtype=torch.int32)\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0628\u0631\u0631\u0633\u06cc \u0622\u0646\u0647\u0627 \u0646\u06cc\u0632 \u0645\u0634\u0627\u0647\u062f\u0647 \u06a9\u0631\u062f <code>dtype<\/code> \u0632\u0645\u06cc\u0646\u0647 \u0647\u0627\u06cc:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-built_in\">print<\/span>(tensor_a.dtype) \n<span class=\"hljs-built_in\">print<\/span>(tensor_b.dtype) \n<span class=\"hljs-built_in\">print<\/span>(tensor_c.dtype) \n<\/code><\/pre>\n<h3 id=\"numpyarraytopytorchtensorwithdtype\"><span class=\"ez-toc-section\" id=\"numpy_array_%d8%a8%d9%87_pytorch_tensor_%d8%a8%d8%a7_dtype\"><\/span>Numpy Array \u0628\u0647 PyTorch Tensor \u0628\u0627 <em>dtype<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0627\u06cc\u0646 \u0631\u0648\u06cc\u06a9\u0631\u062f\u0647\u0627 \u0647\u0645\u0686\u0646\u06cc\u0646 \u062f\u0631 \u0627\u06cc\u0646 \u06a9\u0647 \u0622\u06cc\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0647 \u0635\u0631\u0627\u062d\u062a \u0645\u0648\u0631\u062f \u0646\u0638\u0631 \u0631\u0627 \u062a\u0646\u0638\u06cc\u0645 \u06a9\u0646\u06cc\u062f \u0645\u062a\u0641\u0627\u0648\u062a \u0647\u0633\u062a\u0646\u062f <code>dtype<\/code> \u0686\u0647 \u0632\u0645\u0627\u0646\u06cc <em>\u067e\u062f\u06cc\u062f \u0622\u0648\u0631\u062f\u0646<\/em> \u062a\u0627\u0646\u0633\u0648\u0631 <code>from_numpy()<\/code> \u0648 <code>Tensor()<\/code> \u0627\u0644\u0641 \u0631\u0627 \u0642\u0628\u0648\u0644 \u0646\u06a9\u0646 <code>dtype<\/code> \u0627\u0633\u062a\u062f\u0644\u0627\u0644\u060c \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 <code>tensor()<\/code> \u0645\u06cc\u06a9\u0646\u062f:<\/p>\n<pre><code class=\"hljs\">\ntensor_a = torch.from_numpy(np_array)\n\ntensor_b = torch.Tensor(np_array)\n\ntensor_c = torch.tensor(np_array, dtype=torch.int32)\n\n<span class=\"hljs-built_in\">print<\/span>(tensor_a.dtype) \n<span class=\"hljs-built_in\">print<\/span>(tensor_b.dtype) \n<span class=\"hljs-built_in\">print<\/span>(tensor_c.dtype) \n<\/code><\/pre>\n<p>\u0628\u0647 \u0637\u0648\u0631 \u0637\u0628\u06cc\u0639\u06cc\u060c \u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0647\u0631 \u06cc\u06a9 \u0627\u0632 \u0622\u0646\u0647\u0627 \u0631\u0627 \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0647\u0645\u0627\u0646 \u0646\u062d\u0648 \u0627\u0631\u0633\u0627\u0644 \u06a9\u0646\u06cc\u062f \u0648 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f <code>dtype<\/code> <em>\u0628\u0639\u062f \u0627\u0632<\/em> \u062e\u0644\u0642\u062a \u0646\u06cc\u0632 \u067e\u0633 \u067e\u0630\u06cc\u0631\u0634 \u0627\u0644\u0641 <code>dtype<\/code> \u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u06cc\u06a9 \u0645\u062d\u062f\u0648\u062f\u06cc\u062a \u0646\u06cc\u0633\u062a\u060c \u0628\u0644\u06a9\u0647 \u0628\u06cc\u0634\u062a\u0631 \u06cc\u06a9 \u0631\u0627\u062d\u062a\u06cc \u0627\u0633\u062a:<\/p>\n<pre><code class=\"hljs\">tensor_a = tensor_a.<span class=\"hljs-built_in\">float<\/span>()\ntensor_b = tensor_b.<span class=\"hljs-built_in\">float<\/span>()\ntensor_c = tensor_c.<span class=\"hljs-built_in\">float<\/span>()\n\n<span class=\"hljs-built_in\">print<\/span>(tensor_a.dtype) \n<span class=\"hljs-built_in\">print<\/span>(tensor_b.dtype) \n<span class=\"hljs-built_in\">print<\/span>(tensor_c.dtype) \n<\/code><\/pre>\n<h2 id=\"convertpytorchtensortonumpyarray\"><span class=\"ez-toc-section\" id=\"%d8%aa%d8%a7%d9%86%d8%b3%d9%88%d8%b1_pytorch_%d8%b1%d8%a7_%d8%a8%d9%87_numpy_array_%d8%aa%d8%a8%d8%af%db%8c%d9%84_%da%a9%d9%86%db%8c%d8%af\"><\/span>\u062a\u0627\u0646\u0633\u0648\u0631 PyTorch \u0631\u0627 \u0628\u0647 Numpy Array \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u062f<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062a\u0628\u062f\u06cc\u0644 \u06cc\u06a9 \u062a\u0627\u0646\u0633\u0648\u0631 PyTorch \u0628\u0647 \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 Numpy \u0633\u0627\u062f\u0647 \u0627\u0633\u062a\u060c \u0632\u06cc\u0631\u0627 \u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627 \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a \u0633\u0627\u062e\u062a\u0647 \u0645\u06cc \u0634\u0648\u0646\u062f. \u0631\u0648\u06cc \u0628\u0627\u0644\u0627\u06cc \u0622\u0631\u0627\u06cc\u0647\u200c\u0647\u0627\u06cc Numpy\u060c \u0648 \u062a\u0646\u0647\u0627 \u06a9\u0627\u0631\u06cc \u06a9\u0647 \u0628\u0627\u06cc\u062f \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u0645 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0633\u0627\u062e\u062a\u0627\u0631 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0632\u06cc\u0631\u06cc\u0646 \u0631\u0627 \u00ab\u062f\u0631 \u0645\u0639\u0631\u0636 \u062f\u06cc\u062f\u00bb \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u0645.<\/p>\n<p>\u0627\u0632 \u0622\u0646\u062c\u0627\u06cc\u06cc \u06a9\u0647 PyTorch \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0645\u062d\u0627\u0633\u0628\u0627\u062a \u0627\u0646\u062c\u0627\u0645 \u0634\u062f\u0647 \u0631\u0627 \u0628\u0647\u06cc\u0646\u0647 \u06a9\u0646\u062f \u0631\u0648\u06cc \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u062f\u0627\u062f\u0647 \u0647\u0627 \u0631\u0648\u06cc \u0633\u062e\u062a \u0627\u0641\u0632\u0627\u0631 \u0634\u0645\u0627\u060c \u0647\u0631 \u0686\u0646\u062f \u0686\u0646\u062f \u0646\u06a9\u062a\u0647 \u0648\u062c\u0648\u062f \u062f\u0627\u0631\u062f:<\/p>\n<pre><code class=\"hljs\">tensor = 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>))\n\nnp_a = tensor.numpy()\nnp_b = tensor.detach().numpy()\nnp_c = tensor.detach().cpu().numpy()\n<\/code><\/pre>\n<blockquote>\n<p>\u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646\u060c \u0686\u0631\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f <code>detach()<\/code> \u0648 <code>cpu()<\/code> \u0642\u0628\u0644 \u0627\u0632 \u0627\u0641\u0634\u0627\u06cc \u0633\u0627\u062e\u062a\u0627\u0631 \u062f\u0627\u062f\u0647 \u0632\u06cc\u0631\u0628\u0646\u0627\u06cc\u06cc \u0628\u0627 <code>numpy()<\/code>\u060c \u0648 <em>\u0686\u0647 \u0632\u0645\u0627\u0646\u06cc<\/em> \u0628\u0627\u06cc\u062f \u062c\u062f\u0627\u0634 \u06a9\u0646\u06cc \u0648 \u0628\u0647 \u0633\u06cc \u067e\u06cc \u06cc\u0648 \u0627\u0646\u062a\u0642\u0627\u0644 \u0628\u062f\u06cc\u061f<\/p>\n<\/blockquote>\n<h3 id=\"cpupytorchtensorcpunumpyarray\"><span class=\"ez-toc-section\" id=\"cpu_pytorch_tensor_-%3e_cpu_numpy_array\"><\/span>CPU PyTorch Tensor -> CPU Numpy Array<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0627\u06af\u0631 \u062a\u0627\u0646\u0633\u0648\u0631 \u0634\u0645\u0627 \u0627\u0633\u062a \u0631\u0648\u06cc CPU\u060c \u062c\u0627\u06cc\u06cc \u06a9\u0647 \u0622\u0631\u0627\u06cc\u0647 Numpy \u062c\u062f\u06cc\u062f \u0646\u06cc\u0632 \u062f\u0631 \u0622\u0646 \u0642\u0631\u0627\u0631 \u062e\u0648\u0627\u0647\u062f \u06af\u0631\u0641\u062a &#8211; \u062e\u0648\u0628 \u0627\u0633\u062a \u0641\u0642\u0637 \u0633\u0627\u062e\u062a\u0627\u0631 \u062f\u0627\u062f\u0647 \u0631\u0627 \u062f\u0631 \u0645\u0639\u0631\u0636 \u062f\u06cc\u062f \u0642\u0631\u0627\u0631 \u062f\u0647\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">np_a = tensor.numpy()\n\n<\/code><\/pre>\n<p>\u0627\u06cc\u0646 \u062e\u06cc\u0644\u06cc \u062e\u0648\u0628 \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u062f \u0648 \u0634\u0645\u0627 \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 Numpy \u062a\u0645\u06cc\u0632 \u062f\u0627\u0631\u06cc\u062f.<\/p>\n<h3 id=\"cpupytorchtensorwithgradientscpunumpyarray\"><span class=\"ez-toc-section\" id=\"cpu_pytorch_tensor_%d8%a8%d8%a7_%da%af%d8%b1%d8%a7%d8%af%db%8c%d8%a7%d9%86_-%3e_cpu_numpy_array\"><\/span>CPU PyTorch Tensor \u0628\u0627 \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 -> CPU Numpy Array<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0628\u0627 \u0627\u06cc\u0646 \u062d\u0627\u0644\u060c \u0627\u06af\u0631 \u062a\u0627\u0646\u0633\u0648\u0631 \u0634\u0645\u0627 <em>\u0646\u06cc\u0627\u0632 \u062f\u0627\u0631\u062f<\/em> \u0634\u0645\u0627 \u0628\u0631\u0627\u06cc \u0622\u0646 \u0646\u06cc\u0632 \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u0647\u0627 \u0631\u0627 \u0645\u062d\u0627\u0633\u0628\u0647 \u06a9\u0646\u06cc\u062f (\u06cc\u0639\u0646\u06cc <code>requires_grad<\/code> \u0622\u0631\u06af\u0648\u0645\u0627\u0646 \u062a\u0646\u0638\u06cc\u0645 \u0634\u062f\u0647 \u0627\u0633\u062a <code>True<\/code>)\u060c \u0627\u06cc\u0646 \u0631\u0648\u06cc\u06a9\u0631\u062f \u062f\u06cc\u06af\u0631 \u06a9\u0627\u0631 \u0646\u062e\u0648\u0627\u0647\u062f \u06a9\u0631\u062f.  \u062a\u0648 \u0645\u062c\u0628\u0648\u0631\u06cc <em>\u062c\u062f\u0627 \u06a9\u0631\u062f\u0646<\/em> \u0622\u0631\u0627\u06cc\u0647 \u0632\u06cc\u0631\u06cc\u0646 \u0627\u0632 \u062a\u0627\u0646\u0633\u0648\u0631 \u0648 \u0627\u0632 \u0637\u0631\u06cc\u0642 <em>\u062c\u062f\u0627 \u06a9\u0631\u062f\u0646<\/em>\u060c \u0634\u0645\u0627 \u0634\u06cc\u0628 \u0647\u0627 \u0631\u0627 \u062d\u0630\u0641 \u062e\u0648\u0627\u0647\u06cc\u062f \u06a9\u0631\u062f:<\/p>\n<pre><code class=\"hljs\">tensor = 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>), dtype=torch.float32, requires_grad=<span class=\"hljs-literal\">True<\/span>)\n\nnp_a = tensor.numpy()\n\nnp_b = tensor.detach().numpy()\n\n<\/code><\/pre>\n<h3 id=\"gpupytorchtensorcpunumpyarray\"><span class=\"ez-toc-section\" id=\"gpu_pytorch_tensor_-%3e_cpu_numpy_array\"><\/span>GPU PyTorch Tensor -> CPU Numpy Array<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u062f\u0631 \u0646\u0647\u0627\u06cc\u062a &#8211; \u0627\u06af\u0631 \u062a\u0627\u0646\u0633\u0648\u0631 \u062e\u0648\u062f \u0631\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0631\u062f\u0647 \u0627\u06cc\u062f \u0631\u0648\u06cc GPU\u060c \u0634\u0627\u06cc\u0627\u0646 \u0630\u06a9\u0631 \u0627\u0633\u062a \u06a9\u0647 \u0622\u0631\u0627\u06cc\u0647 \u0647\u0627\u06cc Numpy \u0645\u0639\u0645\u0648\u0644\u06cc \u0627\u0632 \u0634\u062a\u0627\u0628 GPU \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0646\u0645\u06cc \u06a9\u0646\u0646\u062f.  \u0633\u0627\u06a9\u0646 \u0647\u0633\u062a\u0646\u062f \u0631\u0648\u06cc CPU!  \u062a\u0648 \u0645\u062c\u0628\u0648\u0631\u06cc <em>\u0627\u0646\u062a\u0642\u0627\u0644<\/em> \u062a\u0627\u0646\u0633\u0648\u0631 \u0628\u0647 \u06cc\u06a9 CPU\u060c \u0648 <em>\u0633\u067e\u0633<\/em> \u062c\u062f\u0627 \u06a9\u0631\u062f\u0646 \/ \u0627\u0641\u0634\u0627\u06cc \u0633\u0627\u062e\u062a\u0627\u0631 \u062f\u0627\u062f\u0647<\/p>\n<div class=\"alert alert-note\">\n<div class=\"flex\">\n<div class=\"flex-shrink-0 mr-3\"><\/div>\n<div class=\"w-full\">\n<p><strong>\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f:<\/strong> \u0627\u06cc\u0646 \u06a9\u0627\u0631 \u0631\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646 \u0627\u0632 \u0637\u0631\u06cc\u0642 <code>to('cpu')<\/code> \u06cc\u0627 <code>cpu()<\/code> \u062a\u0648\u0627\u0628\u0639 &#8211; \u0622\u0646\u0647\u0627 \u0627\u0632 \u0646\u0638\u0631 \u0639\u0645\u0644\u06a9\u0631\u062f\u06cc \u0645\u0639\u0627\u062f\u0644 \u0647\u0633\u062a\u0646\u062f.<\/p>\n<\/p><\/div><\/div><\/div>\n<p>\u0627\u06cc\u0646 \u0628\u0627\u06cc\u062f \u0628\u0647 \u0635\u0631\u0627\u062d\u062a \u0627\u0646\u062c\u0627\u0645 \u0634\u0648\u062f\u060c \u0632\u06cc\u0631\u0627 \u0627\u06af\u0631 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc \u0634\u062f <em>\u0628\u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631<\/em> &#8211; \u062a\u0628\u062f\u06cc\u0644 \u0628\u06cc\u0646 CPU \u0648 CUDA Tensors \u0628\u0647 \u200b\u200b\u0622\u0631\u0627\u06cc\u0647 \u0647\u0627 \u062f\u0631 \u0632\u06cc\u0631 \u06a9\u0627\u067e\u0648\u062a \u0645\u062a\u0641\u0627\u0648\u062a \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f \u060c \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0645\u0646\u062c\u0631 \u0628\u0647 \u0627\u0634\u06a9\u0627\u0644\u0627\u062a \u063a\u06cc\u0631 \u0645\u0646\u062a\u0638\u0631\u0647 \u062f\u0631 \u062e\u0637 \u0634\u0648\u062f.<\/p>\n<p>PyTorch \u06a9\u0627\u0645\u0644\u0627\u064b \u0648\u0627\u0636\u062d \u0627\u0633\u062a\u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0627\u0632 \u0627\u06cc\u0646 \u0646\u0648\u0639 \u062a\u0628\u062f\u06cc\u0644 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0628\u0647 \u0637\u0648\u0631 \u0647\u062f\u0641\u0645\u0646\u062f \u0627\u062c\u062a\u0646\u0627\u0628 \u0634\u062f:<\/p>\n<pre><code class=\"hljs\">\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>), dtype=torch.float32, requires_grad=<span class=\"hljs-literal\">True<\/span>).cuda()\n\nnp_b = tensor.detach().numpy()\n\nnp_c = tensor.detach().cpu().numpy()\n\n<\/code><\/pre>\n<div class=\"alert alert-note\">\n<div class=\"flex\">\n<div class=\"flex-shrink-0 mr-3\"><\/div>\n<div class=\"w-full\">\n<p><strong>\u062a\u0648\u062c\u0647 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f:<\/strong> \u0628\u0633\u06cc\u0627\u0631 \u062a\u0648\u0635\u06cc\u0647 \u0645\u06cc \u0634\u0648\u062f \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f <code>detach()<\/code> <strong>\u0642\u0628\u0644 \u0627\u0632<\/strong> <code>cpu()<\/code>\u060c \u0628\u0631\u0627\u06cc \u0647\u0631\u0633 \u06a9\u0631\u062f\u0646 \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u0647\u0627 \u0642\u0628\u0644 \u0627\u0632 \u0627\u0646\u062a\u0642\u0627\u0644 \u0622\u0646\u0647\u0627 \u0628\u0647 CPU.  \u0634\u06cc\u0628 \u0647\u0627 \u0628\u0647 \u0647\u0631 \u062d\u0627\u0644 \u0628\u0639\u062f \u0627\u0632 \u0622\u0646 \u0645\u0647\u0645 \u0646\u062e\u0648\u0627\u0647\u0646\u062f \u0628\u0648\u062f <code>detach()<\/code> \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f &#8211; \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u06a9\u067e\u06cc \u06a9\u0631\u062f\u0646 \u0622\u0646\u0647\u0627 \u062f\u0631 <em>\u0647\u0631 \u0646\u0642\u0637\u0647<\/em> \u06a9\u0627\u0645\u0644\u0627 \u0632\u0627\u0626\u062f \u0648 \u0646\u0627\u06a9\u0627\u0631\u0622\u0645\u062f \u0627\u0633\u062a.  \u0628\u0647\u062a\u0631 \u0627\u0633\u062a \u0647\u0631 \u0686\u0647 \u0632\u0648\u062f\u062a\u0631 \u00ab\u0648\u0632\u0646 \u0645\u0631\u062f\u0647\u00bb \u0631\u0627 \u06a9\u0627\u0647\u0634 \u062f\u0647\u06cc\u062f.<\/p>\n<\/p><\/div><\/div><\/div>\n<p>\u0628\u0647 \u0637\u0648\u0631 \u06a9\u0644\u06cc &#8211; \u0627\u06cc\u0646 \u0631\u0648\u0634 \u0627\u06cc\u0645\u0646 \u062a\u0631\u06cc\u0646 \u0627\u0633\u062a\u060c \u0632\u06cc\u0631\u0627 \u0645\u0647\u0645 \u0646\u06cc\u0633\u062a \u06a9\u0647 \u0627\u0632 \u0686\u0647 \u0646\u0648\u0639 \u062a\u0627\u0646\u0633\u0648\u0631\u06cc \u06a9\u0627\u0631 \u0645\u06cc \u06a9\u0646\u06cc\u062f &#8211; \u0634\u06a9\u0633\u062a \u0646\u0645\u06cc \u062e\u0648\u0631\u062f.  \u0627\u06af\u0631 \u06cc\u06a9 \u062a\u0627\u0646\u0633\u0648\u0631 CPU \u062f\u0627\u0631\u06cc\u062f \u0648 \u0633\u0639\u06cc \u0645\u06cc \u06a9\u0646\u06cc\u062f \u0622\u0646 \u0631\u0627 \u0628\u0647 CPU \u0628\u0641\u0631\u0633\u062a\u06cc\u062f &#8211; \u0647\u06cc\u0686 \u0627\u062a\u0641\u0627\u0642\u06cc \u0646\u0645\u06cc \u0627\u0641\u062a\u062f.  \u0627\u06af\u0631 \u06cc\u06a9 \u062a\u0627\u0646\u0633\u0648\u0631 \u0628\u062f\u0648\u0646 \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u062f\u0627\u0631\u06cc\u062f \u0648 \u0633\u0639\u06cc \u06a9\u0646\u06cc\u062f \u0622\u0646 \u0631\u0627 \u062c\u062f\u0627 \u06a9\u0646\u06cc\u062f &#8211; \u0647\u06cc\u0686 \u0627\u062a\u0641\u0627\u0642\u06cc \u0646\u0645\u06cc \u0627\u0641\u062a\u062f.  \u062f\u0631 \u0627\u0646\u062a\u0647\u0627\u06cc \u062f\u06cc\u06af\u0631 \u0686\u0648\u0628 &#8211; \u0627\u0633\u062a\u062b\u0646\u0627\u0647\u0627 \u067e\u0631\u062a\u0627\u0628 \u0645\u06cc \u0634\u0648\u0646\u062f.<\/p>\n<h2 id=\"conclusion\"><span class=\"ez-toc-section\" id=\"%d9%86%d8%aa%db%8c%d8%ac%d9%87\"><\/span>\u0646\u062a\u06cc\u062c\u0647<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062f\u0631 \u0627\u06cc\u0646 \u0631\u0627\u0647\u0646\u0645\u0627 &#8211; \u0642\u0628\u0644 \u0627\u0632 \u0628\u0631\u0631\u0633\u06cc \u0631\u0648\u0634 \u062a\u0628\u062f\u06cc\u0644 \u06cc\u06a9 \u0622\u0631\u0627\u06cc\u0647 Numpy \u0628\u0647 \u06cc\u06a9 \u062a\u0627\u0646\u0633\u0648\u0631 PyTorch\u060c \u0646\u06af\u0627\u0647\u06cc \u0628\u0647 \u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627\u06cc PyTorch \u0627\u0646\u062f\u0627\u062e\u062a\u0647\u200c\u0627\u06cc\u0645.  \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a\u060c \u0645\u0627 \u0628\u0631\u0631\u0633\u06cc \u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u0645 \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627\u06cc PyTorch \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u0646\u062f \u0622\u0631\u0627\u06cc\u0647 Numpy \u0632\u06cc\u0631\u0628\u0646\u0627\u06cc\u06cc \u0631\u0627 \u0646\u0634\u0627\u0646 \u062f\u0647\u0646\u062f\u060c \u0648 \u062f\u0631 \u0686\u0647 \u0645\u0648\u0627\u0631\u062f\u06cc \u0628\u0627\u06cc\u062f \u0627\u0646\u062a\u0642\u0627\u0644\u200c\u0647\u0627 \u0648 \u0647\u0631\u0633\u200c\u0647\u0627\u06cc \u0627\u0636\u0627\u0641\u06cc \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u062f.<\/p>\n<\/div>\n<p><script>\n                        !function(f,b,e,v,n,t,s)\n                        {if(f.fbq)return;n=f.fbq=function(){n.callMethod?\n                        n.callMethod.apply(n,arguments):n.queue.push(arguments)};\n                        if(!f._fbq)f._fbq=n;n.push=n;n.loaded=!0;n.version='2.0';\n                        n.queue=();t=b.createElement(e);t.async=!0;\n                        t.src=v;s=b.getElementsByTagName(e)(0);\n                        s.parentNode.insertBefore(t,s)}(window, document,'script',\n                        'https:\/\/connect.facebook.net\/en_US\/fbevents.js');\n                        fbq('init', '525232124909042');\n                        fbq('track', 'PageView');\n                    <\/script>    (\u0628\u0631\u0686\u0633\u0628\u200c\u0647\u0627 \u0628\u0647 \u062a\u0631\u062c\u0645\u0647)# python<br \/>\n<br \/><br \/>\n<br \/>\u0645\u0646\u062a\u0634\u0631 \u0634\u062f\u0647 \u062f\u0631 1403-01-07 03:25:03<br \/>\n<\/p>\n\n\n<div class=\"kk-star-ratings kksr-auto kksr-align-center kksr-valign-bottom\"\n    data-payload='{&quot;align&quot;:&quot;center&quot;,&quot;id&quot;:&quot;14974&quot;,&quot;slug&quot;:&quot;default&quot;,&quot;valign&quot;:&quot;bottom&quot;,&quot;ignore&quot;:&quot;&quot;,&quot;reference&quot;:&quot;auto&quot;,&quot;class&quot;:&quot;&quot;,&quot;count&quot;:&quot;0&quot;,&quot;legendonly&quot;:&quot;&quot;,&quot;readonly&quot;:&quot;&quot;,&quot;score&quot;:&quot;0&quot;,&quot;starsonly&quot;:&quot;&quot;,&quot;best&quot;:&quot;5&quot;,&quot;gap&quot;:&quot;5&quot;,&quot;greet&quot;:&quot;\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628&quot;,&quot;legend&quot;:&quot;0\\\/5 (0 \u0631\u0627\u06cc)&quot;,&quot;size&quot;:&quot;30&quot;,&quot;title&quot;:&quot;\u0628\u0627 PyTorch \u0622\u0631\u0627\u06cc\u0647 Numpy \u0631\u0627 \u0628\u0647 Tensor \u0648 Tensor \u0631\u0627 \u0628\u0647 Numpy Array \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u062f&quot;,&quot;width&quot;:&quot;0&quot;,&quot;_legend&quot;:&quot;{score}\\\/{best} ({count} \u0631\u0627\u06cc)&quot;,&quot;font_factor&quot;:&quot;1.25&quot;}'>\n            \n<div class=\"kksr-stars\">\n    \n<div class=\"kksr-stars-inactive\">\n            <div class=\"kksr-star\" data-star=\"1\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"2\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"3\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"4\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" data-star=\"5\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n    \n<div class=\"kksr-stars-active\" style=\"width: 0px;\">\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n            <div class=\"kksr-star\" style=\"padding-left: 5px\">\n            \n\n<div class=\"kksr-icon\" style=\"width: 30px; height: 30px;\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n                \n\n<div class=\"kksr-legend\" style=\"font-size: 24px;\">\n            <span class=\"kksr-muted\">\u0627\u0645\u062a\u06cc\u0627\u0632 \u0634\u0645\u0627 \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0637\u0644\u0628<\/span>\n    <\/div>\n    <\/div>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">\u0632\u0645\u0627\u0646 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u0645\u0637\u0627\u0644\u0639\u0647: <\/span> <span class=\"rt-time\"> 4<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span>\u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627 \u0627\u0634\u06cc\u0627\u0621 \u0686\u0646\u062f \u0628\u0639\u062f\u06cc \u0648 \u0628\u0644\u0648\u06a9 \u0646\u0645\u0627\u06cc\u0634 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0636\u0631\u0648\u0631\u06cc \u0686\u0627\u0631\u0686\u0648\u0628 \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0645\u0627\u0646\u0646\u062f TensorFlow \u0648 PyTorch \u0647\u0633\u062a\u0646\u062f. \u0622 \u0627\u0633\u06a9\u0627\u0644\u0631 \u062f\u0627\u0631\u0627\u06cc \u0627\u0628\u0639\u0627\u062f \u0635\u0641\u0631 \u0627\u0633\u062a\u060c a \u0628\u0631\u062f\u0627\u0631 \u06cc\u06a9 \u0628\u0639\u062f \u062f\u0627\u0631\u062f\u060c \u0627\u0644\u0641 \u0645\u0627\u062a\u0631\u06cc\u0633 \u062f\u0627\u0631\u0627\u06cc \u062f\u0648 \u0628\u0639\u062f \u0648 \u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627 \u0633\u0647 \u06cc\u0627 \u0628\u06cc\u0634\u062a\u0631 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u0646\u062f. \u062f\u0631 \u0639\u0645\u0644\u060c \u0645\u0627 \u0627\u063a\u0644\u0628 \u0628\u0647 \u0627\u0633\u06a9\u0627\u0644\u0631\u0647\u0627 \u0648 \u0628\u0631\u062f\u0627\u0631\u0647\u0627 \u0648 \u0645\u0627\u062a\u0631\u06cc\u0633 \u0647\u0627 \u0645\u0627\u0646\u0646\u062f \u062a\u0627\u0646\u0633\u0648\u0631\u0647\u0627 [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":9162,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1743,620],"tags":[],"class_list":["post-14974","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","category-programming"],"acf":[],"_links":{"self":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/14974","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/comments?post=14974"}],"version-history":[{"count":0,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/14974\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media\/9162"}],"wp:attachment":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media?parent=14974"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/categories?post=14974"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/tags?post=14974"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}