InoteveraGaidhi rinotevera
Batch vs Real-Time Inference
Tekinoroji
Nhungamiro yehunyanzvi
Batch Normalization
Batch normalization inzira inodzoreredza zvinopinza kune imwe neimwe layer yeneural network panguva yekudzidziswa, ichiita yakadzika network kudzidzisa nekukurumidza uye nekuvimbika.
Teerera kugwaro iriAI-yakarondedzerwa · ~2 min
Pa peji ino2 min verenga
Pfupiso
Yakava imwe yenzira dzinoshandiswa zvakanyanya mukudzidza kwakadzama.
Kudzika Kwakadzika
Sezvo data ichiyerera kuburikidza netiweki yakadzika, kugovera kwehukoshero kudyisa imwe neimwe layer inoramba ichichinja seyekutanga maseru anogadziridza, izvo zvinononoka uye zvinokanganisa kudzidziswa. Batch normalization, yakaunzwa naIoffe naSzegedy muna 2015, inogadzirisa izvi nekugadzirisa mapindiro ega ega ega pane yazvino mini-batch kuitira kuti iite zero zvinoreva uye musiyano weyuniti. Inobva yaisa maparamendi maviri anogona kudzidziswa, gamma uye beta, iyo inoregedza network kuyera uye kushandura iyo yakajairwa tsika kumashure kana zvichibatsira, saka inorasikirwa nekumiririra simba. Mubairo wacho wakakura: network inoshivirira mwero wekufunda wepamusoro, inoungana mumakumi mashoma enguva, haina hanya nekutanga uremu, uye kazhinji inogadzirisa zvirinani. Kubata ndeyekuti maitiro anoenderana nebatch statistics, saka mabheti madiki anogona kuita kuti isagadzikane.
Kuitwa muNyika yeChokwadi
Kupinza batch zvakajairwa zvikamu muResNet mufananidzo classifier kuti igone kudzidzisa nechiyero chepamusoro chekudzidza uye kuungana munguva shoma shoma.
Kudzikamisa kudzidziswa kweiyo yakadzika convolutional network yekufungidzira yekurapa iyo yakambosiyana pasina kujaira.
Kuderedza kunzwisiswa kune uremu kutanga mune yakajairika CNN, saka mainjiniya anopedza nguva shoma-kugadzirisa nemaoko kutanga maitiro.
Kuchinja kubva pakudzidziswa-modhi yebatch statistics kuenda kuavhareji inomhanya yaavhareji paunenge uchitumira modhi kuitira kuti fungidziro yemufananidzo mumwe irambe ichienderana.
Ramangwana reBatch Normalization
Batch normalization inoramba iine bhiza rekushanda mune convolutional vision modhi, asi kuvimba kwayo nebatch statistics kunonetsa kune anodzokororwa network, madiki mabhechi, uye akagoverwa kudzidziswa. Izvo zvafambisa kutorwa kwedzimwe nzira senge layerization, iyo inojairira mukati memuenzaniso mumwechete uye ikozvino inotonga eshanduko yezvivakwa, pamwe neboka uye semuenzaniso kudzoreredza kune chaiwo madomasi. Tsvagiridzo inoenderera mberi mune yakajairika-yemahara network inoenderana nemabhenefiti ayo kuburikidza nekuchenjerera kutanga uye kuyera. Tarisira kuti normalization igare yakakosha, neiyo yakasarudzika yakasarudzwa kuti ikwane iyo dhizaini.
Kuzvishandisa
Nei zvichikosha
- Mutengo uye bhajeti. Zvisarudzo zvezvivakwa zvinotyaira kuita uye mutengo wekushandisa kwemakore.
- Sarudzo dzakajeka. Dzidzo yehunyanzvi inobatsira zvikwata kusarudza murwi wakakodzera, kwete iwo mutsva chete.
- Kudzora kwemhando yepamusoro. Sarudzo dzeinjiniya dziri nani dzinoderedza zviitiko zvekuvimbika mukugadzira.
Chenjera
- Kugadzirisa imwe bhenji kunogona kuvanza yakafara system kushaya simba.
- Infrastructure uye mari yekugadzirisa inowanzotarisirwa pasi.
- Chengetedzo uye kucherechedzwa mapundu anogona kukura sezvo masisitimu anowedzera kuoma.
Matanho anotevera
- Tsanangura latency, mhando, uye mutengo zvinangwa usati waitwa.
- Benchmark pasi pechokwadi mutoro uye data mamiriro.
- Chishandiso chekutarisa zvikanganiso, kudonha, uye mushandisi maitiro.
- Gadzirira nzira dzekudzosera kumashure uye dzezviitiko usati wawedzera.
Ramba Uchiongorora
Tsamba yemahara
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Take the Batch Normalization quiz
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Chii chinonzi Batch Normalization?
Batch normalization inzira inodzoreredza zvinopinza kune imwe neimwe layer yeneural network panguva yekudzidziswa, ichiita yakadzika network kudzidzisa nekukurumidza uye nekuvimbika. Yakava imwe yenzira dzinoshandiswa zvakanyanya mukudzidza kwakadzama.
Chii chinoita batch normalization normalize?
Batch Norm inomisikidza zvinopinza zvechitubu uchishandisa zvinoreva uye musiyano wakaverengerwa pane yazvino mini-batch, ichichengeta ma activation munzvimbo yakagadzikana apo kudzidziswa kunoenderera.
Nei batch normalization ichisanganisira inodzidziswa paramita gamma uye beta?
Mushure mekujairira kusvika ku zero zvinoreva uye musiyano weyuniti, gamma uye beta rega network idzoke uye ichinjezve hunhu kana izvo zvichibatsira, saka kujairana hakudzikisire izvo layer inogona kumiririra.
Chii chinowanzo taurwa chinobatsira chebatch normalization?
Nekuchengeta maseketi ekuiswa akanyatso kucherwa, batch tsika inoita kuti network idzidzire nemazinga akakura ekudzidza, kusanganidzana nekukurumidza, uye kusanzwa zvakanyanya nekutanga.
Panguva yekufungidzira (kufanotaura nezve data nyowani), ndedzipi nhamba dzinoshandiswa nebatch normalization?
Kushandisa live batch statistics pakunongedza kwaizoita kuti kufanotaura kunoenderana nekuti ndeupi mimwe mienzaniso inogovera batch. Panzvimbo iyoyo, batch yakajairwa inoshandisa yakamisikidzwa kumhanya mavhareji akachengetwa panguva yekudzidziswa.
Sei batch normalization ichigona kuita zvisina kunaka nemadiki madiki saizi?
Batch zvakajairika zvinoenderana nekufungidzira zvinoreva uye musiyano kubva kubhechi. Nemienzaniso mishoma, fungidziro idzodzo dzine ruzha, izvo zvinogona kukanganisa kudzidziswa.
Ramba uchidzidza
Mazano anoenderana
Mamwe madhairekitori akasarudzirwa nyaya iyi