Overview
Neural Architecture Search (NAS) inogadzirisa dhizaini yeneural network zvimiro - kurega algorithms, kwete vanhu, kusarudza kuti mangani akaturikidzana, ndeapi mashandiro, uye kuti anobatana sei. Inoshandura dhizaini yemhando kuita dambudziko rekutsvaga, kuwana zvivakwa zvinogona kukwikwidza kana kurova zvakagadzirwa nemaoko.
Neural Architecture Search inogara mukati meiyo AI toolkit. Paunonzwisisa, mamwe maAI misoro inova nyore kuongorora uye kuenzanisa.
Deep Dive
Kugadzira neural network nemaoko kunononoka uye kunovimba nenyanzvi intuition. NAS inotsiva iyo nekutsvaga pamusoro penzvimbo yakatsanangurwa yezvivakwa zvinogoneka, inotungamirwa nezano rinokurudzira vamiriri uye nzira yekufungidzira kuti imwe neimwe yakanaka sei. Yekutanga NAS yakashandisa kusimbisa kudzidza kana shanduko algorithms, kudzidzisa zviuru zvevamiriri network - zvine mukurumbira kudhura zviuru zveGPU-mazuva. Kubudirira kwacho kwaive kuita kuti kutsvaga kudhure: kugovana uremu ('supernet' ine vese vavhoti) uye nzira dzinosiyanisa seDARTS, iyo inozorodza sarudzo dzakajeka mune dzinoramba dzichienderera kuitira kuti gradient descent igone kukwirisa zvivakwa uye uremu pamwechete. NAS yakagadzira mamodheru anoshanda seEfficientNet uye akati wandei-akagadziridzwa nharembozha dzave kushandiswa mukugadzira.
Technical Insight
NAS ine zvikamu zvitatu: nzvimbo yekutsvaga (zvivharo zvekuvaka uye kuti vangabatana sei), nzira yekutsvaga (kusimbisa kudzidza, kushanduka, kutsvaga kwekutsvaga, kana gradient-based), uye nzira yekufungidzira maitiro. Naively kudzidzisa mukwikwidzi wega wega kuchinjika kunodhura zvisingaite, saka NAS inoshandisa mapfupi: kugovana uremu pane supernet, yakaderera-kutendeseka proxies (shoma epoch, diki data), uye vakadzidza kufanotaura. DARTS inoita sarudzo yakasarudzika yekuti 'iyo oparesheni inoenda pano' inoenderera kuburikidza nesoftmax-yakayerwa musanganiswa, inokwidziridza nemagradients, yobva yaratidza mhedzisiro mukuvaka kwekupedzisira.
Mastering Neural Architecture Search
Neural Architecture Search (NAS) inogadzirisa dhizaini yeneural network zvimiro - kurega algorithms, kwete vanhu, kusarudza kuti mangani akaturikidzana, ndeapi mashandiro, uye kuti anobatana sei. Inoshandura dhizaini yemhando kuita dambudziko rekutsvaga, kuwana zvivakwa zvinogona kukwikwidza kana kurova zvakagadzirwa nemaoko. Neural Architecture Search inogara mukati meiyo AI toolkit. Paunonzwisisa, mamwe maAI misoro inova nyore kuongorora uye kuenzanisa. Kuti uvake kunzwisisa kwakadzama, bata Neural Architecture Search semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvaunoda mhedzisiro, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Neural Architecture Search zvinovaka mamodheru akasimba ekutanga, wozoisa mepu iwo mamodheru kune zvipingaidzo chaizvo zvekugadzira. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Inokubatsira kuparadzanisa zvakajeka zvichemo zvehunyanzvi kubva mumutauro wekushambadzira. Panguva imwecheteyo, Zvikwata zvakasiyana zvinogona kushandisa izwi rimwechete zvakasiyana, saka tsanangura nzvimbo nekukasira. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Inokubatsira kuparadzanisa zvakajeka zvichemo zvehunyanzvi kubva mumutauro wekushambadzira.
Inokubatsira kuparadzanisa zvakajeka zvichemo zvehunyanzvi kubva mumutauro wekushambadzira. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Iwe unogona kubvunza zvirinani kuita mibvunzo usati washandisa mari kana nguva.
Iwe unogona kubvunza zvirinani kuita mibvunzo usati washandisa mari kana nguva. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvine nzwisiso yakagovaniswa inoita zvirinani chigadzirwa, mutemo, uye sarudzo dzekudzidza.
Zvikwata zvine nzwisiso yakagovaniswa inoita zvirinani chigadzirwa, mutemo, uye sarudzo dzekudzidza. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Google's EfficientNet mhuri, ine zvivakwa zvakasanganiswa zvakatungamirwa nekutsvaga otomatiki kwechokwadi kwakasimba-per-FLOP.
Mobile vision modhi (seMnasNet) yakatsvaga ne latency parunhare chairwo mu loop yekumhanyisa pa-mudziyo.
Hardware-inoziva NAS iyo inogadzira network kune chaiyo accelerator ndangariro uye compute miganho.
AutoML mapuratifomu anoita kuti vasiri nyanzvi vawane inokwikwidza tsika modhi nekutsvaga zvivakwa otomatiki.
Maitiro Ekuita
Neural Architecture Tsvaga mukuita
Google's EfficientNet mhuri, ine zvivakwa zvakasanganiswa zvakatungamirwa nekutsvaga otomatiki kwechokwadi kwakasimba-per-FLOP.
Google's EfficientNet mhuri, ine maumbirwo akaumbwa akatungamirirwa nekutsvaga otomatiki kwechokwadi kwakasimba-per-FLOP Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura hunhu hwemberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Neural Architecture Tsvaga mukuita
Mobile vision modhi (seMnasNet) yakatsvaga ne latency parunhare chairwo mu loop yekumhanyisa pa-mudziyo.
Mamodheru ekuona mamodheru (akadai seMnasNet) akatsvaga ne latency parunhare chairwo mulop ye-on-mudziyo kumhanya Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye kukanganisa mutengo nekufamba kwenguva.
Neural Architecture Tsvaga mukuita
Hardware-inoziva NAS iyo inogadzira network kune chaiyo accelerator ndangariro uye compute miganho.
Hardware-inoziva NAS iyo inogadzira network kune chaiyo yekumhanyisa ndangariro uye compute miganho Matimu anowanzo kuwana zvirinani zvibodzwa kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Neural Architecture Tsvaga mukuita
AutoML mapuratifomu anoita kuti vasiri nyanzvi vawane inokwikwidza tsika modhi nekutsvaga zvivakwa otomatiki.
AutoML mapuratifomu anoita kuti vasiri nyanzvi vawane yemakwikwi emhando yemhando nekutsvaga zvivakwa otomatiki Matimu anowanzo kuwana mibairo iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Zvikwata zvakasiyana zvinogona kushandisa izwi rimwechete zvakasiyana, saka tsanangura nzvimbo nekukurumidza.
Benchmarks inogona kutaridzika yakasimba nepo chaiyo-yenyika kuita isina kuenzana.
Kuregeredza mhando yedata uye zvirongwa zvekuongorora zvinowanzogadzira mhedzisiro isina kusimba.
Implementation Roadmap
Tanga netsanangudzo yemutauro wakajeka yemhedzisiro yaunoda.
Tanga netsanangudzo yemutauro wakajeka yemhedzisiro yaunoda. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Sarudza metric imwe yekubudirira uye imwe yekutadza mamiriro usati waedzwa.
Sarudza metric imwe yekubudirira uye imwe yekutadza mamiriro usati waedzwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Mhanya mutyairi mudiki ane data remumiriri, kwete demo rakakwenenzverwa.
Mhanya mutyairi mudiki ane data remumiriri, kwete demo rakakwenenzverwa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Gwaro uko Neural Architecture Kutsvaga kunobatsira uye uko nzira dzakareruka dziri nani.
Gwaro uko Neural Architecture Kutsvaga kunobatsira uye uko nzira dzakareruka dziri nani. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.