{"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\/news\/vypusk-sistemy-mashinnogo-obucheniya-tensorflow-2-0","title":{"rendered":"Publikimi i sistemit t\u00eb m\u00ebsimit automatik 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\">Presented<\/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>, e cila ofron realizime 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 leht\u00eb 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++, q\u00eb lejon menaxhimin e nd\u00ebrtimit dhe ekzekutimit t\u00eb graf\u00ebve t\u00eb llogaritjeve. Kodi i sistemit \u00ebsht\u00eb shkruar n\u00eb gjuh\u00ebt C++ dhe Python dhe <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/tensorflow\">shp\u00ebrndahet<\/a><\/noindex> n\u00eb baz\u00eb t\u00eb licenc\u00ebs Apache. <\/p>\n<p>Platforma u zhvillua 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 fotografi, 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\/\">k\u00ebrkimin<\/a><\/noindex> e lajmeve n\u00eb Google News dhe organizimin e p\u00ebrkthimeve me kuptim. Sistemet e shp\u00ebrndara t\u00eb m\u00ebsimit t\u00eb makinerive mund t\u00eb ndihmohen n\u00eb pajisje standarde, fal\u00eb mb\u00ebshtetjes t\u00eb integruar n\u00eb TensorFlow p\u00ebr shp\u00ebrndarjen e llogaritjeve n\u00eb shum\u00eb CPU ose GPU. <\/p>\n<p>TensorFlow ofron nj\u00eb bibliotek\u00eb algoritmesh t\u00eb gatsh\u00ebm p\u00ebr llogaritje numerike, t\u00eb realizuar p\u00ebrmes graf\u00ebve t\u00eb rrjedh\u00ebs s\u00eb dh\u00ebnave (data flow graphs). Ngritjet n\u00eb k\u00ebto grafe realizojn\u00eb operacione matematikore ose pika hyrjeje\/daljeje, nd\u00ebrsa lidhjet e grafit p\u00ebrfaq\u00ebsojn\u00eb masiv t\u00eb shumt\u00eb t\u00eb dh\u00ebnash (tenzor\u00eb), t\u00eb cilat rrjedhin midis ngritjeve.<br \/>\nNgritjet mund t\u00eb caktohen p\u00ebr pajisje llogarit\u00ebse dhe t\u00eb ekzekutohen asinkronisht, duke trajtuar paralelisht t\u00eb gjitha tenzor\u00ebt p\u00ebrkat\u00ebs, duke lejuar q\u00eb ngritjet t\u00eb funksionojn\u00eb n\u00eb m\u00ebnyr\u00eb t\u00eb nj\u00ebkohshme n\u00eb nj\u00eb rrjet nervor, ashtu si aktivizimi i nj\u00ebkohsh\u00ebm i neuroneve n\u00eb tru.<\/p>\n<p>Kjo version i ri u p\u00ebrqendrua kryesisht n\u00eb thjesht\u00ebsimin dhe leht\u00ebsimin 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\">innovations<\/a><\/noindex>:<\/p>\n<ul>\n<li class=\"l\"> P\u00ebr nd\u00ebrtimin dhe trajnimin e modeleve \u00ebsht\u00eb propozuar nj\u00eb API e re e nivelit t\u00eb lart\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/beta\/guide\/keras\/overview\">Keras<\/a><\/noindex>, e cila ofron disa mund\u00ebsi nd\u00ebrfaqesh p\u00ebr nd\u00ebrtimin e modeleve (Sekondar, Funksionale, N\u00ebnklasifikimi) me mund\u00ebsin\u00eb e tyre <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/eager\">ekzekutimit t\u00eb menj\u00ebhersh\u00ebm<\/a><\/noindex> (pa kompilim paraprak) dhe me nj\u00eb mekaniz\u00ebm t\u00eb thjesht\u00eb p\u00ebr debuggim;\n<li class=\"l\"> Shtuar API <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/beta\/guide\/distribute_strategy\">tf.distribute.Strategy<\/a><\/noindex> p\u00ebr organizimin <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/distributed_training\">e m\u00ebsimit t\u00eb shp\u00ebrndar\u00eb<\/a><\/noindex> t\u00eb modeleve me ndryshime minimale n\u00eb kodin ekzistues. P\u00ebrve\u00e7 mund\u00ebsis\u00eb p\u00ebr t\u00eb shp\u00ebrndar\u00eb llogaritjet n\u00eb <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/gpu\">shum\u00eb GPU<\/a><\/noindex>, \u00ebsht\u00eb n\u00eb dispozicion mb\u00ebshtetje eksperimentale p\u00ebr shp\u00ebrndarjen e procesit t\u00eb trajnimit n\u00eb shum\u00eb procesor\u00eb t\u00eb pavarur dhe mund\u00ebsin\u00eb e p\u00ebrdorimit t\u00eb cloud <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 tenzor\u00ebve);\n<li class=\"l\"> N\u00eb vend t\u00eb modelit deklarativ t\u00eb nd\u00ebrtimit t\u00eb grafit 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 p\u00ebrmes thirrjes tf.function mund t\u00eb shnd\u00ebrrohen n\u00eb graf\u00eb dhe m\u00eb pas t\u00eb ekzekutohen me distanc\u00eb, t\u00eb serializohen ose t\u00eb optimizohen p\u00ebr t\u00eb rritur performanc\u00ebn;\n<li class=\"l\"> Shtuar p\u00ebrkthyesi <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/function\">AutoGraph<\/a><\/noindex>, i cili shnd\u00ebrron rrjedh\u00ebn e komandave Python n\u00eb shprehje TensorFlow, duke lejuar 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 \u00ebsht\u00eb unifikuar formati i shk\u00ebmbimit t\u00eb modeleve dhe \u00ebsht\u00eb shtuar mb\u00ebshtetje p\u00ebr ruajtjen dhe rikthimin e gjendjes s\u00eb modeleve. Modelet e nd\u00ebrtuara 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 pajisjet 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 tf.train.Optimizers dhe tf.keras.Optimizers jan\u00eb unifikuar, nd\u00ebrsa p\u00ebr t\u00eb llogaritur gradien\u00ebt \u00ebsht\u00eb propozuar klasi i ri  <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 gjat\u00eb p\u00ebrdorimit t\u00eb GPU.<br \/>\nShpejt\u00ebsia e m\u00ebsimit t\u00eb modeleve n\u00eb sistemet me GPU NVIDIA Volta dhe Turing \u00ebsht\u00eb rritur deri n\u00eb tri her\u00eb;<\/p>\n<li class=\"l\"> <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/effective_tf2\">\u00cbsht\u00eb b\u00ebr\u00eb<\/a><\/noindex> Nj\u00eb pastrim i madh i API-s\u00eb, shum\u00eb thirrje jan\u00eb rinovuar 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 vazhdimin e p\u00ebrdorimit t\u00eb vjet\u00ebr t\u00eb API-s\u00eb, \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-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2.1 - 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 rel=\"canonical\" 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