Ntụlegharị gradient
Ntụle nlele gradient (nke a na-akpọkwa nlele ọrụ ọrụ) bụ aghụghọ na-echekwa ebe nchekwa na-atụfu ọtụtụ mmemme n'etiti n'oge ngafe na-aga n'ihu ma na-atụgharị ha na ofufe n'oge mgbasa ozi.
Nchịkọta
It lets you train deeper, larger networks by trading extra compute for much lower memory use.
Ime miri emi
Ọzụzụ netwọkụ akwara ozi na-echekwa ihe mmemme oyi akwa ọ bụla n'oge ngafe n'ihi na mgbasa ozi chọrọ ka ha gbakọọ gradients. Maka ụdị miri emi, mmemme ndị a na-achịkwa ebe nchekwa. Ntụle nlele gradient na-echekwa naanị n'ọkwa dị obere nke 'ebe nlele' wee tụfuo ndị ọzọ. Mgbe backprop rutere mpaghara nke ewepụrụ ọrụ ya, ọ na-emegharị nhazigharị n'ihu maka naanị akụkụ ahụ iji megharia ihe ọ chọrọ, wee gaa n'ihu. N'iji ebe nlele etinyere n'ogo square-root-of-N ọ bụla, ebe nchekwa maka ọrụ na-adaba n'usoro N iji tụọ square-root-of-N, ebe ịgbakọ na-ebili naanị ihe dị ka otu ngafe na-aga n'ihu (ihe dịka 20-30% ji nwayọ nwayọ). Nke a na-eme ka o kwe omume ịkwado nnukwu batch nha ma ọ bụ ntụgharị dị omimi n'otu GPU.
Nghọta nka nka
Usoro a na-eji oge-na-echefu echefu ahia. Ịchekwa mmemme niile na-adị ngwa ngwa mana ebe nchekwa-agụụ; recomputing ha dị ọnụ ala na oge accelerators ikwu na-eri nke na-agba ọsọ nke ebe nchekwa. Frameworks dị ka PyTorch (torch.utils.checkpoint) kechie modul ka e wee chekwaa ihe nrụpụta ya mana a na-agụgharị ihe ntinye ya n'oge azụ. Ịhọrọ ebe nleba anya ihe dị mkpa: ọbụna oghere nke akụkụ sqrt(N) na-ebelata mkpokọta ebe nchekwa ma na-agbakwunye naanị otu ngafe n'ihu nke gbakọọ mkpokọta.
Mmetụta atụmatụ
Ọnụ ego na mmefu ego
Mkpebi ihe owuwu ụlọ na-akwalite arụmọrụ yana ọnụ ahịa ọrụ ruo ọtụtụ afọ.
Mkpebi doro anya
Nkà mmụta nka na-enyere ndị otu egwuregwu aka ịhọrọ nchịkọta ziri ezi, ọ bụghị naanị nke kachasị ọhụrụ.
Quality akara
Nhọrọ injinia ka mma na-ebelata ihe omume ntụkwasị obi na mmepụta.
Ọdịnihu nke nyocha nyocha gradient
Ntụle nlele gradient bụ ọkọlọtọ ugbu a na ọzụzụ ụdị nnukwu ma na-abawanye na akpaghị aka, yana ụlọ akwụkwọ ọbá akwụkwọ na-ahọpụtara gị ebe nlele kacha mma. Ọ na-ejikọta ya na FSDP, nkenke agwakọta, na mbugharị iji kwalite nha ụdị dị elu. Na-atụ anya nlele nlele 'ahọpụtara' nke na-akwụghachi naanị ọrụ dị ọnụ ala ka ị na-edobe ndị dị oke ọnụ (dị ka matrices nlebara anya) cache, gbakwunyere usoro ndị na-achịkọta ihe na ngwaọrụ dị ka PyTorch's torch.compile nke na-ekpebi ozugbo ihe ị ga-echekwa vesos recompute maka nguzozi ọsọ-ọsọ kacha mma.
Mmejuputa n'ezie n'ụwa
Ịzụ ihe ngbanwe dị omimi nke nwere nnukwu batch na otu GPU site na ịtụfu na ịgbakọ ọrụ oyi akwa.
Ụdị ọhụụ na-emezigharị nke ọma na onyonyo dị elu ebe maapụ ịgbalite ga-ejupụta ebe nchekwa GPU.
Ịmakụ ndị na-agbanwe ihu na-enyere gradient_checkpointing=Ezigbo dabara ụdị ijeri paramita n'oge a na-emegharị mma.
Ijikọ nlele na FSDP ka edobere ma paramita na mmemme dị obere, na-enye ọzụzụ nke ụdị asụsụ buru ibu.
Ihe ize ndụ & okporo ụzọ nche
Ịkwalite otu akara ngosi nwere ike zoo adịghị ike sistemụ sara mbara.
A na-eledakarị ihe akụrụngwa na ụgwọ ọrụ anya.
Ọdịiche nchekwa na nleba anya nwere ike itolite ka sistemu na-adịwanye mgbagwoju anya.
Map mmejuputa
Kọwaa latency, ịdịmma na ebumnuche ọnụ ahịa tupu mmejuputa ya.
Benchmark n'okpuru ibu dị adị na ọnọdụ data.
Nleba anya akụrụngwa maka mperi, ịkpafu na mmetụta onye ọrụ.
Kwadebe ụzọ nzaghachi azụghachi azụ na ihe omume tupu ịchachaa.
Nọgide na-eme nchọpụta
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Ntuziaka na-esote
Mkpokọta gradient
Ajụjụ a na-ajụkarị
What is Gradient Checkpointing?
Ntụle nlele gradient (nke a na-akpọkwa nlele ọrụ ọrụ) bụ aghụghọ na-echekwa ebe nchekwa na-atụfu ọtụtụ mmemme n'etiti n'oge ngafe na-aga n'ihu ma na-atụgharị ha na ofufe n'oge mgbasa ozi. Ọ na-enye gị ohere ịzụ netwọk miri emi, nke buru ibu site na ịzụ ahịa mgbakwunye maka iji ebe nchekwa dị ala.
Kedu ihe nlele gradient na-azụ ahịa bụ isi iji chekwaa ebe nchekwa?
Ntụle nyocha nke gradient na-atụgharị ọrụ ndị a tụfuru n'oge ngafe azụ azụ, na-emefu mkpirisi maka mgbanwe maka ebe nchekwa belatara nke ukwuu.
Kedu ihe kpatara eji echekwa mmemme n'oge ngafe mbugharị?
Backprop na-agbakọ gradients na-eji mmemme etiti sitere na ngafe mbugharị, yabụ na ha ga-adịrịrị ma ọbụghị na agbakọghachiri ha.
Kedu ka ebe nchekwa ịgbalite ga-esi arụ ọrụ ma ọ bụrụ na edobere ebe nlele ọ bụla n'ígwé sqrt(N) na netwọk N-layer?
Ebe nleba anya n'ọkpụkpụ n'ọkwa square-root-of-N ọ bụla na-ebelata ebe nchekwa ọrụ echekwabara site n'usoro N ruo ịtụ sqrt(N).
Odika ngụkọ ole ka nlebanya gradient edobere nke ọma na-agbakwunye?
Site n'itinye ebe nlele dị mma, ihe dị n'elu bụ ihe dị ka otu ngafe na-aga n'ihu, na-abụkarị ihe dịka 20-30%.
Na PyTorch, kedu akụrụngwa a na-ejikarị etinye nlele gradient na modul?
torch.utils.checkpoint na-ekechi modul ka a na-atụgharịghachi ọrụ ime ya n'oge azụ kama ịchekwa ya.