{"id":38573,"date":"2019-10-31T22:24:37","date_gmt":"2019-10-31T19:24:37","guid":{"rendered":"https:\/\/prohoster.info\/blog\/vypusk-sistemy-mashinnogo-obucheniya-tensorflow-2-0\/"},"modified":"2019-10-31T22:24:37","modified_gmt":"2019-10-31T19:24:37","slug":"vypusk-sistemy-mashinnogo-obucheniya-tensorflow-2-0","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/novosti-interneta\/vypusk-sistemy-mashinnogo-obucheniya-tensorflow-2-0","title":{"rendered":"L\u00ebshimi i sistemit t\u00eb m\u00ebsimit t\u00eb makineri TensorFlow 2.0","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p><noindex><a rel=\"nofollow\" href=\"https:\/\/medium.com\/tensorflow\/tensorflow-2-0-is-now-available-57d706c2a9ab\">T\u00eb paraqitura<\/a><\/noindex> l\u00ebshim i r\u00ebnd\u00ebsish\u00ebm i platform\u00ebs s\u00eb m\u00ebsimit t\u00eb makinerive <noindex><a rel=\"nofollow\" href=\"http:\/\/tensorflow.org\/\">TensorFlow 2.0<\/a><\/noindex>, i cili ofron zbatime t\u00eb gatshme t\u00eb algoritmeve t\u00eb ndrysh\u00ebm t\u00eb thell\u00eb t\u00eb m\u00ebsimit t\u00eb makinerive, nj\u00eb nd\u00ebrfaqe t\u00eb thjesht\u00eb programimi p\u00ebr nd\u00ebrtimin e modeleve n\u00eb gjuh\u00ebn Python dhe nj\u00eb nd\u00ebrfaqe t\u00eb nivelit t\u00eb ul\u00ebt p\u00ebr gjuh\u00ebn C++, e cila lejon menaxhimin e nd\u00ebrtimit dhe ekzekutimit t\u00eb grafik\u00ebve t\u00eb llogaritjes. Kodi i sistemit \u00ebsht\u00eb shkruar n\u00eb gjuh\u00ebt C++ dhe Python dhe <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/tensorflow\">distribuohet<\/a><\/noindex> n\u00eb p\u00ebrputhje me licenc\u00ebn Apache. <\/p>\n<p>Platforma \u00ebsht\u00eb zhvilluar fillimisht nga ekipi Google Brain dhe p\u00ebrdoret n\u00eb sh\u00ebrbimet e Google p\u00ebr njohjen e z\u00ebrit, identifikimin e fytyrave n\u00eb foto, p\u00ebrcaktimin e ngjashm\u00ebrive t\u00eb imazheve, filtrimin e spamit n\u00eb Gmail, <noindex><a rel=\"nofollow\" href=\"https:\/\/www.blog.google\/products\/news\/new-google-news-ai-meets-human-intelligence\/\">propozimin<\/a><\/noindex> e lajmeve n\u00eb Google News dhe organizimin e p\u00ebrkthimeve n\u00eb p\u00ebrputhje me kuptimin. Sistemet e shp\u00ebrndara t\u00eb m\u00ebsimit t\u00eb makinerive mund t\u00eb nd\u00ebrtohen n\u00eb pajisje standarde, fal\u00eb mb\u00ebshtetjes s\u00eb p\u00ebrfshir\u00eb n\u00eb TensorFlow p\u00ebr shp\u00ebrndarjen e llogaritjeve n\u00eb disa CPU ose GPU. <\/p>\n<p>TensorFlow ofron nj\u00eb bibliotek\u00eb algoritmesh t\u00eb gatshme p\u00ebr llogaritje numerike, t\u00eb realizuara p\u00ebrmes grafeve t\u00eb fluksit t\u00eb t\u00eb dh\u00ebnave (data flow graphs). Nodalet n\u00eb k\u00ebto grafe realizojn\u00eb operacione matematikore ose pika hyrjeje\/daljeje, nd\u00ebrsa skajet e grafit p\u00ebrfaq\u00ebsojn\u00eb tabela shum\u00ebdimensionale t\u00eb t\u00eb dh\u00ebnave (tenzora) q\u00eb rrjedhin midis nodave.<br \/>\nNodalet mund t\u00eb lidhen me pajisjet llogarit\u00ebse dhe t\u00eb kryhen asinkronisht, duke procesuar nj\u00ebkoh\u00ebsisht t\u00eb gjith\u00eb tenzor\u00ebt e duhur, \u00e7ka mund\u00ebson pun\u00ebn e p\u00ebrbashk\u00ebt t\u00eb nodave n\u00eb nj\u00eb rrjet nervor, ngjash\u00ebm me aktivizimin e p\u00ebrbashk\u00ebt t\u00eb neuron\u00ebve n\u00eb tru.<\/p>\n<p>V\u00ebmendja kryesore gjat\u00eb p\u00ebrgatitjes s\u00eb versionit t\u00eb ri \u00ebsht\u00eb vendosur n\u00eb thjesht\u00ebsin\u00eb dhe leht\u00ebsin\u00eb e p\u00ebrdorimit. <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/tensorflow\/releases\/tag\/v2.0.0\">Disa<\/a><\/noindex> <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/effective_tf2\">risit\u00eb<\/a><\/noindex>:<\/p>\n<ul>\n<li class=\"l\"> P\u00ebr nd\u00ebrtimin dhe st\u00ebrvitjen e modeleve \u00ebsht\u00eb propozuar nj\u00eb API i ri me nivel t\u00eb lart\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/beta\/guide\/keras\/overview\">Keras<\/a><\/noindex>, i cili ofron disa mund\u00ebsi nd\u00ebrfaqesh p\u00ebr nd\u00ebrtimin e modeleve (Sequential, Functional, Subclassing) me mund\u00ebsin\u00eb p\u00ebr <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/eager\">ekzekutimin e menj\u00ebhersh\u00ebm<\/a><\/noindex> (pa kompilim paraprak) dhe me nj\u00eb mekaniz\u00ebm t\u00eb thjesht\u00eb p\u00ebr debugging;\n<li class=\"l\"> API e re <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/beta\/guide\/distribute_strategy\">tf.distribute.Strategy<\/a><\/noindex> p\u00ebr organizimin e <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/distributed_training\">m\u00ebsimit t\u00eb shp\u00ebrndar\u00eb<\/a><\/noindex> modeleve me ndryshime minimale t\u00eb kodit ekzistues. P\u00ebrve\u00e7 mund\u00ebsis\u00eb s\u00eb shp\u00ebrndarjes s\u00eb llogaritjeve n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/gpu\">shum\u00eb GPU<\/a><\/noindex>, mb\u00ebshtetje eksperimentale p\u00ebr shp\u00ebrndarjen e procesit t\u00eb trajnimit n\u00eb disa trajtues t\u00eb pavarur dhe mund\u00ebsia p\u00ebr t\u00eb angazhuar <noindex><a rel=\"nofollow\" href=\"https:\/\/ru.wikipedia.org\/wiki\/%D0%A2%D0%B5%D0%BD%D0%B7%D0%BE%D1%80%D0%BD%D1%8B%D0%B9_%D0%BF%D1%80%D0%BE%D1%86%D0%B5%D1%81%D1%81%D0%BE%D1%80_Google\">TPU<\/a><\/noindex> (nj\u00ebsia e p\u00ebrpunimit t\u00eb tensor\u00ebve);\n<li class=\"l\"> N\u00eb vend t\u00eb modelit deklarativ t\u00eb nd\u00ebrtimit t\u00eb grafikut me ekzekutim p\u00ebrmes tf.Session, ofrohet mund\u00ebsia p\u00ebr t\u00eb shkruar funksione t\u00eb zakonshme n\u00eb gjuh\u00ebn Python, t\u00eb cilat me an\u00eb t\u00eb thirrjes tf.function mund t\u00eb konvertohen n\u00eb grafe dhe m\u00eb pas t\u00eb ekzekutohen, serializohen ose optimizohen p\u00ebr t\u00eb rritur performanc\u00ebn;\n<li class=\"l\"> T\u00eb shtuar nj\u00eb p\u00ebrkthyes <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/function\">AutoGraph<\/a><\/noindex>, q\u00eb shnd\u00ebrron rrjedh\u00ebn e komandave Python n\u00eb shprehje TensorFlow, duke e b\u00ebr\u00eb t\u00eb mundur p\u00ebrdorimin e kodit n\u00eb gjuh\u00ebn Python brenda funksioneve t\u00eb dekoruara me tf.function, tf.data, tf.distribute dhe tf.keras;\n<li class=\"l\"> N\u00eb SavedModel, formati i shk\u00ebmbimit t\u00eb modeleve \u00ebsht\u00eb uniformuar dhe \u00ebsht\u00eb shtuar mb\u00ebshtetje p\u00ebr ruajtjen dhe rikthimin e gjendjes s\u00eb modeleve. Modelet e mbledhura p\u00ebr TensorFlow tani mund t\u00eb p\u00ebrdoren n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/lite\">TensorFlow Lite<\/a><\/noindex> (n\u00eb pajisje mobile), <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/js\">TensorFlow JS<\/a><\/noindex>  (n\u00eb shfletues ose Node.js), <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/serving\">TensorFlow Serving<\/a><\/noindex> dhe <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/hub\">TensorFlow Hub<\/a><\/noindex>;\n<li class=\"l\"> API-t\u00eb e unifikuara tf.train.Optimizers dhe tf.keras.Optimizers, n\u00eb vend t\u00eb compute_gradients, \u00ebsht\u00eb propozuar nj\u00eb klas\u00eb e re p\u00ebr llogaritjen e gradient\u00ebve.  <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/api_docs\/python\/tf\/GradientTape\">GradientTape<\/a><\/noindex>;\n<li class=\"l\"> Performanca \u00ebsht\u00eb rritur ndjesh\u00ebm kur p\u00ebrdoren GPU.<br \/>\nShpejt\u00ebsia e t\u00eb m\u00ebsuarit t\u00eb modeleve n\u00eb sistemet me GPU NVIDIA Volta dhe Turing \u00ebsht\u00eb rritur deri n\u00eb tre her\u00eb.<\/p>\n<li class=\"l\"> <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/effective_tf2\">\u00cbsht\u00eb kryer<\/a><\/noindex> Ka pasur nj\u00eb pastrim t\u00eb madh t\u00eb API-t, shum\u00eb thirrje jan\u00eb rib\u00ebr\u00eb ose fshir\u00eb, mb\u00ebshtetja p\u00ebr variablat global\u00eb n\u00eb metodat ndihm\u00ebse \u00ebsht\u00eb nd\u00ebrprer\u00eb. N\u00eb vend t\u00eb tf.app, tf.flags, tf.logging, \u00ebsht\u00eb propozuar nj\u00eb API i ri absl-py. P\u00ebr t\u00eb vazhduar p\u00ebrdorimin e API-t t\u00eb vjet\u00ebr, \u00ebsht\u00eb p\u00ebrgatitur moduli compat.v1.\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Burimi: <a \ncontent=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=51595\">opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d \u0437\u043d\u0430\u0447\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u0432\u044b\u043f\u0443\u0441\u043a \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f TensorFlow 2.0, \u043f\u0440\u0435\u0434\u043e\u0441\u0442\u0430\u0432\u043b\u044f\u044e\u0449\u0435\u0439 \u0433\u043e\u0442\u043e\u0432\u044b\u0435 \u0440\u0435\u0430\u043b\u0438\u0437\u0430\u0446\u0438\u0438 \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0445 \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u043e\u0432 \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0433\u043e \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f, \u043f\u0440\u043e\u0441\u0442\u043e\u0439 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u043d\u044b\u0439 \u0438\u043d\u0442\u0435\u0440\u0444\u0435\u0439\u0441 \u0434\u043b\u044f \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python \u0438 \u043d\u0438\u0437\u043a\u043e\u0443\u0440\u043e\u0432\u043d\u0435\u0432\u044b\u0439 \u0438\u043d\u0442\u0435\u0440\u0444\u0435\u0439\u0441 \u0434\u043b\u044f \u044f\u0437\u044b\u043a\u0430 \u0421++, \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0438\u0439 \u0443\u043f\u0440\u0430\u0432\u043b\u044f\u0442\u044c \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u0435\u043c \u0438 \u0432\u044b\u043f\u043e\u043b\u043d\u0435\u043d\u0438\u0435\u043c \u0432\u044b\u0447\u0438\u0441\u043b\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0445 \u0433\u0440\u0430\u0444\u043e\u0432. \u041a\u043e\u0434 \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0430\u0445 \u0421++ \u0438 Python \u0438 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 Apache. \u041f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u0430 \u0438\u0437\u043d\u0430\u0447\u0430\u043b\u044c\u043d\u043e \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u0430\u043d\u0430 \u043a\u043e\u043c\u0430\u043d\u0434\u043e\u0439 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-38573","post","type-post","status-publish","format-standard","hentry","category-novosti-interneta"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.0.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"\u041f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u0435\u043d \u0437\u043d\u0430\u0447\u0438\u0442\u0435\u043b\u044c\u043d\u044b\u0439 \u0432\u044b\u043f\u0443\u0441\u043a \u043f\u043b\u0430\u0442\u0444\u043e\u0440\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f\" \/>\n\t<meta name=\"robots\" content=\"max-image-preview:large\" \/>\n\t<meta name=\"author\" content=\"Yuri Gagarin\"\/>\n\t<link 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