{"id":106018,"date":"2022-12-13T09:36:49","date_gmt":"2022-12-13T07:36:49","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-sistemy-mashinnogo-perevoda-opennmt-tf-2-30"},"modified":"2022-12-13T09:36:49","modified_gmt":"2022-12-13T07:36:49","slug":"vypusk-sistemy-mashinnogo-perevoda-opennmt-tf-2-30","status":"publish","type":"post","link":"https:\/\/prohoster.info\/cs\/blog\/news\/vypusk-sistemy-mashinnogo-perevoda-opennmt-tf-2-30","title":{"rendered":"Vyd\u00e1n\u00ed syst\u00e9mu strojov\u00e9ho p\u0159ekladu OpenNMT-tf 2.30","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Byla zve\u0159ejn\u011bna verze syst\u00e9mu strojov\u00e9ho p\u0159ekladu OpenNMT-tf 2.30.0 (Open Neural Machine Translation), kter\u00fd vyu\u017e\u00edv\u00e1 metody strojov\u00e9ho u\u010den\u00ed. K\u00f3d modul\u016f vyv\u00edjen\u00fdch projektem OpenNMT-tf je naps\u00e1n v jazyce Python, vyu\u017e\u00edv\u00e1 knihovnu TensorFlow a je \u0161\u00ed\u0159en pod licenc\u00ed MIT.     <\/p>\n<p>Sou\u010dasn\u011b se vyv\u00edj\u00ed varianta OpenNMT zalo\u017een\u00e1 na knihovn\u011b PyTorch, kter\u00e1 se li\u0161\u00ed z hlediska podporovan\u00fdch mo\u017enost\u00ed. Krom\u011b toho je OpenNMT na b\u00e1zi PyTorch prezentov\u00e1n jako jednodu\u0161\u0161\u00ed pro pou\u017eit\u00ed a multimod\u00e1ln\u00ed, zat\u00edmco varianta na b\u00e1zi TensorFlow je ozna\u010dov\u00e1na jako modul\u00e1rn\u00ed, stabiln\u00ed a umo\u017e\u0148uj\u00edc\u00ed vyu\u017e\u00edt mo\u017enosti GPU pro zrychlen\u00ed procesu u\u010den\u00ed neuronov\u00e9 s\u00edt\u011b. Pro usnadn\u011bn\u00ed distribuce produktu projekt tak\u00e9 vyv\u00edj\u00ed sob\u011bsta\u010dnou variantu p\u0159eklada\u010de v jazyce C++ \u2014 CTranslate2, kter\u00e1 pou\u017e\u00edv\u00e1 p\u0159edem natr\u00e9novan\u00e9 modely bez vazby na dal\u0161\u00ed z\u00e1vislosti.         <\/p>\n<p>Modely jsou p\u0159ipraveny pro anglick\u00fd, n\u011bmeck\u00fd a katal\u00e1nsk\u00fd jazyk, pro ostatn\u00ed jazyky si lze model vytvo\u0159it samostatn\u011b na z\u00e1klad\u011b datov\u00e9 sady projektu OPUS (pro tr\u00e9nink syst\u00e9mu jsou p\u0159ed\u00e1v\u00e1ny dva soubory \u2014 jeden s v\u011btami v p\u016fvodn\u00edm jazyce a druh\u00fd s kvalitn\u00edm p\u0159ekladem t\u011bchto v\u011bt do c\u00edlov\u00e9ho jazyka).    <\/p>\n<p>Projekt se vyv\u00edj\u00ed za \u00fa\u010dasti spole\u010dnosti SYSTRAN, kter\u00e1 se specializuje na v\u00fdvoj prost\u0159edk\u016f strojov\u00e9ho p\u0159ekladu, a skupiny v\u00fdzkumn\u00edk\u016f z Harvardu, kte\u0159\u00ed vyv\u00edjej\u00ed modely lidsk\u00e9ho jazyka pro syst\u00e9my strojov\u00e9ho u\u010den\u00ed. U\u017eivatelsk\u00e9 rozhran\u00ed je maxim\u00e1ln\u011b zjednodu\u0161en\u00e9 a vy\u017eaduje pouze uveden\u00ed vstupn\u00edho souboru s textem a souboru pro ulo\u017een\u00ed v\u00fdsledku p\u0159ekladu. Syst\u00e9m roz\u0161\u00ed\u0159en\u00ed umo\u017e\u0148uje implementaci dodate\u010dn\u00e9 funk\u010dnosti na b\u00e1zi OpenNMT, nap\u0159\u00edklad autoreferov\u00e1n\u00ed, klasifikaci text\u016f a generaci titulk\u016f.     <\/p>\n<p>V nov\u00e9 verzi:  <\/p>\n<ul>\n<li class=\"l\"> Byla p\u0159id\u00e1na podpora pro knihovnu TensorFlow 2.11, ale nov\u00e9 optimaliz\u00e1tory Keras zat\u00edm nejsou podporov\u00e1ny (je nutn\u00e9 pou\u017e\u00edvat re\u017eim tf.keras.optimizers.legacy).\n<li class=\"l\"> Byla p\u0159id\u00e1na podpora nov\u00e9 v\u011btve enginu CTranslate2 3.x, ur\u010den\u00e9 pro efektivn\u00ed prov\u00e1d\u011bn\u00ed model\u016f s architekturou \u201etransformer\u201c.\n<li class=\"l\"> Byl p\u0159id\u00e1n parametr \u0161kolen\u00ed model\u016f pad_to_bucket_boundary pro zahrnut\u00ed dodate\u010dn\u00e9ho vypln\u011bn\u00ed, kter\u00e9 vyrovn\u00e1v\u00e1 velikost bloku na hodnoty n\u00e1sob\u00edc\u00ed length_bucket_width.\n<li class=\"l\"> Byla integrov\u00e1na podpora metrik chrf a chrf++ z projektu SacreBLEU, kter\u00e9 porovn\u00e1vaj\u00ed strojov\u00fd p\u0159eklad s referen\u010dn\u00edm lidsk\u00fdm p\u0159ekladem.\n<li class=\"l\"> Byl odstran\u011bn atribut modelu ctranslate2_spec, kter\u00fd se ji\u017e nepou\u017e\u00edv\u00e1 v CTranslate2.  <\/ul>\n<p>Zdroj: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/www.opennet.ru\/opennews\/art.shtml?num=58316\">opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u041e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043d \u0432\u044b\u043f\u0443\u0441\u043a \u0441\u0438\u0441\u0442\u0435\u043c\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043f\u0435\u0440\u0435\u0432\u043e\u0434\u0430 OpenNMT-tf 2.30.0 (Open Neural Machine Translation), \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u044e\u0449\u0435\u0439 \u043c\u0435\u0442\u043e\u0434\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f. \u041a\u043e\u0434 \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u043c\u044b\u0445 \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u043c OpenNMT-tf \u043c\u043e\u0434\u0443\u043b\u0435\u0439 \u043d\u0430\u043f\u0438\u0441\u0430\u043d \u043d\u0430 \u044f\u0437\u044b\u043a\u0435 Python, \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u0442 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0443 TensorFlow \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 MIT. \u041f\u0430\u0440\u0430\u043b\u043b\u0435\u043b\u044c\u043d\u043e \u0440\u0430\u0437\u0432\u0438\u0432\u0430\u0435\u0442\u0441\u044f \u0432\u0430\u0440\u0438\u0430\u043d\u0442 OpenNMT \u043d\u0430 \u0431\u0430\u0437\u0435 \u0431\u0438\u0431\u043b\u0438\u043e\u0442\u0435\u043a\u0438 PyTorch, \u043a\u043e\u0442\u043e\u0440\u044b\u0439 \u043e\u0442\u043b\u0438\u0447\u0430\u0435\u0442\u0441\u044f \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 \u043f\u043e\u0434\u0434\u0435\u0440\u0436\u0438\u0432\u0430\u0435\u043c\u044b\u0445 \u0432\u043e\u0437\u043c\u043e\u0436\u043d\u043e\u0441\u0442\u0435\u0439. \u041a\u0440\u043e\u043c\u0435 \u0442\u043e\u0433\u043e, OpenNMT \u043d\u0430 \u0431\u0430\u0437\u0435 PyTorch \u043f\u0440\u0435\u043f\u043e\u0434\u043d\u043e\u0441\u0438\u0442\u0441\u044f \u043a\u0430\u043a \u0431\u043e\u043b\u0435\u0435 [&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-106018","post","type-post","status-publish","format-standard","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.3 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