Reseau autoroute yi ak lëkkaloo yi
Skip connections yi dañuy may xibaar yi ñu romb ay layer, te reso otorout yi nekkoon nañu xeetu gated bu njëkk ci xalaat bii.
Résumé
They solve the problem of training very deep networks, which paved the way for ResNets and modern deep learning.
Plongeur bu xóot
Laata ñuy salte lëkkaloo yi, dajale ay couche yu bari dafa tax reso yi gëna tar, baña gëna baax, ngir tàggat ndax gradient yi dañu ni mes, siñaal yi dañu yàqu. Reseau otorout yi, yuñ dugal ci 2015, yokk nañu ay buntu yuñ jàng ngir saytu ba ñaata layer lañuy soppi wala ñu koy yóbbu ci yoon wu jub, inspiré ci LSTM gating. Ginaaw loolu yàggul dara, ResNets yombal lii ci lëkkaloo residuel, fu benn couche jàng benn fonction residuel ba noppi ñu yokk limu génne ci limu dugal jaaraleko ci gaawaayu dàntite. Gaawaay yooyu dañuy defar yoon yu jub ngir gradient yi mëna dellu ginaaw, loolu mooy tax ñu mëna tàggat reso yu am téemeeri wala sax junni couche yu xóot. Leegi lëkkalekaay yi dañuy feeñ fépp, lu ci melni U-Nets, DenseNets, ak trafo.
Gis-gis xarala
Bloc residuel dafay xayma génne = F(x) + x, kon reso bi soxla jàng residual F(x) rek moo gën jàng mapping bi yépp. Ci jamonoy backpropagation, terme dàntite biy yokk dafay jaar ci gradient yi te duñu soppiku, di moytu gradient yiy réer. Reseau otorout yi dañuy yamale lii ci buntu soppiku T ak buntu yóbbu, genn = F(x)*T(x) + x*(1 - T(x)), fu ñuy jàngee T te tollu ci diggante 0 ak 1.
njeextalu pexe
Njëgg ak budget
Dogal yi architecture di jël dañuy indi njariñ ak njëgu liggéey bi ay at ci ginaaw.
dogal yu gëna leer
Njàngalem xarala yi dafay jàppale ekip yi ñu tànn li gën, te baña yam ci li gëna bees daal.
Xool kalite
Tanneef yu gëna baax ci wàllu ingeñër dina wàññi jafe-jafe yi ci wàllu wóor ci liggéey bi.
Ëlëgu reso yu mag yi ak lëkkaloo yi
Lëkkaloo yi ñuy sànni leegi dañuy nekk bloku tabax buñ jagleel, duñu ay pexe yuñ mëna tànn. Bépp transformatër dafay jëfandikoo lëkkaloo yu des ci wàllu bàyyi xel ak feed-forward sublayers, te dañuy wéy di am solo ci xeetu diffusion, segmentation U-Nets, ak reso graph. Gëstu dafay jàngat plasement normalisasioŋ bu gëna baax, eskalaasioŋ buñ mëna jàng ci yooni residual yi, ak architecture yuñ mëna delloosi yuy xaymawaat aktivaasioŋ yi ngir denc mémoire bi. Li gëna am solo mooy ñu baña yàq siñaal bi ci xóotaayu suuf si, dina wéy lu model yi di màgg.
Doxal ci àdduna dëgg
ResNet-50 ak ResNet-152 dañuy jëfandikoo ay gaawaay yu des ngir tàggat ay nataal yu xóot lool
Transformatër yi ak xeetu làkk yu yaatu yi dañuy wër lëkkaloo yi des ci wàllu bàyyi xel ak feed-forward
Lëkkaloo U-Net dafay jaar ci ay detay yu baax ci barab bi, daale ko ci enkodeer bi dem ci dekodeer bi ngir am nataalu pajum bu jaar yoon
DenseNet dafay boole couche bu nekk ak couche yi ci topp, di ñaax nit ñi ñu jëfandikoowaat man-man yi ak yombal debit gradient bi
Risk yi ak balustrade yi
Optimize benn benchmark mën na nëbb ñakk kattan yu gëna yaatu ci sistem bi.
Njëg li ñuy fay ci infrastructure yi ak ci toppatoo dañuy faral di suufeel.
Bu sistem yi di gëna xawa jafee xam, jafe-jafe yi am ci wàllu kaaraange ak seetlu mën nañu gëna bari.
Roadmap ngir samp gi
Mandargal latency, kalite, ak njëg yi laata ngay jëfandikoo.
Benchmark ci biir sargal ak done yu dëggu.
Jumtukaay bi di saytu njuumte yi, derive bi ak njeextalu jëfandikukat bi.
Waajal rollback ak yooni tontu ci jafe-jafe yi laata ngay eskale.
Weyal di banneexu
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Gis bi ci topp
Reseau Siamese ak ñàkka am ñatti doom
Laaj yi ñuy faral di laaj
What is Highway Networks and Skip Connections?
Skip connections yi dañuy may xibaar yi ñu romb ay layer, te reso otorout yi nekkoon nañu xeetu gated bu njëkk ci xalaat bii. Dañuy saafara jafe-jafe tàggat reso yu xóot lool, loolu moo ubbi yoonu ResNets ak jàng bu xóot bu bees.
Ban jafe-jafe bu mag la skip connections di jàppale ci saafara ci reso yu xóot lool yi?
Soo joxee yoon yu jub, skip lëkkaloo yi may gradient yi ak siñaal yi ñu jaar ci stack yu xóot yi, tax reso yu xóot yi mëna tàggat.
Luy xayma ab bloku residual bu yomb?
Benn bloku residuel dafay yokk duggal x ci gennup buñ soppi F(x), kon couche bi dafay jàng residual bi kese.
Lan moo inspiré mecanisme gating bi ci reso otoroute yi?
Reseau otorout yi leble nañu xalaatu buntu yiñ jàngee ci LSTM yi ngir saytu ba ñaata xibaar lañuy soppi ak ñaata lañuy jaar.
Ci biir reso otorout, lan la buntu transformaasioŋ T(x) di doxal?
Lépp luy génn mooy F(x)*T(x) + x*(1 - T(x)), kon T mooy dogal ekilibre bi am ci digganté soppi ak yóbbu liñu dugal.
Ban architecture bu bees moo sukkandiko ci lëkkaloo yi des ci biir ay sous-couche?
Transformatër yi dañuy def lëkkaloo yu des ci seen biir ak seen feed-forward sublayers ci jëmmal buñ miin.