ZeRO iyo Optimizers Sharded
ZeRO (Zero Redundancy Optimizer) waxay meesha ka saartaa isku-duubnida xusuusta wasakhda leh ee isbarbar-dhigga xogta iyadoo la kala qaybinayo gobolka wax-soo-kabiyaha, gradients, iyo miisaannada GPU-yada oo dhan.
Dulmar
Waxay kuu ogolaanaysaa inaad tababarto moodooyin aad u badan oo leh fududaynta isbarbardhigga xogta laakiin qayb ka mid ah xusuusta-GPU-da.
quusid qoto dheer
Marka la eego xogta caadiga ah, GPU kastaa wuxuu kaydiyaa nuqul buuxa oo buuxa oo ah gobolka hagaajinta, gradients, iyo xuduudaha, taas oo si weyn u khasaarinaysa, gaar ahaan Adam, halkaas oo gobolka wax-qabadku dhowr jeer ka weyn yahay qaabka laftiisa. ZeRO, oo uu soo bandhigay Microsoft gudaha DeepSpeed, waxay meesha ka saaraysaa shaqo-ka-dhimistan iyadoo loo qaybinayo kiraystayaashan GPU-yada oo dhan si qalab kastaa u yeesho jeex keliya. ZeRO waxay ku timaadaa saddex marxaladood oo horusocod ah: Marxaladda 1 shards optimizer state, Marxaladda 2 waxay ku darsataa jeexjeexid gradient ah, iyo Marxaladda 3 jeexjeexyada laftooda. Sida loo baahdo, GPU-yadu waxay ku ururiyaan xaleefyada maqan iyagoo isticmaalaya isgaarsiin, xisaabiya, ka dibna sii daaya. Natiijadu aad bay u hoosaysaa xusuusta GPU kasta, taasoo awood u siinaya bilyan- ilaa trillion-tababarka cabbirka, iyadoo la ilaalinayo qaabka barnaamijka fudud ee isbarbardhigga xogta.
Aragtida Farsamada
ZeRO waxa ay ka baayacmushtartaa isgaarsiin dheeraad ah oo kaydinta xusuusta ah. Marxaladda 3, kahor gudbinta lakabka, dhammaan-ururinta waxay ururiyaan xuduudaha lakabka buuxa ee GPU kasta; ka dib jeexyada aan la iska lahayn waa la tuuraa si loo soo celiyo xusuusta. Gradients waa la yareeyay-kala firdhiyey sidaa darteed GPU kastaa wuxuu hayaa kaliya jajabka gradient ee u dhigma cabbirrada uu isagu leeyahay. PyTorch's FSDP (Fullly Sharded Data Parallel) waxay u fulisaa isla fikradda asal ahaan, iyada oo ku duuduubaysa qaybo si ay u jeexjeexdo oo dib ugu shaandheyso duulista.
Saamaynta Istiraatijiyadeed
Qiimaha iyo miisaaniyada
Go'aamada qaab-dhismeedku waxay horseedaan waxqabadka iyo kharashka hawlgalka sannadaha.
Go'aamo cad
Waxbarashada farsamada waxay ka caawisaa kooxaha inay doortaan xidhmo sax ah, ma aha oo kaliya kan ugu cusub.
Xakamaynta tayada
Doorashooyinka injineernimada ee wanaagsan waxay yareeyaan shilalka la isku halleyn karo ee wax soo saarka.
Mustaqbalka ZeRO iyo Hagaajinta Sharded
Sharding waxa ay noqonaysaa meesha ugu saraysa ee tababbarka baaxada leh ee aan ahayn ikhtiyaar qalaad. Filo is dhex galka qoto dheer ee soo dejinta (ku riixida xaleefyada CPU ama NVMe iyada oo loo sii marayo ZeRO-Infinity), isku dhafka wanaagsan ee dhammaan-ururinta oo yareeya-kala firdhiso xisaabinta si ay u qariyaan kharashkooda, iyo isku-darka tensor iyo isbarbardhigga dhuumaha. Sida moodellada ay u sii kordhayaan, hagaajineyaasha jeexjeexan ee xusuusta waxtarka leh ayaa udub dhexaad u ah in lagu rakibo miisaaniyadaha qalabka dhabta ah.
Dhaqangelinta Adduunka-dhabta ah
Isticmaalka DeepSpeed Zero Stage 2 si aad u hagaajisid qaabka luqadaha balaayiin-halbeeg ah oo haddii kale buux dhaafin lahaa xusuusta GPU.
Tababarka PyTorch FSDP, kaas oo jeexjeexaya cabbirrada, gradients, iyo hagaajinta guud ahaan GPU-yada oo ururiya lakab kasta marka loo baahdo.
Codsashada ZeRO-Offload si loogu riixo hagaajinta gobolka xusuusta CPU, u oggolaanaysa hal GPU inuu tababaro nooc marar badan ka weyn VRAM-kiisa.
Isku-dubbarididda moodal-halbeeg-trillion-ka ah oo leh ZeRO-Infinity iyadoo la dhex-gudbinayo jaangooyooyinka cabbirka kaydinta NVMe marka xusuusta GPU iyo CPU ay dhammaato.
Khatarta & Dariiqyada Ilaalada
Hagaajinta hal bartilmaameed waxay qarin kartaa daciifnimada nidaamka ballaaran.
Kaabayaasha dhaqaalaha iyo dayactirka inta badan waa la dhayalsadaa.
Nabadgelyada iyo daldaloolada u fiirsashada ayaa kori kara marka nidaamyadu noqdaan kuwo aad u adag.
Qorshe Hawleedka Dhaqangelinta
Qeex daahida, tayada, iyo bartilmaameedyada qiimaha ka hor inta aan la hirgelin.
Benchmark marka la eego culeyska dhabta ah iyo xaaladaha xogta.
La socodka qalabka khaladaadka, leexashada, iyo saamaynta isticmaalaha.
U diyaari dib-u-noqoshada iyo dariiqyada jawaab-celinta dhacdada ka hor inta aanad miisaan.
Sii wad Sahaminta
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Hagaha xiga
Lookahead iyo Lion Optimizers
Su'aalaha soo noqnoqda
Waa maxay ZeRO iyo Shaarded Optimizers?
ZeRO (Zero Redundancy Optimizer) waxay meesha ka saartaa isku-duubnida xusuusta wasakhda leh ee isbarbar-dhigga xogta iyadoo la kala qaybinayo gobolka wax-soo-kabiyaha, gradients, iyo miisaannada GPU-yada oo dhan. Waxay kuu ogolaanaysaa inaad tababarto moodooyin aad u waaweyn oo leh fududaynta isbarbardhigga xogta laakiin qayb ka mid ah xusuusta GPU-daba.
Waa maxay dib-u-celinta ZeRO marka la barbar dhigo isbarbardhigga xogta cad?
Isbarbardhigga xogta caadiga ah waxay ku kaydisaa koob buuxa oo ah xaalad wanaajinta, gradients, iyo miisaan GPU kasta; ZeRO jeexan kuwan si GPU kastaa u haysto jeex kaliya.
Waa maxay sababta ay optimizer state inta badan u tahay hog xusuusta ugu weyn ee Adam?
Aadam waxa uu ilaaliyaa qiyaasaha socodsiinta sida daqiiqadaha koowaad iyo labaad halkiibeeg kasta, kaas oo lagu daray fp32 miisaannada sayidku waxay dhumin karaan cabbirka moodeelka.
Waa maxay jeexjeexyada ZeRO Stage 3 ee heerarka 1 iyo 2 aysan samaynin?
Marxaladda 1 shards ee hagaajinta gobolka, Marxaladda 2 waxay ku darsataa gradients, iyo Marxaladda 3aad waxay sii socotaa iyadoo la kala qaybinayo cabbirrada moodalka guud ahaan GPU-yada sidoo kale.
Marxaladda ZeRO 3, sidee buu GPU-gu u helayaa cabbirrada buuxa ee uu uga baahan yahay gudbinta lakabka?
Ka hor inta aan la xisaabin lakabka, dhammaan-ururiyuhu wuxuu ururiyaa cabbiraadkiisa buuxa ee GPU kasta; marka la sameeyo, jeexjeexyada aan la iska lahayn ayaa xor u ah inay dib u soo ceshadaan xusuusta.
Waa kuwee astaanta PyTorch ee asal ahaan u fulisa shaxaynta qaabka ZeRO?
PyTorch's Fully Sharded Data Parallel (FSDP) jeexjeexyada jaangooyooyinka, jaranjarada, iyo hagaajinta gobolka, ururinta iyo dib u habaynta iyaga oo duulaya, oo eegaya ZeRO.