{"id":103181,"date":"2022-02-03T09:36:41","date_gmt":"2022-02-03T07:36:42","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi"},"modified":"2022-02-03T09:36:41","modified_gmt":"2022-02-03T07:36:42","slug":"deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sk\/blog\/news\/deepmind-predstavil-sistemu-mashinnogo-obucheniya-dlya-generaczii-koda-po-tekstovomu-opisaniyu-zadachi","title":{"rendered":"DeepMind predstavil syst\u00e9m strojov\u00e9ho u\u010denia na generovanie k\u00f3du na z\u00e1klade textov\u00e9ho opisu \u00falohy.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Spolo\u010dnos\u0165 DeepMind, zn\u00e1ma svojimi vyvinut\u00fdmi technol\u00f3giami v oblasti umelej inteligencie a strojov\u00e9ho u\u010denia s neur\u00f3nov\u00fdmi sie\u0165ami, ktor\u00e9 s\u00fa schopn\u00e9 hra\u0165 po\u010d\u00edta\u010dov\u00e9 a stolov\u00e9 hry na \u00farovni \u010dloveka, predstavila projekt AlphaCode. Tento projekt rozv\u00edja syst\u00e9m strojov\u00e9ho u\u010denia na generovanie k\u00f3du, ktor\u00fd je schopn\u00fd \u00fa\u010dastni\u0165 sa s\u00fa\u0165a\u017e\u00ed v programovan\u00ed na platforme Codeforces a dosahova\u0165 priemern\u00e9 v\u00fdsledky. K\u013e\u00fa\u010dovou charakteristikou tohto v\u00fdvoja je schopnos\u0165 generova\u0165 k\u00f3d v jazykoch Python alebo C++, pri\u010dom ako vstupn\u00fd text je dan\u00e9 zadanie v anglickom jazyku. <\/p>\n

Na testovanie syst\u00e9mu bolo vybran\u00fdch 10 nov\u00fdch s\u00fa\u0165a\u017e\u00ed Codeforces s viac ako 5000 \u00fa\u010dastn\u00edkmi, ktor\u00e9 sa uskuto\u010dnili po ukon\u010den\u00ed tr\u00e9ningu modelu strojov\u00e9ho u\u010denia. V\u00fdsledky vykon\u00e1vania \u00faloh umo\u017enili syst\u00e9mu AlphaCode umiestni\u0165 sa pribli\u017ene v strede rebr\u00ed\u010dka t\u00fdchto s\u00fa\u0165a\u017e\u00ed (54,3 %). Predpokladan\u00fd celkov\u00fd rating AlphaCode dosiahol 1238 bodov, \u010do zabezpe\u010duje zaradenie do Top 28 % medzi v\u0161etk\u00fdmi \u00fa\u010dastn\u00edkmi Codeforces, ktor\u00ed sa aspo\u0148 raz z\u00fa\u010dastnili s\u00fa\u0165a\u017e\u00ed v posledn\u00fdch 6 mesiacoch. Uv\u00e1dza sa, \u017ee projekt sa zatia\u013e nach\u00e1dza v po\u010diato\u010dnej f\u00e1ze v\u00fdvoja a do bud\u00facna sa pl\u00e1nuje zlep\u0161i\u0165 kvalita generovan\u00e9ho k\u00f3du, ako aj rozv\u00edja\u0165 AlphaCode smerom k syst\u00e9mom, ktor\u00e9 pom\u00e1haj\u00fa pri p\u00edsan\u00ed k\u00f3du, alebo n\u00e1strojom na v\u00fdvoj aplik\u00e1ci\u00ed, ktor\u00e9 bud\u00fa m\u00f4c\u0165 pou\u017e\u00edva\u0165 aj \u013eudia bez program\u00e1torsk\u00fdch zru\u010dnost\u00ed. <\/p>\n

V projekte sa pou\u017e\u00edva architekt\u00fara neur\u00f3novej siete \u201eTransformer\u201c v kombin\u00e1cii s met\u00f3dami vzorkovania a filtr\u00e1cie, ktor\u00e9 umo\u017e\u0148uj\u00fa generova\u0165 r\u00f4zne nepredv\u00eddate\u013en\u00e9 varianty k\u00f3du, zodpovedaj\u00face textu v prirodzenom jazyku. Po filtr\u00e1cii, klastrovan\u00ed a hodnoten\u00ed sa z vytv\u00e1ran\u00e9ho pr\u00fadu variantov vyber\u00e1 najoptim\u00e1lnej\u0161\u00ed funk\u010dn\u00fd k\u00f3d, ktor\u00fd sa n\u00e1sledne overuje na z\u00edskanie spr\u00e1vneho v\u00fdsledku (v ka\u017edej \u00falohe s\u00fa\u0165a\u017ee sa uv\u00e1dza pr\u00edklad vstupn\u00fdch \u00fadajov a zodpovedaj\u00faci v\u00fdsledok, ktor\u00fd by mal by\u0165 z\u00edskan\u00fd po vykonan\u00ed programu).

\"DeepMind<\/center> <\/p>\n

Na hrub\u00e9 tr\u00e9novanie syst\u00e9mu strojov\u00e9ho u\u010denia bola pou\u017eit\u00e1 k\u00f3dov\u00e1 z\u00e1klad\u0148a dostupn\u00e1 vo verejn\u00fdch repozit\u00e1roch GitHub. Po pr\u00edprave po\u010diato\u010dn\u00e9ho modelu sa vykon\u00e1vala f\u00e1za optimaliz\u00e1cie, realizovan\u00e1 na z\u00e1klade kolekcie k\u00f3du s pr\u00edkladmi \u00faloh a rie\u0161en\u00ed, ktor\u00e9 pon\u00fakli \u00fa\u010dastn\u00edkom s\u00fa\u0165a\u017e\u00ed Codeforces, CodeChef, HackerEarth, AtCoder a Aizu. Na tr\u00e9ning bolo celkovo vyu\u017eit\u00fdch 715 GB k\u00f3du z GitHubu a viac ako mili\u00f3n pr\u00edkladov rie\u0161en\u00ed typick\u00fdch \u00faloh z t\u00fdchto s\u00fa\u0165a\u017e\u00ed. Pred prechodom na generovanie k\u00f3du text \u00falohy prech\u00e1dzal f\u00e1zou normaliz\u00e1cie, po\u010das ktorej bolo odstr\u00e1nen\u00e9 v\u0161etko nadbyto\u010dn\u00e9 a zostali len v\u00fdznamn\u00e9 \u010dasti.

\"DeepMind<\/center>
\n
Zdroj: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f DeepMind, \u043f\u043e\u043b\u0443\u0447\u0438\u0432\u0448\u0430\u044f \u0438\u0437\u0432\u0435\u0441\u0442\u043d\u043e\u0441\u0442\u044c \u0441\u0432\u043e\u0438\u043c\u0438 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0430\u043c\u0438 \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u0438 \u0438\u0441\u043a\u0443\u0441\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u0438\u043d\u0442\u0435\u043b\u043b\u0435\u043a\u0442\u0430 \u0438 \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0445 \u0441\u0435\u0442\u0435\u0439, \u0441\u043f\u043e\u0441\u043e\u0431\u043d\u044b\u0445 \u0438\u0433\u0440\u0430\u0442\u044c \u0432 \u043a\u043e\u043c\u043f\u044c\u044e\u0442\u0435\u0440\u043d\u044b\u0435 \u0438 \u043d\u0430\u0441\u0442\u043e\u043b\u044c\u043d\u044b\u0435 \u0438\u0433\u0440\u044b \u043d\u0430 \u0443\u0440\u043e\u0432\u043d\u0435 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