{"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\/cs\/blog\/news\/vypusk-sistemy-mashinnogo-obucheniya-tensorflow-2-0","title":{"rendered":"Vyd\u00e1n\u00ed syst\u00e9mu strojov\u00e9ho u\u010den\u00ed 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\">P\u0159edstaven\u00ed<\/a><\/noindex> v\u00fdznamn\u00e9 vyd\u00e1n\u00ed platformy strojov\u00e9ho u\u010den\u00ed <noindex><a rel=\"nofollow\" href=\"http:\/\/tensorflow.org\/\">TensorFlow 2.0<\/a><\/noindex>, kter\u00e1 poskytuje p\u0159ipraven\u00e9 implementace r\u016fzn\u00fdch algoritm\u016f hlubok\u00e9ho strojov\u00e9ho u\u010den\u00ed, jednoduch\u00e9 programov\u00e9 rozhran\u00ed pro vytv\u00e1\u0159en\u00ed model\u016f v jazyce Python a n\u00edzko\u00farov\u0148ov\u00e9 rozhran\u00ed pro jazyk C++, kter\u00e9 umo\u017e\u0148uje \u0159\u00eddit budov\u00e1n\u00ed a prov\u00e1d\u011bn\u00ed v\u00fdpo\u010detn\u00edch graf\u016f. K\u00f3d syst\u00e9mu je naps\u00e1n v jazyc\u00edch C++ a Python a <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/tensorflow\">distribuov\u00e1no<\/a><\/noindex> pod licenc\u00ed Apache. <\/p>\n<p>Platforma byla p\u016fvodn\u011b vyvinuta t\u00fdmem Google Brain a pou\u017e\u00edv\u00e1 se v slu\u017eb\u00e1ch Google pro rozpozn\u00e1v\u00e1n\u00ed \u0159e\u010di, identifikaci obli\u010dej\u016f na fotografi\u00edch, ur\u010dov\u00e1n\u00ed podobnosti obraz\u016f, filtrov\u00e1n\u00ed spamu v Gmailu, <noindex><a rel=\"nofollow\" href=\"https:\/\/www.blog.google\/products\/news\/new-google-news-ai-meets-human-intelligence\/\">v\u00fdb\u011br<\/a><\/noindex> novinek v Google News a organizaci p\u0159eklad\u016f s ohledem na kontext. Distribuovan\u00e9 syst\u00e9my strojov\u00e9ho u\u010den\u00ed lze vytv\u00e1\u0159et na standardn\u00edm hardwaru, d\u00edky vestav\u011bn\u00e9 podpo\u0159e v TensorFlow pro rozlo\u017een\u00ed v\u00fdpo\u010dt\u016f na v\u00edce CPU nebo GPU. <\/p>\n<p>TensorFlow poskytuje knihovnu p\u0159ipraven\u00fdch algoritm\u016f numerick\u00fdch v\u00fdpo\u010dt\u016f, realizovan\u00fdch pomoc\u00ed graf\u016f tok\u016f dat (data flow graphs). Uzly v t\u011bchto grafech realizuj\u00ed matematick\u00e9 operace nebo vstupn\u011b\/v\u00fdstupn\u00ed body, zat\u00edmco hrany grafu p\u0159edstavuj\u00ed v\u00edcerozm\u011brn\u00e9 datov\u00e9 pole (tenzory), kter\u00e9 proch\u00e1zej\u00ed mezi uzly.<br \/>\nUzly mohou b\u00fdt p\u0159i\u0159azeny k v\u00fdpo\u010detn\u00edm za\u0159\u00edzen\u00edm a prov\u00e1d\u011bny asynchronn\u011b, paraleln\u011b zpracov\u00e1vaj\u00edc\u00ed v\u0161echny odpov\u00eddaj\u00edc\u00ed tenzory, co\u017e umo\u017e\u0148uje organizovat sou\u010dasn\u00e9 fungov\u00e1n\u00ed uzl\u016f v neuronov\u00e9 s\u00edti podobn\u011b jako sou\u010dasnou aktivaci neuron\u016f v mozku.<\/p>\n<p>Hlavn\u00ed d\u016fraz p\u0159i p\u0159\u00edprav\u011b nov\u00e9 verze byl kladen na zjednodu\u0161en\u00ed a jednoduchost pou\u017eit\u00ed. <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/tensorflow\/releases\/tag\/v2.0.0\">N\u011bkter\u00e9<\/a><\/noindex> <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/effective_tf2\">novinky<\/a><\/noindex>:<\/p>\n<ul>\n<li class=\"l\"> Pro vytv\u00e1\u0159en\u00ed a tr\u00e9nov\u00e1n\u00ed model\u016f byl navr\u017een nov\u00fd vysoce \u00farov\u0148ov\u00fd API <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/beta\/guide\/keras\/overview\">Keras<\/a><\/noindex>, kter\u00fd poskytuje n\u011bkolik variant rozhran\u00ed pro vytv\u00e1\u0159en\u00ed model\u016f (Sekven\u010dn\u00ed, Funk\u010dn\u00ed, Podt\u0159\u00edd\u011bn\u00ed) s mo\u017enost\u00ed jejich <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/eager\">okam\u017eit\u00e9ho proveden\u00ed<\/a><\/noindex> (bez p\u0159edchoz\u00edho kompilov\u00e1n\u00ed) a s jednoduch\u00fdm mechanismem lad\u011bn\u00ed;\n<li class=\"l\"> Bylo p\u0159id\u00e1no API <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/beta\/guide\/distribute_strategy\">tf.distribute.Strategy<\/a><\/noindex> pro organizaci <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/distributed_training\">distribuovan\u00e9ho u\u010den\u00ed<\/a><\/noindex> model\u016f s minim\u00e1ln\u00edmi zm\u011bnami st\u00e1vaj\u00edc\u00edho k\u00f3du. Krom\u011b mo\u017enosti rozlo\u017een\u00ed v\u00fdpo\u010dt\u016f na <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/gpu\">v\u00edce GPU<\/a><\/noindex>, je k dispozici experiment\u00e1ln\u00ed podpora pro rozlo\u017een\u00ed procesu u\u010den\u00ed na v\u00edce nez\u00e1visl\u00fdch zpracovatel\u016f a mo\u017enost zapojen\u00ed cloudov\u00fdch <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> (Tensor processing unit);\n<li class=\"l\"> Nam\u00edsto deklarativn\u00edho modelu pro tvorbu grafu s prov\u00e1d\u011bn\u00edm p\u0159es tf.Session byla poskytnuta mo\u017enost psan\u00ed b\u011b\u017en\u00fdch funkc\u00ed v jazyce Python, kter\u00e9 mohou b\u00fdt pomoc\u00ed vol\u00e1n\u00ed tf.function p\u0159evedeny na grafy a pot\u00e9 prov\u00e1d\u011bny, serializov\u00e1ny nebo optimalizov\u00e1ny pro zv\u00fd\u0161en\u00ed v\u00fdkonu;\n<li class=\"l\"> Byl p\u0159id\u00e1n p\u0159eklada\u010d <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/function\">AutoGraph<\/a><\/noindex>, kter\u00fd p\u0159ev\u00e1d\u00ed tok p\u0159\u00edkaz\u016f Pythonu na v\u00fdrazy TensorFlow, co\u017e umo\u017e\u0148uje pou\u017e\u00edvat k\u00f3d v jazyce Python v r\u00e1mci funkc\u00ed opat\u0159en\u00fdch dekor\u00e1torem tf.function, tf.data, tf.distribute a tf.keras;\n<li class=\"l\"> Ve SavedModel byl sjednocen form\u00e1t v\u00fdm\u011bny model\u016f a p\u0159id\u00e1na podpora pro ukl\u00e1d\u00e1n\u00ed a obnovov\u00e1n\u00ed stav\u016f model\u016f. Modely sestaven\u00e9 pro TensorFlow mohou nyn\u00ed b\u00fdt pou\u017eity v <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/lite\">TensorFlow Lite<\/a><\/noindex> (na mobiln\u00edch za\u0159\u00edzen\u00edch), <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/js\">TensorFlow JS<\/a><\/noindex>  (v prohl\u00ed\u017ee\u010di nebo Node.js), <noindex><a rel=\"nofollow\" href=\"https:\/\/github.com\/tensorflow\/serving\">TensorFlow Serving<\/a><\/noindex> a <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/hub\">TensorFlow Hub<\/a><\/noindex>;\n<li class=\"l\"> Byly sjednoceny API tf.train.Optimizers a tf.keras.Optimizers, nam\u00edsto compute_gradients pro v\u00fdpo\u010det gradient\u016f byl nab\u00eddnut nov\u00fd t\u0159\u00edda  <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/api_docs\/python\/tf\/GradientTape\">GradientTape<\/a><\/noindex>;\n<li class=\"l\"> V\u00fdrazn\u011b se zv\u00fd\u0161il v\u00fdkon p\u0159i pou\u017e\u00edv\u00e1n\u00ed GPU.<br \/>\nRychlost u\u010den\u00ed model\u016f na syst\u00e9mech s GPU NVIDIA Volta a Turing vzrostla a\u017e t\u0159ikr\u00e1t;<\/p>\n<li class=\"l\"> <noindex><a rel=\"nofollow\" href=\"https:\/\/www.tensorflow.org\/guide\/effective_tf2\">Bylo provedeno<\/a><\/noindex> bylo provedeno velk\u00e9 \u010di\u0161t\u011bn\u00ed API, mnoho vol\u00e1n\u00ed bylo p\u0159ejmenov\u00e1no nebo odstran\u011bno, byla ukon\u010dena podpora glob\u00e1ln\u00edch prom\u011bnn\u00fdch v pomocn\u00fdch metod\u00e1ch. M\u00edsto tf.app, tf.flags, tf.logging byl nab\u00eddnut nov\u00fd API absl-py. Pro pokra\u010dov\u00e1n\u00ed v pou\u017e\u00edv\u00e1n\u00ed star\u00e9ho API byl p\u0159ipraven modul compat.v1.\n<\/ul>\n<p><noindex><a rel=\"nofollow\" name=\"link\"><\/a><\/noindex><\/p>\n<p>Zdroj: <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 5.0.3 - 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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