{"id":15762,"date":"2024-01-16T20:25:12","date_gmt":"2024-01-16T16:55:12","guid":{"rendered":"https:\/\/rasanegar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/"},"modified":"2024-01-16T20:25:12","modified_gmt":"2024-01-16T16:55:12","slug":"%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f","status":"publish","type":"post","link":"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/","title":{"rendered":"\u0686\u0647 \u0686\u06cc\u0632\u06cc \u062f\u0631 Tensorflow 2.0 \u062c\u062f\u06cc\u062f \u0627\u0633\u062a\u061f"},"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\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#%d9%85%d8%b9%d8%b1%d9%81%db%8c\" >\u0645\u0639\u0631\u0641\u06cc<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#tensorflow_1x\" >TensorFlow 1.x<\/a><\/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\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#%d8%a7%d8%b9%d9%84%d8%a7%d9%85_tensorflow_20\" >\u0627\u0639\u0644\u0627\u0645 Tensorflow 2.0<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#%d8%aa%d8%a7%d8%b2%d9%87_%d9%87%d8%a7%db%8c_tensorflow_20\" >\u062a\u0627\u0632\u0647 \u0647\u0627\u06cc Tensorflow 2.0<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#1_%d8%a7%d8%b3%d8%aa%d9%82%d8%b1%d8%a7%d8%b1_%d9%85%d8%af%d9%84_%d9%87%d8%a7_%d8%b1%d9%88%db%8c_%d9%be%d9%84%d8%aa%d9%81%d8%b1%d9%85_%d9%87%d8%a7%db%8c_%d9%85%d8%aa%d8%b9%d8%af%d8%af\" >1. \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0645\u062f\u0644 \u0647\u0627 \u0631\u0648\u06cc \u067e\u0644\u062a\u0641\u0631\u0645 \u0647\u0627\u06cc \u0645\u062a\u0639\u062f\u062f<\/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\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#2_%d8%a7%d8%b9%d8%af%d8%a7%d9%85_%d9%85%d8%b4%d8%aa%d8%a7%d9%82\" >2. \u0627\u0639\u062f\u0627\u0645 \u0645\u0634\u062a\u0627\u0642<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#3_%d8%a7%d8%af%d8%ba%d8%a7%d9%85_keras_%d8%a8%d8%a7_tensorflow\" >3. \u0627\u062f\u063a\u0627\u0645 Keras \u0628\u0627 Tensorflow<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#4_tffunction_%d8%af%da%a9%d9%88%d8%b1%d8%a7%d8%aa%d9%88%d8%b1\" >4. tf.function \u062f\u06a9\u0648\u0631\u0627\u062a\u0648\u0631<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#5_%d8%a2%d9%85%d9%88%d8%b2%d8%b4_%d8%a8%d8%a7_%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%85%d8%ad%d8%a7%d8%b3%d8%a8%d8%a7%d8%aa_%d8%aa%d9%88%d8%b2%db%8c%d8%b9_%d8%b4%d8%af%d9%87\" >5. \u0622\u0645\u0648\u0632\u0634 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u062d\u0627\u0633\u0628\u0627\u062a \u062a\u0648\u0632\u06cc\u0639 \u0634\u062f\u0647<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#6_tfdata_%d9%88_%d9%85%d8%ac%d9%85%d9%88%d8%b9%d9%87_%d8%af%d8%a7%d8%af%d9%87_%d9%87%d8%a7\" >6. tf.data \u0648 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#7_tfkerasmodel\" >7. tf.keras.Model<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#8_tfgradienttape\" >8. tf.GradientTape<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/rasanegaar.com\/blog\/%da%86%d9%87-%da%86%db%8c%d8%b2%db%8c-%d8%af%d8%b1-tensorflow-2-0-%d8%ac%d8%af%db%8c%d8%af-%d8%a7%d8%b3%d8%aa%d8%9f\/#%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\"> 7<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span><p> <br \/>\n<\/p>\n<div><noscript><\/noscript><\/p>\n<h2 id=\"introduction\"><span class=\"ez-toc-section\" id=\"%d9%85%d8%b9%d8%b1%d9%81%db%8c\"><\/span>\u0645\u0639\u0631\u0641\u06cc<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0627\u06af\u0631 \u0634\u0645\u0627 \u06cc\u06a9 \u0645\u0647\u0646\u062f\u0633 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u060c \u062f\u0627\u0646\u0634\u0645\u0646\u062f \u062f\u0627\u062f\u0647 \u06cc\u0627 \u0639\u0644\u0627\u0642\u0647\u200c\u0645\u0646\u062f\u06cc \u0647\u0633\u062a\u06cc\u062f \u06a9\u0647 \u0647\u0631 \u0627\u0632 \u06af\u0627\u0647\u06cc \u0628\u0631\u0627\u06cc \u0633\u0631\u06af\u0631\u0645\u06cc \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0631\u0627 \u062a\u0648\u0633\u0639\u0647 \u0645\u06cc\u200c\u062f\u0647\u062f\u060c \u0627\u062d\u062a\u0645\u0627\u0644\u0627\u064b \u0628\u0627 Tensorflow \u0622\u0634\u0646\u0627 \u0647\u0633\u062a\u06cc\u062f.<\/p>\n<p>Tensorflow \u06cc\u06a9 \u0686\u0627\u0631\u0686\u0648\u0628 \u0645\u062a\u0646 \u0628\u0627\u0632 \u0648 \u0631\u0627\u06cc\u06af\u0627\u0646 \u0627\u0633\u062a \u06a9\u0647 \u062a\u0648\u0633\u0637 Google Brain Team \u0646\u0648\u0634\u062a\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a \u0648 \u0628\u0647 \u0632\u0628\u0627\u0646 \u0647\u0627\u06cc Python\u060c C++ \u0648 CUDA \u0646\u0648\u0634\u062a\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a.  \u0628\u0631\u0627\u06cc \u062a\u0648\u0633\u0639\u0647\u060c \u0622\u0632\u0645\u0627\u06cc\u0634 \u0648 \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/p>\n<p>\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 TensorFlow \u0627\u0632 \u0686\u0646\u062f\u06cc\u0646 \u067e\u0644\u062a\u0641\u0631\u0645 \u0648 \u0632\u0628\u0627\u0646 \u0647\u0627\u06cc \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u06a9\u0627\u0645\u0644 \u0646\u062f\u0627\u0634\u062a \u0648 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc \u062e\u06cc\u0644\u06cc \u0633\u0631\u06cc\u0639 \u0648 \u06a9\u0627\u0631\u0622\u0645\u062f \u0646\u0628\u0648\u062f\u060c \u0627\u0645\u0627 \u0628\u0627 \u06af\u0630\u0634\u062a \u0632\u0645\u0627\u0646 \u0648 \u067e\u0633 \u0627\u0632 \u0686\u0646\u062f \u0628\u0647 \u0631\u0648\u0632 \u0631\u0633\u0627\u0646\u06cc\u060c Tensorflow \u0627\u06a9\u0646\u0648\u0646 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0686\u0627\u0631\u0686\u0648\u0628\u06cc \u0628\u0631\u0627\u06cc \u062a\u0648\u0633\u0639\u0647 \u062f\u0631 \u0646\u0638\u0631 \u06af\u0631\u0641\u062a\u0647 \u0645\u06cc \u0634\u0648\u062f. \u060c \u0622\u0645\u0648\u0632\u0634 \u0648 \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0645\u062f\u0644 \u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u06cc.<\/p>\n<h2 id=\"tensorflow1x\"><span class=\"ez-toc-section\" id=\"tensorflow_1x\"><\/span>TensorFlow 1.x<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Tensorflow 1.x \u0646\u06cc\u0632 \u06cc\u06a9 \u062c\u0647\u0634 \u0628\u0632\u0631\u06af \u0628\u0631\u0627\u06cc \u0627\u06cc\u0646 \u0686\u0627\u0631\u0686\u0648\u0628 \u0628\u0648\u062f.  \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u062c\u062f\u06cc\u062f\u060c \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647\u0628\u0648\u062f \u06cc\u0627\u0641\u062a\u0647 \u0648 \u0645\u0634\u0627\u0631\u06a9\u062a \u0647\u0627\u06cc \u0645\u0646\u0628\u0639 \u0628\u0627\u0632 \u0631\u0627 \u0645\u0639\u0631\u0641\u06cc \u06a9\u0631\u062f.  \u0627\u06cc\u0646 API \u0633\u0637\u062d \u0628\u0627\u0644\u0627\u06cc\u06cc \u0631\u0627 \u0628\u0631\u0627\u06cc TensorFlow \u0645\u0639\u0631\u0641\u06cc \u06a9\u0631\u062f \u06a9\u0647 \u0633\u0627\u062e\u062a \u0646\u0645\u0648\u0646\u0647 \u0647\u0627\u06cc \u0627\u0648\u0644\u06cc\u0647 \u0631\u0627 \u062f\u0631 \u06a9\u0645\u062a\u0631\u06cc\u0646 \u0632\u0645\u0627\u0646 \u0628\u0633\u06cc\u0627\u0631 \u0622\u0633\u0627\u0646 \u06a9\u0631\u062f.<\/p>\n<p>\u0628\u0627 Keras \u0633\u0627\u0632\u06af\u0627\u0631 \u0633\u0627\u062e\u062a\u0647 \u0634\u062f.  \u0627\u0645\u0627 \u0646\u06a9\u062a\u0647 \u0627\u0635\u0644\u06cc \u06a9\u0647 \u062a\u0648\u0633\u0639\u0647\u200c\u062f\u0647\u0646\u062f\u06af\u0627\u0646 \u0631\u0627 \u0622\u0632\u0627\u0631 \u0645\u06cc\u200c\u062f\u0647\u062f \u0627\u06cc\u0646 \u0628\u0648\u062f \u06a9\u0647 \u0647\u0646\u06af\u0627\u0645 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 TensorFlow \u062a\u0645\u0627\u06cc\u0644\u06cc \u0628\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0633\u0627\u062f\u06af\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0646\u062f\u0627\u0634\u062a\u0646\u062f.<\/p>\n<p>\u062f\u0631 TensorFlow\u060c \u0647\u0631 \u0645\u062f\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u06cc\u06a9 \u0646\u0645\u0648\u062f\u0627\u0631 \u0646\u0645\u0627\u06cc\u0634 \u062f\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f \u0648 \u06af\u0631\u0647 \u0647\u0627 \u0645\u062d\u0627\u0633\u0628\u0627\u062a \u0645\u0648\u062c\u0648\u062f \u062f\u0631 \u0646\u0645\u0648\u062f\u0627\u0631 \u0631\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u0646\u062f.  \u0646\u0645\u0648\u0646\u0647 \u0627\u06cc \u0627\u0632 \u0622\u0646 \u0627\u0633\u062a <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Symbolic_programming\">&#8220;\u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u0646\u0645\u0627\u062f\u06cc\u0646&#8221;<\/a> \u0648 \u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647 \u067e\u0627\u06cc\u062a\u0648\u0646 \u06cc\u06a9 \u0627\u0633\u062a <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Imperative_programming#:~:text=In%20computer%20science,%20imperative%20programming,for%20the%20computer%20to%20perform\">&#8220;\u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u0636\u0631\u0648\u0631\u06cc&#8221;<\/a> \u0632\u0628\u0627\u0646.<\/p>\n<p>\u0645\u0646 \u0628\u0647 \u062c\u0632\u0626\u06cc\u0627\u062a \u0632\u06cc\u0627\u062f \u0646\u0645\u06cc \u067e\u0631\u062f\u0627\u0632\u0645 \u0632\u06cc\u0631\u0627 \u0627\u06cc\u0646 \u0627\u0632 \u062d\u0648\u0635\u0644\u0647 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062e\u0627\u0631\u062c \u0627\u0633\u062a.  \u0627\u0645\u0627 \u0646\u06a9\u062a\u0647 \u0627\u06cc\u0646\u062c\u0627\u0633\u062a \u06a9\u0647 \u0628\u0627 \u0627\u0646\u062a\u0634\u0627\u0631 PyTorch (\u06a9\u0647 \u0628\u06cc\u0634\u062a\u0631 \u0628\u0647 \u0633\u0645\u062a \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u0627\u0645\u0631\u06cc \u06af\u0631\u0627\u06cc\u0634 \u062f\u0627\u0631\u062f \u0648 \u0627\u0632 \u0631\u0641\u062a\u0627\u0631 \u067e\u0648\u06cc\u0627\u06cc \u067e\u0627\u06cc\u062a\u0648\u0646 \u0628\u0647\u0631\u0647 \u0645\u06cc \u0628\u0631\u062f)\u060c \u062a\u0627\u0632\u0647 \u0648\u0627\u0631\u062f\u0627\u0646 \u0648 \u062f\u0627\u0646\u0634\u0645\u0646\u062f\u0627\u0646 \u062a\u062d\u0642\u06cc\u0642\u0627\u062a\u06cc \u0645\u062a\u0648\u062c\u0647 \u0634\u062f\u0646\u062f \u06a9\u0647 PyTorch \u0631\u0627\u062d\u062a \u062a\u0631 \u0627\u0632 Tensorflow \u0642\u0627\u0628\u0644 \u062f\u0631\u06a9 \u0648 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0627\u0633\u062a \u0648 \u062f\u0631 \u0645\u062f\u062a \u06a9\u0648\u062a\u0627\u0647\u06cc PyTorch \u0645\u062d\u0628\u0648\u0628\u06cc\u062a \u067e\u06cc\u062f\u0627 \u06a9\u0631\u062f. .<\/p>\n<p>\u0647\u0631 \u062a\u0648\u0633\u0639\u0647\u200c\u062f\u0647\u0646\u062f\u0647 \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648 \u0647\u0645\u06cc\u0646 \u0631\u0627 \u0627\u0632 \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648 \u0648 \u062a\u06cc\u0645 \u0645\u063a\u0632 \u06af\u0648\u06af\u0644 \u0645\u06cc\u200c\u062e\u0648\u0627\u0633\u062a.  \u0639\u0644\u0627\u0648\u0647 \u0628\u0631 \u0627\u06cc\u0646\u060c TensorFlow 1.x \u062a\u0648\u0633\u0639\u0647 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0631\u0627 \u067e\u0634\u062a \u0633\u0631 \u06af\u0630\u0627\u0634\u062a \u06a9\u0647 \u0645\u0646\u062c\u0631 \u0628\u0647 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 API\u0647\u0627 \u0634\u062f\u060c \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c <code>tf.layers, tf.contrib.layers, tf.keras<\/code> \u0648 \u062a\u0648\u0633\u0639\u0647 \u062f\u0647\u0646\u062f\u06af\u0627\u0646 \u06af\u0632\u06cc\u0646\u0647 \u0647\u0627\u06cc \u0632\u06cc\u0627\u062f\u06cc \u0628\u0631\u0627\u06cc \u0627\u0646\u062a\u062e\u0627\u0628 \u062f\u0627\u0634\u062a\u0646\u062f \u06a9\u0647 \u0645\u0646\u062c\u0631 \u0628\u0647 \u062f\u0631\u06af\u06cc\u0631\u06cc \u0634\u062f.<\/p>\n<h2 id=\"announcementoftensorflow20\"><span class=\"ez-toc-section\" id=\"%d8%a7%d8%b9%d9%84%d8%a7%d9%85_tensorflow_20\"><\/span>\u0627\u0639\u0644\u0627\u0645 Tensorflow 2.0<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u06a9\u0627\u0645\u0644\u0627\u064b \u0648\u0627\u0636\u062d \u0628\u0648\u062f \u06a9\u0647 \u062a\u06cc\u0645 \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648 \u0628\u0627\u06cc\u062f \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0633\u0627\u0626\u0644 \u0631\u0633\u06cc\u062f\u06af\u06cc \u0645\u06cc \u06a9\u0631\u062f\u060c \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0622\u0646\u0647\u0627 \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648 2.0 \u0631\u0627 \u0645\u0639\u0631\u0641\u06cc \u06a9\u0631\u062f\u0646\u062f.<\/p>\n<p>\u0627\u06cc\u0646 \u06cc\u06a9 \u06af\u0627\u0645 \u0628\u0632\u0631\u06af \u0628\u0648\u062f \u0632\u06cc\u0631\u0627 \u0628\u0631\u0627\u06cc \u0631\u0633\u06cc\u062f\u06af\u06cc \u0628\u0647 \u0647\u0645\u0647 \u0645\u0633\u0627\u0626\u0644 \u0628\u0627\u06cc\u062f \u062a\u063a\u06cc\u06cc\u0631\u0627\u062a \u0628\u0632\u0631\u06af\u06cc \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u06a9\u0631\u062f\u0646\u062f.  \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0645\u0631\u062f\u0645 \u0628\u0627 \u062a\u062c\u0631\u0628\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062f\u06cc\u06af\u0631\u06cc \u0645\u0648\u0627\u062c\u0647 \u0634\u062f\u0646\u062f\u060c \u0627\u0645\u0627 \u067e\u06cc\u0634\u0631\u0641\u062a\u200c\u0647\u0627 \u0628\u0627\u0639\u062b \u0634\u062f \u0627\u0631\u0632\u0634 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u062c\u062f\u062f \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u062f.<\/p>\n<p>\u062f\u0631 \u0645\u0631\u062d\u0644\u0647 \u0622\u0645\u0648\u0632\u0634 \u0628\u0627 \u0645\u0627 \u0622\u0634\u0646\u0627 \u0645\u06cc \u0634\u0648\u06cc\u0645 <code>tf.data<\/code> \u0648 Datasets \u06a9\u0647 \u0628\u0647 \u0645\u0627 \u0627\u062c\u0627\u0632\u0647 \u0645\u06cc \u062f\u0647\u0646\u062f import \u0648 process \u062f\u0627\u062f\u0647 \u0647\u0627 \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc  \u0633\u067e\u0633\u060c \u0628\u0627 \u0622\u0645\u0648\u0632\u0634 \u062a\u0648\u0632\u06cc\u0639 \u0634\u062f\u0647 \u0631\u0648\u06cc \u0686\u0646\u062f\u06cc\u0646 CPU\u060c GPU \u0648 TPU \u0622\u0634\u0646\u0627 \u0645\u06cc \u0634\u0648\u06cc\u0645.  \u0628\u0631\u0627\u06cc \u0633\u0631\u06cc\u0627\u0644 \u0633\u0627\u0632\u06cc \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0627\u0632 <code>SavedModel<\/code> \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u062f\u0631 TensorFlow Hub \u06cc\u0627 \u062e\u062f\u0645\u0627\u062a\u06cc \u0645\u0627\u0646\u0646\u062f TensorFlow Serving\u060c TensorFlow Lite \u06cc\u0627 TensorFlow.js:<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/rasanegar.com\/blog\/wp-content\/uploads\/2024\/01\/whats-new-in-tensorflow-2.png\" alt=\"\u0645\u0639\u0645\u0627\u0631\u06cc tensorflow 2.0\" title=\"\"><\/p>\n<p><small>\u0627\u0639\u062a\u0628\u0627\u0631: <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/blog.tensorflow.org\/2019\/09\/tensorflow-20-is-now-available.html\">blog.tensorflow.org<\/a><\/small><\/p>\n<h2 id=\"whatsnewintensorflow20\"><span class=\"ez-toc-section\" id=\"%d8%aa%d8%a7%d8%b2%d9%87_%d9%87%d8%a7%db%8c_tensorflow_20\"><\/span>\u062a\u0627\u0632\u0647 \u0647\u0627\u06cc Tensorflow 2.0<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0645\u0631\u0648\u0631\u06cc \u06a9\u0648\u062a\u0627\u0647 \u0628\u0631 \u0645\u0647\u0645 \u062a\u0631\u06cc\u0646 \u0628\u0647 \u0631\u0648\u0632 \u0631\u0633\u0627\u0646\u06cc \u0647\u0627\u06cc\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0628\u0627 Tensorflow 2 \u0627\u0631\u0627\u0626\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<h3 id=\"1deployingmodelsonmultipleplatforms\"><span class=\"ez-toc-section\" id=\"1_%d8%a7%d8%b3%d8%aa%d9%82%d8%b1%d8%a7%d8%b1_%d9%85%d8%af%d9%84_%d9%87%d8%a7_%d8%b1%d9%88%db%8c_%d9%be%d9%84%d8%aa%d9%81%d8%b1%d9%85_%d9%87%d8%a7%db%8c_%d9%85%d8%aa%d8%b9%d8%af%d8%af\"><\/span>1. \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0645\u062f\u0644 \u0647\u0627 \u0631\u0648\u06cc \u067e\u0644\u062a\u0641\u0631\u0645 \u0647\u0627\u06cc \u0645\u062a\u0639\u062f\u062f<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Tensorflow \u0647\u0645\u06cc\u0634\u0647 \u0628\u0631\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f \u0628\u0633\u06cc\u0627\u0631 \u0645\u0646\u0627\u0633\u0628 \u0628\u0648\u062f\u060c \u0627\u0645\u0627 Tensorflow 2 \u0633\u0627\u0632\u06af\u0627\u0631\u06cc \u0648 \u0628\u0631\u0627\u0628\u0631\u06cc \u0631\u0627 \u062f\u0631 \u0686\u0646\u062f\u06cc\u0646 \u067e\u0644\u062a\u0641\u0631\u0645 \u0628\u0647\u0628\u0648\u062f \u0628\u062e\u0634\u06cc\u062f.<\/p>\n<p>\u0627\u06cc\u0646 \u067e\u0644\u062a\u0641\u0631\u0645 \u062c\u062f\u06cc\u062f \u0631\u0627 \u0628\u0631\u0627\u06cc \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0645\u0639\u0631\u0641\u06cc \u06a9\u0631\u062f <code>SavedModel<\/code> \u0641\u0631\u0645\u062a\u06cc \u06a9\u0647 \u0628\u0647 \u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0645\u062f\u0644 \u0647\u0627\u06cc \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648 \u0631\u0627 \u0630\u062e\u06cc\u0631\u0647 \u06a9\u0646\u06cc\u0645.  \u0646\u06a9\u062a\u0647 \u062c\u062f\u06cc\u062f \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0645\u062f\u0644 \u0630\u062e\u06cc\u0631\u0647 \u0634\u062f\u0647 \u062e\u0648\u062f \u0631\u0627 \u0645\u0633\u062a\u0642\u0631 \u06a9\u0646\u06cc\u062f \u0631\u0648\u06cc \u0647\u0631 \u067e\u0644\u062a \u0641\u0631\u0645\u060c \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u0645\u062b\u0627\u0644\u060c \u0631\u0648\u06cc \u062f\u0633\u062a\u06af\u0627\u0647 \u0647\u0627\u06cc \u0645\u0648\u0628\u0627\u06cc\u0644 \u06cc\u0627 \u0627\u06cc\u0646\u062a\u0631\u0646\u062a \u0627\u0634\u06cc\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.tensorflow.org\/lite\" class=\"broken_link\">Tensorflow Lite<\/a> \u06cc\u0627 Node.js \u0628\u0627 <a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.tensorflow.org\/js\" class=\"broken_link\">Tensorflow.js<\/a>.  \u0647\u0645\u0686\u0646\u06cc\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0627\u0632 \u0622\u0646 \u062f\u0631 \u0645\u062d\u06cc\u0637 \u0647\u0627\u06cc \u062a\u0648\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.tensorflow.org\/tfx\/guide\/serving\" class=\"broken_link\">\u0633\u0631\u0648\u06cc\u0633 \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648<\/a>.<\/p>\n<p>\u0628\u06cc\u0627\u06cc\u06cc\u062f \u0646\u06af\u0627\u0647\u06cc \u0628\u0647 \u0631\u0648\u0634 \u0630\u062e\u06cc\u0631\u0647 \u06cc\u06a9 \u0645\u062f\u0644 \u06a9\u0627\u0645\u067e\u0627\u06cc\u0644 \u0628\u06cc\u0646\u062f\u0627\u0632\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> os\n<span class=\"hljs-keyword\">import<\/span> tensorflow <span class=\"hljs-keyword\">as<\/span> tf\n\nmodel = tf.keras.Sequential((\n        tf.keras.layers.Dense(<span class=\"hljs-number\">5<\/span>,actiavtion=<span class=\"hljs-string\">'relu'<\/span>,input_shape=(<span class=\"hljs-number\">16<\/span>,)),\n        tf.keras.layers.Dense(<span class=\"hljs-number\">1<\/span>,activation=<span class=\"hljs-string\">'sigmoid'<\/span>)))\n\nmodel.<span class=\"hljs-built_in\">compile<\/span>(loss=<span class=\"hljs-string\">'binary_crossentropy'<\/span>,optimizer=<span class=\"hljs-string\">'adam'<\/span>)\n\n\nsave_path = path + <span class=\"hljs-string\">\"\/version_number\/\"<\/span>\nsave_path = os.path.join\ntf.saved_model.save(model, save_path)\n<\/code><\/pre>\n<p>\u0648 \u0634\u0645\u0627 \u0628\u0631\u0648\u06cc\u062f.  \u0627\u06a9\u0646\u0648\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0622\u0646 \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0647\u0631 \u06cc\u06a9 \u0627\u0632 \u0633\u0631\u0648\u06cc\u0633 \u0647\u0627\u06cc \u0641\u0648\u0642 \u0627\u0644\u0630\u06a9\u0631 \u0645\u0633\u062a\u0642\u0631 \u06a9\u0646\u06cc\u062f.<\/p>\n<h3 id=\"2eagerexecution\"><span class=\"ez-toc-section\" id=\"2_%d8%a7%d8%b9%d8%af%d8%a7%d9%85_%d9%85%d8%b4%d8%aa%d8%a7%d9%82\"><\/span>2. \u0627\u0639\u062f\u0627\u0645 \u0645\u0634\u062a\u0627\u0642<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0642\u0628\u0644 \u0627\u0632 Tensorflow 2\u060c \u0628\u0627\u06cc\u062f \u06cc\u06a9 \u062c\u0644\u0633\u0647 \u0628\u0631\u0627\u06cc \u0627\u062c\u0631\u0627\u06cc \u0645\u062f\u0644 \u062e\u0648\u062f \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc \u06a9\u0631\u062f\u06cc\u062f.  \u062f\u0631 \u0648\u0627\u0642\u0639\u060c \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0633\u062a\u06cc\u062f print \u0645\u0642\u062f\u0627\u0631 \u06cc\u06a9 \u0645\u062a\u063a\u06cc\u0631 \u0641\u0642\u0637 \u0628\u0631\u0627\u06cc \u0627\u0634\u06a9\u0627\u0644 \u0632\u062f\u0627\u06cc\u06cc\u060c \u0627\u0628\u062a\u062f\u0627 \u0628\u0627\u06cc\u062f \u06cc\u06a9 \u062c\u0644\u0633\u0647 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0631\u062f\u0647 \u0648 \u0633\u067e\u0633 a \u0631\u0627 \u0628\u0646\u0648\u06cc\u0633\u06cc\u062f print \u0628\u06cc\u0627\u0646\u06cc\u0647 \u062f\u0627\u062e\u0644 \u0622\u0646 \u062c\u0644\u0633\u0647<\/p>\n<p>\u0628\u0631\u0627\u06cc \u062a\u063a\u0630\u06cc\u0647 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0628\u0647 \u0645\u062f\u0644\u060c \u0628\u0627\u06cc\u062f \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc\u06cc \u06a9\u0646\u062f \u0648 \u0628\u06cc\u200c\u0641\u0627\u06cc\u062f\u0647 \u0627\u06cc\u062c\u0627\u062f \u0645\u06cc\u200c\u06a9\u0631\u062f\u06cc\u062f.  \u0627\u0633\u0627\u0633\u0627\u064b\u060c \u062f\u0631 Tensorflow 1.x\u060c \u0627\u0628\u062a\u062f\u0627 \u06a9\u0644 \u0646\u0645\u0648\u062f\u0627\u0631 \u0631\u0627 \u0645\u06cc\u200c\u0633\u0627\u0632\u06cc\u062f \u0648 \u0633\u067e\u0633 \u0622\u0646 \u0631\u0627 \u0627\u062c\u0631\u0627 \u0645\u06cc\u200c\u06a9\u0646\u06cc\u062f\u060c \u0628\u0631\u062e\u0644\u0627\u0641 \u0633\u0627\u062e\u062a \u0622\u0646. <em>\u062f\u0631 \u062d\u0627\u0644\u06cc \u06a9\u0647<\/em> \u062f\u0631 \u062d\u0627\u0644 \u0627\u062c\u0631\u0627<\/p>\n<p>\u0627\u06cc\u0646 \u0627\u062d\u0633\u0627\u0633 \u0627\u06cc\u0633\u062a\u0627 \u0648 \u0646\u0627\u0647\u0645\u0648\u0627\u0631 \u0628\u0648\u062f\u060c \u0628\u0647 \u062e\u0635\u0648\u0635 \u0628\u0631\u062e\u0644\u0627\u0641 PyTorch\u060c \u06a9\u0647 \u0628\u0647 \u06a9\u0627\u0631\u0628\u0631\u0627\u0646 \u0627\u062c\u0627\u0632\u0647 \u0645\u06cc \u062f\u0627\u062f \u062f\u0631 \u062d\u06cc\u0646 \u0627\u062c\u0631\u0627 \u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627\u06cc \u067e\u0648\u06cc\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u0646\u062f.<\/p>\n<p>\u062e\u0648\u0634\u0628\u062e\u062a\u0627\u0646\u0647\u060c \u0627\u06cc\u0646 \u062f\u0631 Tensorflow 2.0 \u0627\u0635\u0644\u0627\u062d \u0634\u062f \u06a9\u0647 \u0645\u0627 \u0631\u0627 \u0628\u0627 \u0622\u0646 \u0622\u0634\u0646\u0627 \u06a9\u0631\u062f <em>\u0627\u0639\u062f\u0627\u0645 \u0645\u0634\u062a\u0627\u0642\u0627\u0646\u0647<\/em>.  \u0628\u06cc\u0627\u06cc\u06cc\u062f \u0646\u06af\u0627\u0647\u06cc \u0628\u0647 \u0631\u0648\u0634 \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0646\u0645\u0648\u062f\u0627\u0631 \u062f\u0631 Tensorflow 1.x \u062f\u0631 \u0645\u0642\u0627\u0628\u0644 2.0 \u0628\u06cc\u0646\u062f\u0627\u0632\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> tensorflow <span class=\"hljs-keyword\">as<\/span> tf\n\n<span class=\"hljs-string\">\"\"\"Creating the Graph\"\"\"<\/span>\n\n\na = tf.Variable(<span class=\"hljs-number\">4<\/span>)\nb = tf.Variable(<span class=\"hljs-number\">5<\/span>)\nresult = tf.multiply(a,b)\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646 \u0628\u0631\u0627\u06cc \u062f\u0633\u062a\u0631\u0633\u06cc \u0628\u0647 <code>result<\/code> \u0645\u062a\u063a\u06cc\u0631\u060c \u0645\u0627 \u0628\u0627\u06cc\u062f \u0646\u0645\u0648\u062f\u0627\u0631 \u0631\u0627 \u062f\u0631 \u06cc\u06a9 \u062c\u0644\u0633\u0647 \u0627\u062c\u0631\u0627 \u06a9\u0646\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\">\n<span class=\"hljs-keyword\">with<\/span> tf.Session() <span class=\"hljs-keyword\">as<\/span> sess:\n    \n    sess.run(tf.global_variables_initializer())\n    <span class=\"hljs-built_in\">print<\/span>(sess.run(result))\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646\u060c \u0628\u0647 \u062c\u0627\u06cc \u0622\u0646\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0645\u0633\u062a\u0642\u06cc\u0645\u0627\u064b \u0628\u0647 \u0622\u0646\u0647\u0627 \u062f\u0633\u062a\u0631\u0633\u06cc \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> tensorflow <span class=\"hljs-keyword\">as<\/span> tf\n\n\na = tf.Variable(<span class=\"hljs-number\">4<\/span>)\nb = tf.Variable(<span class=\"hljs-number\">5<\/span>)\n\n<span class=\"hljs-built_in\">print<\/span>(<span class=\"hljs-built_in\">float<\/span>(a*b))\n<\/code><\/pre>\n<h3 id=\"3integrationofkeraswithtensorflow\"><span class=\"ez-toc-section\" id=\"3_%d8%a7%d8%af%d8%ba%d8%a7%d9%85_keras_%d8%a8%d8%a7_tensorflow\"><\/span>3. \u0627\u062f\u063a\u0627\u0645 Keras \u0628\u0627 Tensorflow<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Keras \u06cc\u06a9 API \u0634\u0628\u06a9\u0647 \u0639\u0635\u0628\u06cc \u0648 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0639\u0645\u06cc\u0642 \u0627\u0633\u062a \u06a9\u0647 \u0633\u0627\u062e\u062a\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a \u0631\u0648\u06cc \u0628\u0627\u0644\u0627\u06cc \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648<\/p>\n<p>\u0627\u06a9\u062b\u0631 \u0645\u0631\u062f\u0645 \u0642\u0628\u0644 \u0627\u0632 \u062d\u0631\u06a9\u062a \u0628\u0627 Keras \u0634\u0631\u0648\u0639 \u0645\u06cc \u06a9\u0646\u0646\u062f \u0631\u0648\u06cc \u0628\u0647 Tensorflow \u06cc\u0627 PyTorch.  \u0627\u06cc\u0646 \u0628\u0631\u0627\u06cc \u0622\u0632\u0645\u0627\u06cc\u0634 \u0633\u0631\u06cc\u0639 \u0628\u0627 \u0634\u0628\u06a9\u0647 \u0647\u0627\u06cc \u0639\u0635\u0628\u06cc \u0639\u0645\u06cc\u0642 \u0637\u0631\u0627\u062d\u06cc \u0634\u062f\u0647 \u0627\u0633\u062a \u0648 \u0628\u0646\u0627\u0628\u0631\u0627\u06cc\u0646 \u0633\u0627\u062f\u0647 \u062a\u0631 \u0627\u0633\u062a.<\/p>\n<p>\u0642\u0628\u0644 \u0627\u0632 Tensorflow 2.0\u060c \u062a\u0648\u0633\u0637 \u06a9\u062a\u0627\u0628\u062e\u0627\u0646\u0647 \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0645\u06cc \u0634\u062f\u060c \u0627\u0645\u0627 \u0627\u06cc\u0646\u0637\u0648\u0631 \u0646\u0628\u0648\u062f <em>\u06cc\u06a9\u067e\u0627\u0631\u0686\u0647<\/em>.  \u0627\u06a9\u0646\u0648\u0646\u060c \u0627\u06cc\u0646 \u0628\u0647 \u0637\u0648\u0631 \u0631\u0633\u0645\u06cc \u06cc\u06a9 API \u0633\u0637\u062d \u0628\u0627\u0644\u0627 \u0627\u0633\u062a.  \u0646\u06cc\u0627\u0632\u06cc \u0628\u0647 \u0646\u0635\u0628 \u0635\u0631\u06cc\u062d \u0622\u0646 \u0646\u06cc\u0633\u062a\u060c \u0628\u0627 Tensorflow \u0639\u0631\u0636\u0647 \u0645\u06cc \u0634\u0648\u062f \u0648 \u0627\u06a9\u0646\u0648\u0646 \u0627\u0632 \u0637\u0631\u06cc\u0642 \u0622\u0646 \u0642\u0627\u0628\u0644 \u062f\u0633\u062a\u0631\u0633\u06cc \u0627\u0633\u062a <code>tf.keras<\/code>.<\/p>\n<p>\u0627\u06cc\u0646 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0645\u0646\u062c\u0631 \u0628\u0647 \u067e\u0627\u06a9\u0633\u0627\u0632\u06cc \u0648 \u062d\u0630\u0641 API \u0645\u06cc \u0634\u0648\u062f <code>tf.contrib.layers<\/code> <code>tf.layers<\/code>\u060c \u0648 \u063a\u06cc\u0631\u0647. <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.tensorflow.org\/api_docs\/python\/tf\/keras\" class=\"broken_link\"><code>tf.keras<\/code><\/a>  \u0627\u06a9\u0646\u0648\u0646 API \u0642\u0627\u0628\u0644 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0633\u062a.  \u0647\u0631 \u062f\u0648 <code>tf.contrib.layers<\/code> \u0648 <code>tf.layers<\/code> \u0647\u0645\u06cc\u0646 \u06a9\u0627\u0631 \u0631\u0627 \u0645\u06cc \u06a9\u0631\u062f\u0646\u062f  \u0648 \u0628\u0627 <code>tf.keras<\/code>\u060c \u0627\u0641\u0632\u0648\u0646\u06af\u06cc \u0633\u0647 \u06af\u0627\u0646\u0647 \u0648\u062c\u0648\u062f \u062e\u0648\u0627\u0647\u062f \u062f\u0627\u0634\u062a \u0632\u06cc\u0631\u0627 \u062d\u0627\u0648\u06cc \u0645\u0648\u0627\u0631\u062f \u0627\u0633\u062a <code>tf.keras.layers<\/code> \u0645\u062f\u0648\u0644.<\/p>\n<p>\u0627\u06cc\u0646 \u062a\u06cc\u0645 \u0647\u0645\u0686\u0646\u06cc\u0646 \u06cc\u06a9 <a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.tensorflow.org\/guide\/upgrade\" class=\"broken_link\">\u0631\u0627\u0647\u0646\u0645\u0627<\/a> \u06a9\u062f \u062e\u0648\u062f \u0631\u0627 \u0627\u0632 Tensorflow 1.x \u0628\u0647 Tensorflow 2.0 \u0627\u0631\u062a\u0642\u0627 \u062f\u0647\u06cc\u062f \u0632\u06cc\u0631\u0627 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0628\u0633\u062a\u0647 \u0647\u0627\u06cc \u0642\u062f\u06cc\u0645\u06cc \u0627\u06a9\u0646\u0648\u0646 \u0645\u0646\u0633\u0648\u062e \u0634\u062f\u0647 \u0627\u0646\u062f.<\/p>\n<h3 id=\"4tffunctiondecorator\"><span class=\"ez-toc-section\" id=\"4_tffunction_%d8%af%da%a9%d9%88%d8%b1%d8%a7%d8%aa%d9%88%d8%b1\"><\/span>4. <em>tf.function<\/em> \u062f\u06a9\u0648\u0631\u0627\u062a\u0648\u0631<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0627\u06cc\u0646 \u0646\u06cc\u0632 \u06cc\u06a9\u06cc \u0627\u0632 \u0647\u06cc\u062c\u0627\u0646 \u0627\u0646\u06af\u06cc\u0632\u062a\u0631\u06cc\u0646 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc Tensorflow 2 \u0627\u0633\u062a <a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.tensorflow.org\/guide\/function\" class=\"broken_link\"><code>@tf.function<\/code><\/a>  \u062f\u06a9\u0648\u0631\u0627\u062a\u0648\u0631 \u0628\u0647 \u062a\u0648\u0627\u0628\u0639 \u067e\u0627\u06cc\u062a\u0648\u0646 \u0627\u062c\u0627\u0632\u0647 \u0645\u06cc \u062f\u0647\u062f \u062a\u0627 \u0628\u0647 \u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0628\u0647 \u0622\u0646 \u062a\u0628\u062f\u06cc\u0644 \u0634\u0648\u0646\u062f <em>\u0646\u0645\u0648\u062f\u0627\u0631\u0647\u0627\u06cc \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648<\/em>.<\/p>\n<p>\u0634\u0645\u0627 \u0647\u0646\u0648\u0632 \u0647\u0645 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0645\u0627\u0645 \u0645\u0632\u0627\u06cc\u0627\u06cc \u0627\u062c\u0631\u0627\u06cc \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u0646\u0645\u0648\u062f\u0627\u0631 \u0631\u0627 \u062f\u0627\u0634\u062a\u0647 \u0628\u0627\u0634\u06cc\u062f \u0648 \u0627\u0632 \u0634\u0631 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u0633\u0646\u06af\u06cc\u0646 \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u062c\u0644\u0633\u0647 \u062e\u0644\u0627\u0635 \u0634\u0648\u06cc\u062f.  \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>@tf.function<\/code> \u062f\u06a9\u0648\u0631\u0627\u062a\u0648\u0631 \u0628\u0647 \u0639\u0645\u0644\u06a9\u0631\u062f\u06cc \u0645\u0627\u0646\u0646\u062f:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-meta\">@tf.function<\/span>\n<span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span> <span class=\"hljs-title\">multiply<\/span>(<span class=\"hljs-params\">a, b<\/span>):<\/span>\n  <span class=\"hljs-keyword\">return<\/span> a * b\n\nmultiply(tf.ones((<span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">2<\/span>)), tf.ones((<span class=\"hljs-number\">2<\/span>, <span class=\"hljs-number\">2<\/span>)))\n<\/code><\/pre>\n<p>\u062f\u0631 \u0635\u0648\u0631\u062a \u062a\u0639\u062c\u0628\u060c \u0627\u06cc\u0646 \u0628\u0647 \u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u0628\u0627 \u062a\u06a9\u0645\u06cc\u0644 \u0645\u06cc \u0634\u0648\u062f <em>\u062f\u0633\u062a\u062e\u0637<\/em>.  \u0646\u0645\u0648\u062f\u0627\u0631\u06cc \u062a\u0648\u0644\u06cc\u062f \u0645\u06cc\u200c\u06a9\u0646\u062f \u06a9\u0647 \u062f\u0642\u06cc\u0642\u0627\u064b \u0647\u0645\u0627\u0646 \u062c\u0644\u0648\u0647\u200c\u0647\u0627\u06cc \u062a\u0627\u0628\u0639\u06cc \u0631\u0627 \u06a9\u0647 \u0645\u0627 \u062a\u0632\u0626\u06cc\u0646 \u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u0645 \u062f\u0627\u0631\u062f.<\/p>\n<h3 id=\"5trainingusingdistributedcomputing\"><span class=\"ez-toc-section\" id=\"5_%d8%a2%d9%85%d9%88%d8%b2%d8%b4_%d8%a8%d8%a7_%d8%a7%d8%b3%d8%aa%d9%81%d8%a7%d8%af%d9%87_%d8%a7%d8%b2_%d9%85%d8%ad%d8%a7%d8%b3%d8%a8%d8%a7%d8%aa_%d8%aa%d9%88%d8%b2%db%8c%d8%b9_%d8%b4%d8%af%d9%87\"><\/span>5. \u0622\u0645\u0648\u0632\u0634 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0645\u062d\u0627\u0633\u0628\u0627\u062a \u062a\u0648\u0632\u06cc\u0639 \u0634\u062f\u0647<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Tensorflow 2.0 \u0628\u0627 \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647\u0628\u0648\u062f \u06cc\u0627\u0641\u062a\u0647 \u0628\u0631\u0627\u06cc \u0622\u0645\u0648\u0632\u0634 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 GPU \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc \u0634\u0648\u062f.  \u0637\u0628\u0642 \u06af\u0641\u062a\u0647 \u062a\u06cc\u0645\u060c \u0627\u06cc\u0646 \u0646\u0633\u062e\u0647 3 \u0628\u0631\u0627\u0628\u0631 \u0633\u0631\u06cc\u0639\u062a\u0631 \u0627\u0632 Tensorflow 1.x \u0627\u0633\u062a.<\/p>\n<p>\u0648 \u0627\u0632 \u0647\u0645 \u0627\u06a9\u0646\u0648\u0646\u060c \u062a\u0646\u0633\u0648\u0631\u0641\u0644\u0648 \u0645\u06cc \u062a\u0648\u0627\u0646\u062f \u0628\u0627 TPU \u0647\u0627 \u0646\u06cc\u0632 \u06a9\u0627\u0631 \u06a9\u0646\u062f.  \u062f\u0631 \u0648\u0627\u0642\u0639\u060c \u0634\u0645\u0627 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0628\u0627 \u0686\u0646\u062f\u06cc\u0646 TPU \u0648 GPU \u062f\u0631 \u06cc\u06a9 \u0631\u0648\u06cc\u06a9\u0631\u062f \u0645\u062d\u0627\u0633\u0628\u0627\u062a\u06cc \u062a\u0648\u0632\u06cc\u0639 \u0634\u062f\u0647 \u06a9\u0627\u0631 \u06a9\u0646\u06cc\u062f.<\/p>\n<p>\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062f\u0631 \u0627\u06cc\u0646 \u0645\u0648\u0631\u062f \u0628\u06cc\u0634\u062a\u0631 \u0628\u062e\u0648\u0627\u0646\u06cc\u062f <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.tensorflow.org\/guide\/distributed_training\" class=\"broken_link\">\u0631\u0627\u0647\u0646\u0645\u0627\u06cc \u0631\u0633\u0645\u06cc<\/a>.<\/p>\n<h3 id=\"6tfdataanddatasets\"><span class=\"ez-toc-section\" id=\"6_tfdata_%d9%88_%d9%85%d8%ac%d9%85%d9%88%d8%b9%d9%87_%d8%af%d8%a7%d8%af%d9%87_%d9%87%d8%a7\"><\/span>6. <em>tf.data<\/em> \u0648 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u0628\u0627 <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.tensorflow.org\/guide\/data\" class=\"broken_link\"><code>tf.data<\/code><\/a>\u060c \u0627\u06a9\u0646\u0648\u0646 \u0633\u0627\u062e\u062a \u062e\u0637\u0648\u0637 \u0644\u0648\u0644\u0647 \u062f\u0627\u062f\u0647 \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0633\u06cc\u0627\u0631 \u0622\u0633\u0627\u0646 \u0627\u0633\u062a.  \u0646\u06cc\u0627\u0632\u06cc \u0628\u0647 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0646\u06cc\u0633\u062a <code>feed_dict<\/code>. <code>tf.data<\/code> \u0627\u0632 \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0627\u0646\u0648\u0627\u0639 \u0641\u0631\u0645\u062a \u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0645\u0627\u0646\u0646\u062f \u0645\u062a\u0646\u060c \u062a\u0635\u0648\u06cc\u0631\u060c \u0648\u06cc\u062f\u0626\u0648\u060c \u0633\u0631\u06cc \u0632\u0645\u0627\u0646\u06cc \u0648 \u0645\u0648\u0627\u0631\u062f \u062f\u06cc\u06af\u0631 \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0645\u06cc \u06a9\u0646\u062f.<\/p>\n<p>\u0627\u06cc\u0646 \u0644\u0648\u0644\u0647 \u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc \u0628\u0633\u06cc\u0627\u0631 \u062a\u0645\u06cc\u0632 \u0648 \u06a9\u0627\u0631\u0622\u0645\u062f \u0631\u0627 \u0641\u0631\u0627\u0647\u0645 \u0645\u06cc \u06a9\u0646\u062f.  \u0645\u062b\u0644\u0627\u064b \u0628\u06af\u0648\u06cc\u06cc\u062f \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u0645 import \u06cc\u06a9 \u0641\u0627\u06cc\u0644 \u0645\u062a\u0646\u06cc \u0628\u0627 \u0686\u0646\u062f \u06a9\u0644\u0645\u0647 \u06a9\u0647 \u0627\u0632 \u0642\u0628\u0644 \u067e\u0631\u062f\u0627\u0632\u0634 \u0634\u062f\u0647 \u0648 \u062f\u0631 \u06cc\u06a9 \u0645\u062f\u0644 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0645\u06cc \u0634\u0648\u062f.  \u0628\u06cc\u0627\u06cc\u06cc\u062f \u0686\u0646\u062f \u067e\u06cc\u0634 \u067e\u0631\u062f\u0627\u0632\u0634 \u06a9\u0644\u0627\u0633\u06cc\u06a9 \u0631\u0627 \u0628\u0631\u0627\u06cc \u0627\u06a9\u062b\u0631 \u0645\u0634\u06a9\u0644\u0627\u062a NLP \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u0645.<\/p>\n<p>\u0628\u06cc\u0627\u06cc\u06cc\u062f \u0627\u0628\u062a\u062f\u0627 \u0641\u0627\u06cc\u0644 \u0631\u0627 \u0628\u062e\u0648\u0627\u0646\u06cc\u0645\u060c \u0647\u0645\u0647 \u06a9\u0644\u0645\u0627\u062a \u0631\u0627 \u0628\u0647 \u062d\u0631\u0648\u0641 \u06a9\u0648\u0686\u06a9 \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u06cc\u0645 \u0648 \u0622\u0646\u0647\u0627 \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u0644\u06cc\u0633\u062a \u062a\u0642\u0633\u06cc\u0645 \u06a9\u0646\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> numpy <span class=\"hljs-keyword\">as<\/span> np\n\ntext_file = <span class=\"hljs-string\">\"file.txt\"<\/span>\n\ntext = <span class=\"hljs-built_in\">open<\/span>(text_file,<span class=\"hljs-string\">'r'<\/span>).read()\n\ntext = text.lower()\ntext = text.split()\n<\/code><\/pre>\n<p>\u0633\u067e\u0633\u060c \u0645\u0627 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u0645 \u0647\u0645\u0647 \u06a9\u0644\u0645\u0627\u062a \u062a\u06a9\u0631\u0627\u0631\u06cc \u0631\u0627 \u062d\u0630\u0641 \u06a9\u0646\u06cc\u0645.  \u0627\u06cc\u0646 \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u0628\u0627 \u0628\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0622\u0646\u0647\u0627 \u062f\u0631 \u06cc\u06a9 \u0627\u0646\u062c\u0627\u0645 \u0645\u06cc \u0634\u0648\u062f <code>Set<\/code>\u060c \u062a\u0628\u062f\u06cc\u0644 \u0622\u0646 \u0628\u0647 a <code>List<\/code> \u0648 \u0645\u0631\u062a\u0628 \u06a9\u0631\u062f\u0646 \u0622\u0646:<\/p>\n<pre><code class=\"hljs\">words = <span class=\"hljs-built_in\">sorted<\/span>(<span class=\"hljs-built_in\">list<\/span>(<span class=\"hljs-built_in\">set<\/span>(text)))\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646 \u06a9\u0647 \u06a9\u0644\u0645\u0627\u062a \u0645\u0646\u062d\u0635\u0631\u0628\u0647\u200c\u0641\u0631\u062f \u0631\u0627 \u0645\u0631\u062a\u0628 \u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u0645\u060c \u0627\u0632 \u0622\u0646\u0647\u0627 \u0648\u0627\u0698\u06af\u0627\u0646\u06cc \u0645\u06cc\u200c\u0633\u0627\u0632\u06cc\u0645.  \u0647\u0631 \u06a9\u0644\u0645\u0647 \u062f\u0627\u0631\u0627\u06cc \u06cc\u06a9 \u0634\u0646\u0627\u0633\u0647 \u0631\u0642\u0645\u06cc \u0645\u0646\u062d\u0635\u0631 \u0628\u0647 \u0641\u0631\u062f \u062e\u0648\u0627\u0647\u062f \u0628\u0648\u062f \u06a9\u0647 \u0628\u0647 \u0622\u0646 \u0627\u062e\u062a\u0635\u0627\u0635 \u062f\u0627\u062f\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a:<\/p>\n<pre><code class=\"hljs\">vocab_to_int = {word:index <span class=\"hljs-keyword\">for<\/span> index, word <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">enumerate<\/span>(words)}\nint_to_vocab = np.array(words)\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646\u060c \u0628\u0631\u0627\u06cc \u062a\u0628\u062f\u06cc\u0644 \u0622\u0631\u0627\u06cc\u0647 \u0627\u0639\u062f\u0627\u062f \u0635\u062d\u06cc\u062d \u062e\u0648\u062f \u06a9\u0647 \u06a9\u0644\u0645\u0627\u062a \u0631\u0627 \u0628\u0647 \u06cc\u06a9 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 Tensorflow \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc \u06a9\u0646\u06cc\u0645\u060c \u0627\u0632 <code>from_tensor_slices()<\/code> \u0639\u0645\u0644\u06a9\u0631\u062f \u0627\u0631\u0627\u0626\u0647 \u0634\u062f\u0647 \u062a\u0648\u0633\u0637 <code>tf.data.Dataset<\/code>:<\/p>\n<pre><code class=\"hljs\">words_dataset = tf.data.Dataset.from_tensor_slices(words_as_int)\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u0645 \u0639\u0645\u0644\u06cc\u0627\u062a \u0631\u0627 \u0627\u0646\u062c\u0627\u0645 \u062f\u0647\u06cc\u0645 \u0631\u0648\u06cc \u0627\u06cc\u0646 \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647\u060c \u0645\u0627\u0646\u0646\u062f \u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0622\u0646 \u0628\u0647 \u062f\u0646\u0628\u0627\u0644\u0647 \u0647\u0627\u06cc \u06a9\u0648\u0686\u06a9\u062a\u0631:<\/p>\n<pre><code class=\"hljs\">seq_len = <span class=\"hljs-number\">50<\/span>\nsequences = words_dataset.batch(seq_len+<span class=\"hljs-number\">1<\/span>,drop_remainder=<span class=\"hljs-literal\">True<\/span>)\n<\/code><\/pre>\n<p>\u0627\u06a9\u0646\u0648\u0646\u060c \u0647\u0646\u06af\u0627\u0645 \u0622\u0645\u0648\u0632\u0634\u060c \u0645\u06cc\u200c\u062a\u0648\u0627\u0646\u06cc\u0645 \u0628\u0647 \u0631\u0627\u062d\u062a\u06cc \u062f\u0633\u062a\u0647\u200c\u0647\u0627\u06cc\u06cc \u0631\u0627 \u0627\u0632 \u0634\u06cc Dataset \u062f\u0631\u06cc\u0627\u0641\u062a \u06a9\u0646\u06cc\u0645:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">for<\/span> (batch_n,inp) <span class=\"hljs-keyword\">in<\/span> <span class=\"hljs-built_in\">enumerate<\/span>(dataset):\n<\/code><\/pre>\n<p>\u0627\u0632 \u0637\u0631\u0641 \u062f\u06cc\u06af\u0631\u060c \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0645\u0633\u062a\u0642\u06cc\u0645\u0627\u064b \u0645\u062c\u0645\u0648\u0639\u0647 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0645\u0648\u062c\u0648\u062f \u0631\u0627 \u062f\u0631 \u0622\u0646 \u0628\u0627\u0631\u06af\u06cc\u0631\u06cc \u06a9\u0646\u06cc\u062f <code>Dataset<\/code> \u0627\u0634\u06cc\u0627\u0621:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-keyword\">import<\/span> tensorflow_datasets <span class=\"hljs-keyword\">as<\/span> tfds\n\nmnist_data = tfds.load(<span class=\"hljs-string\">\"mnist\"<\/span>)\nmnist_train, mnist_test = mnist_data(<span class=\"hljs-string\">\"train\"<\/span>), mnist_data(<span class=\"hljs-string\">\"test\"<\/span>)\n<\/code><\/pre>\n<h3 id=\"7tfkerasmodel\"><span class=\"ez-toc-section\" id=\"7_tfkerasmodel\"><\/span>7. <em>tf.keras.Model<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>\u06cc\u06a9 \u062a\u0627\u0632\u06af\u06cc \u062f\u0648\u0633\u062a \u062f\u0627\u0634\u062a\u0646\u06cc \u0627\u06cc\u0646 \u0627\u0633\u062a \u06a9\u0647 \u0645\u062f\u0644 \u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0627 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0641\u0631\u0639\u06cc \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0646\u06cc\u062f <code>keras.Model<\/code> \u06a9\u0644\u0627\u0633<\/p>\n<p>\u06af\u0631\u0641\u062a\u0646 \u06cc\u06a9 \u0627\u0634\u0627\u0631\u0647 \u0627\u0632 PyTorch\u060c \u06a9\u0647 \u0628\u0647 \u062a\u0648\u0633\u0639\u0647 \u062f\u0647\u0646\u062f\u06af\u0627\u0646 \u0627\u062c\u0627\u0632\u0647 \u0645\u06cc \u062f\u0647\u062f \u062a\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06a9\u0644\u0627\u0633 \u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0645\u062f\u0644 \u0647\u0627\u06cc\u06cc \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u0646\u062f (\u0633\u0641\u0627\u0631\u0634\u06cc \u06a9\u0631\u062f\u0646 \u06a9\u0644\u0627\u0633 \u0647\u0627\u06cc\u06cc \u06a9\u0647 \u06cc\u06a9 <code>Layer<\/code>\u0648 \u062f\u0631 \u0646\u062a\u06cc\u062c\u0647 \u0633\u0627\u062e\u062a\u0627\u0631 \u0645\u062f\u0644 \u0631\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u0645\u06cc\u200c\u062f\u0647\u062f) &#8211; Tensorflow 2.0\u060c \u0627\u0632 \u0637\u0631\u06cc\u0642 Keras\u060c \u0628\u0647 \u0645\u0627 \u0627\u062c\u0627\u0632\u0647 \u0645\u06cc\u200c\u062f\u0647\u062f \u062a\u0627 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0631\u0627 \u0646\u06cc\u0632 \u062a\u0639\u0631\u06cc\u0641 \u06a9\u0646\u06cc\u0645.<\/p>\n<p>\u0628\u06cc\u0627\u06cc\u06cc\u062f a \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u0645 <code>Sequential<\/code> \u0645\u0627\u0646\u0646\u062f \u0645\u062f\u0644\u06cc \u06a9\u0647 \u0645\u0645\u06a9\u0646 \u0627\u0633\u062a \u0627\u0632 Tensorflow 1 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u06a9\u0646\u06cc\u062f:<\/p>\n<pre><code class=\"hljs\">\nmodel = tf.keras.Sequential((\ntf.keras.layers.Dense(<span class=\"hljs-number\">512<\/span>,activation=<span class=\"hljs-string\">'relu'<\/span>,input_shape=(<span class=\"hljs-number\">784<\/span>,)),\ntf.keras.layers.Dropout(<span class=\"hljs-number\">0.2<\/span>),\ntf.keras.layers.Dense(<span class=\"hljs-number\">512<\/span>,activation=<span class=\"hljs-string\">'relu'<\/span>),\ntf.keras.layers.Dropout(<span class=\"hljs-number\">0.2<\/span>),\ntf.keras.layers.Dense(<span class=\"hljs-number\">10<\/span>,activation=<span class=\"hljs-string\">'softmax'<\/span>)\n))\n<\/code><\/pre>\n<p>\u062f\u0631 \u062d\u0627\u0644 \u062d\u0627\u0636\u0631\u060c \u0628\u0647 \u062c\u0627\u06cc \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 <code>Sequential<\/code> \u0645\u062f\u0644\u060c \u0628\u06cc\u0627\u06cc\u06cc\u062f \u0645\u062f\u0644 \u062e\u0648\u062f \u0631\u0627 \u0628\u0627 \u0637\u0628\u0642\u0647 \u0628\u0646\u062f\u06cc \u0641\u0631\u0639\u06cc \u0628\u0633\u0627\u0632\u06cc\u0645 <code>keras.Model<\/code> \u06a9\u0644\u0627\u0633:<\/p>\n<pre><code class=\"hljs\">\n<span class=\"hljs-class\"><span class=\"hljs-keyword\">class<\/span> <span class=\"hljs-title\">mnist_model<\/span>(<span class=\"hljs-params\">tf.keras.Model<\/span>):<\/span>\n    <span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span> <span class=\"hljs-title\">__init__<\/span>(<span class=\"hljs-params\">self<\/span>):<\/span>\n        <span class=\"hljs-built_in\">super<\/span>(mnist_model,self).__init__()\n        self.dense1 = tf.keras.layers.Dense(<span class=\"hljs-number\">512<\/span>)\n        self.drop1 = tf.keras.layers.Dropout(<span class=\"hljs-number\">0.2<\/span>)\n        self.dense2 = tf.keras.layers.Dense(<span class=\"hljs-number\">512<\/span>)\n        self.drop2 = tf.keras.layers.Dropout(<span class=\"hljs-number\">0.2<\/span>)\n        self.dense3 = tf.keras.layers.Dense(<span class=\"hljs-number\">10<\/span>)\n\n    <span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span> <span class=\"hljs-title\">call<\/span>(<span class=\"hljs-params\">self,x<\/span>):<\/span>\n        x = tf.nn.relu(self.dense1(x))\n        x = self.drop1(x)\n        x = tf.nn.relu(self.dense2(x))\n        x = self.drop2(x)\n        x = tf.nn.softmax(self.dense3(x))\n        <span class=\"hljs-keyword\">return<\/span> x\n<\/code><\/pre>\n<p>\u0645\u0627 \u0628\u0647 \u0637\u0648\u0631 \u0645\u0624\u062b\u0631 \u0647\u0645\u0627\u0646 \u0645\u062f\u0644 \u0631\u0627 \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u0645\u060c \u0627\u06af\u0631\u0686\u0647 \u0627\u06cc\u0646 \u0631\u0648\u06cc\u06a9\u0631\u062f \u0628\u0647 \u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc\u200c\u062f\u0647\u062f \u062a\u0627 \u0628\u0647 \u0637\u0648\u0631 \u06a9\u0627\u0645\u0644 \u0645\u062f\u0644\u200c\u0647\u0627 \u0631\u0627 \u0645\u0637\u0627\u0628\u0642 \u0628\u0627 \u0646\u06cc\u0627\u0632 \u062e\u0648\u062f \u0633\u0641\u0627\u0631\u0634\u06cc\u200c\u0633\u0627\u0632\u06cc \u0648 \u0627\u06cc\u062c\u0627\u062f \u06a9\u0646\u06cc\u0645.<\/p>\n<h3 id=\"8tfgradienttape\"><span class=\"ez-toc-section\" id=\"8_tfgradienttape\"><\/span>8. <em>tf.GradientTape<\/em><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p><code>tf.GradientTape<\/code>  \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u0628\u0647 \u0637\u0648\u0631 \u062e\u0648\u062f\u06a9\u0627\u0631 \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u0647\u0627 \u0631\u0627 \u0645\u062d\u0627\u0633\u0628\u0647 \u06a9\u0646\u06cc\u062f.  \u0627\u06cc\u0646 \u062f\u0631 \u0647\u0646\u06af\u0627\u0645 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062d\u0644\u0642\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0645\u0641\u06cc\u062f \u0627\u0633\u062a.<\/p>\n<p>\u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u0645\u062f\u0644 \u062e\u0648\u062f \u0631\u0627 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u062d\u0644\u0642\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0647 \u062c\u0627\u06cc \u0641\u0631\u0627\u062e\u0648\u0627\u0646\u06cc \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u062f <code>model.fit<\/code>.  \u0627\u06cc\u0646 \u0628\u0647 \u0634\u0645\u0627 \u06a9\u0646\u062a\u0631\u0644 \u0628\u06cc\u0634\u062a\u0631\u06cc \u0631\u0648\u06cc \u0622\u0645\u0648\u0632\u0634 \u0645\u06cc \u062f\u0647\u062f process \u0627\u06af\u0631 \u0645\u06cc \u062e\u0648\u0627\u0647\u06cc\u062f \u0622\u0646 \u0631\u0627 \u062a\u063a\u06cc\u06cc\u0631 \u062f\u0647\u06cc\u062f<\/p>\n<p>\u062c\u0641\u062a \u06a9\u0631\u062f\u0646 \u062d\u0644\u0642\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u06a9\u0647 \u062a\u0648\u0633\u0637 <code>tf.GradientTape<\/code> \u0628\u0627 \u0645\u062f\u0644 \u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u06a9\u0647 \u062a\u0648\u0633\u0637 <code>keras.Model<\/code> \u0628\u0647 \u0634\u0645\u0627 \u06a9\u0646\u062a\u0631\u0644 \u0631\u0648\u06cc \u0645\u062f\u0644\u200c\u0647\u0627 \u0648 \u0622\u0645\u0648\u0632\u0634\u200c\u0647\u0627\u06cc\u06cc \u0645\u06cc\u200c\u062f\u0647\u062f \u06a9\u0647 \u0642\u0628\u0644\u0627\u064b \u0647\u0631\u06af\u0632 \u0646\u062f\u0627\u0634\u062a\u06cc\u062f.<\/p>\n<p>\u0627\u06cc\u0646\u0647\u0627 \u0628\u0647 \u0633\u0631\u0639\u062a \u0628\u0647 \u0648\u06cc\u0698\u06af\u06cc \u0647\u0627\u06cc \u0628\u0633\u06cc\u0627\u0631 \u0645\u062d\u0628\u0648\u0628 \u062f\u0631 \u062c\u0627\u0645\u0639\u0647 \u062a\u0628\u062f\u06cc\u0644 \u0634\u062f\u0646\u062f.  \u062f\u0631 \u0627\u06cc\u0646\u062c\u0627 \u0631\u0648\u0634 \u0627\u06cc\u062c\u0627\u062f \u06cc\u06a9 \u0645\u062f\u0644 \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0627 \u062a\u0648\u0627\u0628\u0639 \u062a\u0632\u0626\u06cc\u0646 \u0634\u062f\u0647 \u0648 \u06cc\u06a9 \u062d\u0644\u0642\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0622\u0645\u062f\u0647 \u0627\u0633\u062a:<\/p>\n<pre><code class=\"hljs\"><span class=\"hljs-string\">\"\"\"Note: We'll be using the model created in the previous section.\"\"\"<\/span>\n\nmodel = mnist_model()\n\noptimizer = tf.keras.optimizers.Adam(learning_rate=<span class=\"hljs-number\">0.001<\/span>)\nloss_object = tf.keras.losses.CategoricalCrossentropy(from_logits=<span class=\"hljs-literal\">False<\/span>)\n\n<span class=\"hljs-meta\">@tf.function<\/span>\n<span class=\"hljs-function\"><span class=\"hljs-keyword\">def<\/span>  <span class=\"hljs-title\">step<\/span>(<span class=\"hljs-params\">model,x,y<\/span>):<\/span>\n    <span class=\"hljs-string\">\"\"\"\n    model: in this case the mnist_model\n    x: input data in batches\n    y: True labels \"\"\"<\/span>\n    \n    <span class=\"hljs-keyword\">with<\/span> tf.GradientTape() <span class=\"hljs-keyword\">as<\/span> tape:\n        \n        predictions = model(x)\n        \n        loss = loss_object(y,predictions)\n    \n    trainable_variables = model.trainable_variables()\n\n    \n    gradients = tape.gradient(loss,trainable_variables)\n    \n    optimizer.apply_gradients(<span class=\"hljs-built_in\">zip<\/span>(gradients,trainable_variables))\n\n    <span class=\"hljs-keyword\">return<\/span> loss\n<\/code><\/pre>\n<p>\u062d\u0627\u0644\u0627 \u0634\u0645\u0627 \u0641\u0642\u0637 \u0645\u06cc \u062a\u0648\u0627\u0646\u06cc\u062f \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f <code>step()<\/code> \u0628\u0627 \u0627\u0631\u0633\u0627\u0644 \u0645\u062f\u0644 \u0648 \u062f\u0627\u062f\u0647 \u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0628\u0647 \u0635\u0648\u0631\u062a \u062f\u0633\u062a\u0647 \u0627\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u06cc\u06a9 \u062d\u0644\u0642\u0647 \u0639\u0645\u0644 \u06a9\u0646\u06cc\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>\u0628\u0627 \u0648\u0631\u0648\u062f Tensorflow 2.0\u060c \u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u0634\u06a9\u0633\u062a \u0647\u0627 \u0645\u062c\u062f\u062f\u0627\u064b \u0627\u0646\u062c\u0627\u0645 \u0634\u062f\u0647 \u0627\u0633\u062a.  \u0627\u0632 \u06af\u0633\u062a\u0631\u0634 \u062a\u0646\u0648\u0639 \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0633\u06cc\u0633\u062a\u0645 \u0648 \u062e\u062f\u0645\u0627\u062a \u062c\u062f\u06cc\u062f \u06af\u0631\u0641\u062a\u0647 \u062a\u0627 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0648 \u062d\u0644\u0642\u0647\u200c\u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc &#8211; Tensorflow 2.0 \u0647\u0645\u0686\u0646\u06cc\u0646 \u062a\u062c\u0631\u0628\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062c\u062f\u06cc\u062f\u06cc \u0631\u0627 \u0628\u0631\u0627\u06cc \u062a\u0645\u0631\u06cc\u0646\u200c\u06a9\u0646\u0646\u062f\u06af\u0627\u0646 \u06a9\u0647\u0646\u0647\u200c\u06a9\u0627\u0631 \u0645\u0639\u0631\u0641\u06cc \u06a9\u0631\u062f\u0647 \u0627\u0633\u062a.<\/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 1403-01-16 20:25:03<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;15762&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;\u0686\u0647 \u0686\u06cc\u0632\u06cc \u062f\u0631 Tensorflow 2.0 \u062c\u062f\u06cc\u062f \u0627\u0633\u062a\u061f&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\"> 7<\/span> <span class=\"rt-label rt-postfix\">\u062f\u0642\u06cc\u0642\u0647<\/span><\/span>\u0645\u0639\u0631\u0641\u06cc \u0627\u06af\u0631 \u0634\u0645\u0627 \u06cc\u06a9 \u0645\u0647\u0646\u062f\u0633 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646\u060c \u062f\u0627\u0646\u0634\u0645\u0646\u062f \u062f\u0627\u062f\u0647 \u06cc\u0627 \u0639\u0644\u0627\u0642\u0647\u200c\u0645\u0646\u062f\u06cc \u0647\u0633\u062a\u06cc\u062f \u06a9\u0647 \u0647\u0631 \u0627\u0632 \u06af\u0627\u0647\u06cc \u0628\u0631\u0627\u06cc \u0633\u0631\u06af\u0631\u0645\u06cc \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0631\u0627 \u062a\u0648\u0633\u0639\u0647 \u0645\u06cc\u200c\u062f\u0647\u062f\u060c \u0627\u062d\u062a\u0645\u0627\u0644\u0627\u064b \u0628\u0627 Tensorflow \u0622\u0634\u0646\u0627 \u0647\u0633\u062a\u06cc\u062f. Tensorflow \u06cc\u06a9 \u0686\u0627\u0631\u0686\u0648\u0628 \u0645\u062a\u0646 \u0628\u0627\u0632 \u0648 \u0631\u0627\u06cc\u06af\u0627\u0646 \u0627\u0633\u062a \u06a9\u0647 \u062a\u0648\u0633\u0637 Google Brain Team \u0646\u0648\u0634\u062a\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a \u0648 \u0628\u0647 \u0632\u0628\u0627\u0646 \u0647\u0627\u06cc Python\u060c C++ \u0648 CUDA \u0646\u0648\u0634\u062a\u0647 \u0634\u062f\u0647 [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":15763,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1743,620],"tags":[],"class_list":["post-15762","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\/15762","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=15762"}],"version-history":[{"count":0,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/posts\/15762\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media\/15763"}],"wp:attachment":[{"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/media?parent=15762"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/categories?post=15762"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rasanegaar.com\/blog\/wp-json\/wp\/v2\/tags?post=15762"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}