Model AI oo hufan u geynaya Aaladaha Edge iyada oo loo sii marayo Nakhshad wadaagga Hardware-Software | B4N1

Model AI oo hufan u geynaya Aaladaha Edge iyada oo loo sii marayo Nakhshad wadaagga Hardware-Software

7 months ago · b4n1 Read time: 4 min

** Qaabka AI ee wax ku ool ah u geynta Aaladaha Edge iyada oo loo sii marayo Naqshad Wadashaqaynta Software-Software ***

hordhac

Fidinta aaladaha cidhifyada ayaa abuuray fursado cusub codsiyada Sirdoonka Artificial (AI) in la geeyo wakhtiga dhabta ah, taas oo awood u siinaya codsiyada sida guryaha smart, baabuurta madax-bannaan, iyo qalabaynta warshadaha. Si kastaba ha noqotee, ilaha xisaabinta xaddidan iyo caqabadaha awoodda aaladaha cidhifyada ayaa caqabado muhiim ah u ah keenista moodalka AI. Maqaalkan, waxaan ku baari doonaa isgoysyada AI, injineernimada softiweerka, iyo qaab dhismeedka si aan u wanaajino waxqabadka aaladda geesaha, ka faa'ideysiga horumarkii ugu dambeeyay ee hufnaanta moodalka AI iyo farsamooyinka naqshadeynta qalabka-software.

** Caqabadaha ka jira Gelitaanka Model AI ee Aaladaha Edge ***

Aaladaha Edge waxa lagu gartaa agabkooda xisaabeed ee xaddidan, oo ay ku jiraan CPU, xusuusta, iyo isticmaalka awoodda. Moodooyinka AI ee dhaqameed, kuwaas oo inta badan loogu talagalay geynta daruuraha ku salaysan, looma hagaajin qalabka cidhifyada. Natiijo ahaan, waxay keeni karaan:

  • ** Hoos u dhaca waxqabadka ***: Moodooyinka AI waxaa laga yaabaa inaysan si hufan ugu socon aaladaha geesaha, taasoo horseedaysa waqtiyo jawaab celin oo gaabis ah iyo hoos u dhac sax ah.
  • ** Isticmaalka tamarta ***: Moodooyinka AI waxay cuni karaan awood muhiim ah, taas oo walaac ku noqon karta aaladaha geesaha ku shaqeeya ee batteriga ku shaqeeya.
  • ** Caqabadaha xusuusta ***: Moodooyinka AI waxay u baahan karaan xaddi badan oo xusuusta ah, taas oo caqabad ku noqon karta aaladaha cirifka leh ee leh ilaha xusuusta xaddidan.

** Farsamooyinka Nakhshad Wadaagga Qalabka-Software ***

Si wax looga qabto caqabadahan, farsamooyinka isku-hawlgalayaasha hardware-software ayaa u soo baxay xal rajo leh. Farsamooyinkani waxay ku lug leeyihiin naqshadaynta labadaba qalabka iyo qaybaha software ee qalabka cidhifyada ee tandem, iyaga oo u wanaajinaya geynta moodalka AI.

1. Goynta moodalka

Goynta moodelku waxay ku lug leedahay ka saarista miisaanka iyo isku xirka aan loo baahnayn ee qaabka AI, yaraynta cabbirkeeda iyo shuruudaha xisaabinta. Farsamadan waxaa lagu dabaqi karaa labadaba shabakadaha neerfaha iyo geedaha go'aanka.

`` Python soo dejinta toosh soo dejinta toosh.nn sida nn

fasalka ModelPruning(nn.Module): iska ilaali init (nafta): super (ModelPruning, self).init() self.fc1 = nn.Linear(784, 128) self.fc2 = nn.Linear(128, 10)

hore u dhac (naftiisa, x):
    x = toosh.relu (self.fc1 (x))
    x = is.fc2 (x)
    soo noqo x

model = ModelPruning () pruned_model = torch.nn.utils.prune_l1_unstructured (qaabka, 'miisaanka', 0.1) ``

**2. Faafinta Aqoonta ***

Faafinta aqoonta waxay ku lug leedahay ka wareejinta aqoonta qaab weyn oo AI ah oo adag una gudbisa mid yar, ka fudud. Farsamadan waxaa loo isticmaali karaa si loo yareeyo cabbirka iyo shuruudaha xisaabinta ee qaabka AI.

`` Python soo dejinta toosh soo dejinta toosh.nn sida nn

Qaybinta Aqoonta fasalka (nn.Module): iska ilaali init (nafta): super (KnowledgeDistillation, self).init() self.fc1 = nn.Linear(784, 128) self.fc2 = nn.Linear(128, 10)

hore u dhac (naftiisa, x):
    x = toosh.relu (self.fc1 (x))
    x = is.fc2 (x)
    soo noqo x

macalin_model = ModelPruning() student_model = Aqoonta Distillation () ``

3. Tirada

Tiro-ururinta waxay ku lug leedahay dhimista saxnaanta miisaanka moodada AI iyo hawlgelinta, yaraynta shuruudaha xisaabinta ee moodalka AI.

`` Python soo dejinta toosh soo dejinta toosh.nn sida nn

Xisaabinta fasalka(nn.Module): iska ilaali init (nafta): super (Quantization, self).init() self.fc1 = nn.Linear(784, 128) self.fc2 = nn.Linear(128, 10)

hore u dhac (naftiisa, x):
    x = toosh.relu (self.fc1 (x))
    x = is.fc2 (x)
    soo noqo x

model = ModelPruning () quantized_model = torch.quantization.quantize_dynamic (model, {torch.nn.Linear}, dtype=torch.qint8) ``

** 5-10ka ugu sarreeya amarada/Qodobka ugu Isticmaalka badan**

Taliska/ Qaybi Sharaxaada
torch.nn.utils.prune_l1_aan habaysan(qaabka, 'miisaanka', 0.1) Model manjooyin iyadoo la isticmaalayo joogtaynta L1
torch.Quantization.quantize_dynamic(model, {toosh.nn.Linear}, dtype=tooshka.qint8) Xisaabinta iyadoo la isticmaalayo xisaabin firfircoon
torch.nn.utils.kldistance (qaabka macalinka, qaabka_ardayga) Faafinta aqoonta iyadoo la adeegsanayo kala duwanaanshaha KL
torch.nn.utils.miisaanka_caadiga ah(model.fc1) Caadiyan miisaanka iyadoo la isticmaalayo heerka miisaanka
torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0) Goynta gradient iyadoo la isticmaalayo clip grad normal
torch.nn.utils.clip_grad_value_(model.parameters(), 1.0) Goynta gradient iyadoo la isticmaalayo clip grad qiimaha
torch.nn.utils.saar_culayska caadiga ah(model.fc1) Ka-saarista miisaanka caadiga ah iyadoo la isticmaalayo ka saarida heerka miisaanka
torch.nn.utils.fuse_conv_bn_eval(model.fc1) Fiyuuska lakabka iswaafaqsan iyadoo la isticmaalayo fuse conv bn eval
torch.nn.utils.fuse_bn_eval(model.fc2) Fiyuuska caadiga ah ee Dufcada iyadoo la isticmaalayo fuse bn eval
torch.nn.utils.fuse_bn_eval(model.fc1) Fiyuuska caadiga ah ee Dufcada iyadoo la isticmaalayo fuse bn eval

Muuqaalka

shaxda { "type": "bar", "xogta": { "labels": ["Model Puning", "Knowledge Distillation", "Quantization"], "datasets": { "label": "Saaxsanaan", "xogta": [0.9, 0.85, 0.8] } }, "ikhtiyaar": { "ciwaan": { "muujin": run, "text": "Isbarbardhigga Saxda ah" }, "halyeey": { "muujin": run } } }

** Gabagabo**

Moodeelka AI ee wax ku oolka leh ee geynta aaladaha cidhifyada waxay u baahan tahay isku darka qalabka iyo farsamooyinka naqshadaynta software. Goynta moodeelka, kala-soocidda aqoonta, iyo qiyaasiddu waa qaar ka mid ah farsamooyinka loo isticmaali karo si loo yareeyo cabbirka iyo shuruudaha xisaabinta ee moodooyinka AI. Iyaga oo ka faa'iidaysanaya farsamooyinkan, horumariyayaashu waxay abuuri karaan moodooyinka AI ee loo habeeyay aaladaha cidhifyada, awood u siinaya codsiyada waqtiga-dhabta ah sida guryaha smart, baabuurta madaxbannaan, iyo automation warshadaha.

Shaqada mustaqbalka

Shaqada mustaqbalka ee aaggan waxaa ka mid ah:

  • ** Horumarinta farsamooyinka cusub ee naqshadaynta hardware-software ***: Cilmi-baarayaasha iyo horumariyayaashu waxay sahamin karaan farsamooyin cusub oo lagu wanaajinayo moodooyinka AI ee aaladaha cidhifyada.
  • ** Hagaajinta manjooyinka moodeelka iyo algorithms-ka-wareejinta aqoonta ***: Samaynta algorithms wax ku ool ah oo loogu talagalay manjooyinka moodeelka iyo leexinta aqoonta waxay u horseedi kartaa waxqabad wanaagsan iyo saxsanaan. ** Baarista isticmaalka moodooyinka kale ee AI ***: Moodooyinka kale ee AI, sida geedaha go'aannada iyo kaymaha random, waxaa lagu sahamin karaa geynta qalabka geesaha.

Adigoo sii wadida horumarinta qaybta naqshadaynta qalabka-software-ka, waxaan abuuri karnaa qaabab AI oo waxtar leh oo waxtar leh oo loogu talagalay aaladaha cirifka ah, awood u siinaya noocyo badan oo codsiyo ah iyo isticmaalka kiisaska.

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