{"version":"1.0","provider_name":"Kodlar\u0131n Gizemli D\u00fcnyas\u0131","provider_url":"https:\/\/fatihsoysal.com\/blog","author_name":"Fatih Soysal","author_url":"https:\/\/fatihsoysal.com\/blog\/author\/fatihsoysal\/","title":"PyTorch Grafiklerinde Y\u00fcksek Dereceli T\u00fcrevler: THOAD Tan\u0131t\u0131m\u0131","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"SiJmdEhLDy\"><a href=\"https:\/\/fatihsoysal.com\/blog\/pytorch-grafiklerinde-yuksek-dereceli-turevler-thoad-tanitimi\/\">PyTorch Grafiklerinde Y\u00fcksek Dereceli T\u00fcrevler: THOAD Tan\u0131t\u0131m\u0131<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/fatihsoysal.com\/blog\/pytorch-grafiklerinde-yuksek-dereceli-turevler-thoad-tanitimi\/embed\/#?secret=SiJmdEhLDy\" width=\"600\" height=\"338\" title=\"&#8220;PyTorch Grafiklerinde Y\u00fcksek Dereceli T\u00fcrevler: THOAD Tan\u0131t\u0131m\u0131&#8221; &#8212; Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" data-secret=\"SiJmdEhLDy\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n<\/script>\n","description":"Derin \u00f6\u011frenme modellerinin optimizasyonu ve analizi i\u00e7in y\u00fcksek dereceli t\u00fcrevlerin \u00f6nemi giderek artmaktad\u0131r. PyTorch'un sundu\u011fu otomatik t\u00fcrev alma yetenekleri genellikle birinci ve ikinci dereceli t\u00fcrevlerle s\u0131n\u0131rl\u0131d\u0131r. Ancak, daha karma\u015f\u0131k optimizasyon teknikleri ve model analizi i\u00e7in daha y\u00fcksek dereceli t\u00fcrevlere ihtiya\u00e7 duyulur. \u0130\u015fte burada THOAD devreye giriyor: PyTorch grafikleri i\u00e7in y\u00fcksek dereceli t\u00fcrev hesaplamas\u0131n\u0131 kolayla\u015ft\u0131ran g\u00fc\u00e7l\u00fc bir ara\u00e7. Bu makale, THOAD'\u0131 s\u0131f\u0131rdan ba\u015flayarak detayl\u0131 bir \u015fekilde a\u00e7\u0131klayacak ve pratik uygulamalar\u0131yla birlikte ileri d\u00fczey teknikleri ele alacakt\u0131r."}