Uhlolojikelele
I-ONNX (Open Neural Network Exchange) ifomethi evamile evulekile yokumela amamodeli okufunda omshini ukuze ahambe ngokukhululeka phakathi kwezinhlaka nezikhathi zokusebenza. Ikuvumela ukuthi uqeqeshe imodeli ethuluzini elilodwa, njenge-PyTorch, futhi uyisebenzise kwenye indawo ngaphandle kokuyibhala kabusha.
I-ONNX kanye Nokusebenzelana Kwemodeli kuyibhlokhi yokwakha yobuchwepheshe ethinta ikhwalithi yamamodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini.
I-Deep Dive
Izinhlaka ezihlukene (i-PyTorch, i-TensorFlow, i-scikit-learn) igcina amamodeli ngamafomethi angahambelani, okwenza ukuthunyelwa kube buhlungu. I-ONNX, eyethulwe ngo-2017 ngu-Microsoft kanye ne-Facebook futhi manje ephethwe ngaphansi kwe-Linux Foundation, ixazulula lokhu ngokuchaza ifomethi yefayela evamile kanye nesethi ejwayelekile yama-opharetha (njenge-Conv, MatMul, Relu) echaza imodeli njengegrafu yokubala. Uthumela imodeli eqeqeshiwe kufayela le-.onnx, futhi noma yisiphi isikhathi sokusebenza esihambisanayo singayilayisha. I-ONNX Runtime ibese isebenzisa igrafu kahle kuzo zonke izingxenye zekhompuyutha ezihlukahlukene, isebenzisa ukulungiselelwa okufana nokuhlanganiswa komsebenzisi nokubalwa komthamo, kanye nokubala komzila kuma-backend afana nama-CPU, ama-NVIDIA GPU (nge-TensorRT), noma ama-accelerator akhethekile. Lokhu kwehlisa ukuqeqeshwa kwamamodeli kusukela ekusetshenzisweni.
I-Technical Insight
Imodeli ye-ONNX iyigrafu yokubala ehleliwe: ama-node ango-opharetha athathwe kusethi ye-opharetha yenguqulo (opset), futhi amaphethelo aphethe ama-tensor anomumo nezinhlobo ezichaziwe. Abathekelisi balandelela noma babhale imodeli yakho ukuze bathwebule le grafu. Uma kucatshangelwa, i-ONNX Runtime ihlukanisa igrafu kubo bonke 'abahlinzeki bokubulala' (i-CPU, i-CUDA, i-TensorRT, njll.), ngayinye iphethe ama-opharetha eyisekela kangcono, futhi isebenzisa ukulungiselelwa kweleveli yegrafu njengokugoqa njalo kanye nokuhlanganiswa kwamanodi ukuze izinto zisheshe.
Ukubamba i-ONNX kanye nokusebenzisana kwemodeli
I-ONNX (Open Neural Network Exchange) ifomethi evamile evulekile yokumela amamodeli okufunda omshini ukuze ahambe ngokukhululeka phakathi kwezinhlaka nezikhathi zokusebenza. Ikuvumela ukuthi uqeqeshe imodeli ethuluzini elilodwa, njenge-PyTorch, futhi uyisebenzise kwenye indawo ngaphandle kokuyibhala kabusha. I-ONNX kanye Nokusebenzelana Kwemodeli kuyibhlokhi yokwakha yobuchwepheshe ethinta ikhwalithi yamamodeli, izindleko zengqalasizinda, ukubambezeleka, nokuthembeka esikalini. Ukuze wakhe ukuqonda okujulile, phatha i-ONNX kanye Nokusebenzelana Kwemodeli njengemodeli yokusebenza, hhayi isici esisodwa: chaza imiphumela efiselekayo, ucacise ukucabanga, futhi uhlukanise lokho isistimu engakwenza ngokwethembeka kulokho okusadinga ukwahlulela kochwepheshe.
Empeleni, amaqembu aqinile asebenzisa i-ONNX kanye Nokusebenzelana Kwemodeli athuthukisa izakhiwo, idatha, nokukhetha kwengqalasizinda ngokumelene nokuthembeka nezindleko. Babhala imibandela yempumelelo ecacile, ukuhlola okuqhathaniswa nedatha engokoqobo nokugeleza komsebenzi, futhi baphindaphinde ngokusekelwe kumaphethini okuhluleka aqashiwe esikhundleni sokuwina kwebhentshimakhi yesikhathi esisodwa. Yilapho ukuqonda kwethiyori kuguquka kube amandla ahlala njalo kuwo wonke umkhiqizo, inqubomgomo, kanye nokusebenza.
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka. Ngesikhathi esifanayo, Ukuthuthukisa ibhentshimakhi eyodwa kungafihla ubuthakathaka obubanzi besistimu. Indlela eqine kakhulu iwukuhlanganisa isivinini sokuhlola nesiyalo sokuphatha: qhuba abashayeli bezindiza, bamba ubufakazi, ushicilele amalogi ezinqumo, futhi ubuyekeze izivikelo ngokuqhubekayo njengoba imodeli yokuziphatha, okulindelwe ngabasebenzisi, kanye nezimfuneko zokulawula zishintsha.
I-Strategic Impact
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka.
Izinqumo zezakhiwo ziqhuba ukusebenza kanye nezindleko zokusebenza iminyaka. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha.
Imfundo yobuchwepheshe isiza amaqembu ukuthi akhethe isitaki esifanele, hhayi nje esisha. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni.
Izinketho ezingcono zobunjiniyela zinciphisa izehlakalo ezinokwethenjelwa ekukhiqizeni. Ekusetshenzisweni kwekhwalithi ephezulu, lokhu kuhunyushwa emithethweni yokusebenza elinganisekayo, imingcele yobunikazi, nemikhuba yokubuyekeza ephindelelayo ukuze amaqembu akwazi ukukala ukuzethemba esikhundleni sokukala ukungaqondakali.
Ukuqaliswa Komhlaba Wangempela
Ithekelisa isihlukanisi sesithombe se-PyTorch ku-ONNX futhi siyisebenzise nge-ONNX Runtime kuseva yokukhiqiza ye-C++ ngaphandle kokuncika kwePython.
Ithumela imodeli kuselula noma isiphequluli nge-ONNX Runtime Web (WebAssembly) ukuze uthole ukuqondiswa okukudivayisi.
Ukusheshisa i-transformer ethunyelwe nge-NVIDIA TensorRT njengomhlinzeki wokusebenzisa we-ONNX Runtime ukuze uthole ukubambezeleka okuphansi.
Ukulinganisa imodeli ye-ONNX ibe yi-int8 ukuze kuncishiswe usayizi wayo futhi kusheshiswe ukucabanga kuma-CPU onqenqema.
Amaphethini Okusebenzisa
I-ONNX kanye nokusebenzisana kwemodeli ekusebenzeni
Ithekelisa isihlukanisi sesithombe se-PyTorch ku-ONNX futhi siyisebenzise nge-ONNX Runtime kuseva yokukhiqiza ye-C++ ngaphandle kokuncika kwePython.
Ithekelisa isihlukanisi sesithombe se-PyTorch ku-ONNX futhi siyisebenzise nge-ONNX Runtime kuseva yokukhiqiza ye-C++ engenakho Amaqembu ancike ePython ngokuvamile athola imiphumela engcono lapho echaza imingcele yekhwalithi ngaphambili, agcine indlela yokukhuphuka yomuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-ONNX kanye nokusebenzisana kwemodeli ekusebenzeni
Ithumela imodeli kuselula noma isiphequluli nge-ONNX Runtime Web (WebAssembly) ukuze uthole ukuqondiswa okukudivayisi.
Ukuthumela imodeli kuselula noma isiphequluli nge-ONNX Runtime Web (WebAssembly) ukuze uthole ukuqondiswa okukudivayisi Amathimba ngokuvamile athola imiphumela engcono lapho echaza ikhwalithi ephezulu ngaphambili, egcina indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-ONNX kanye nokusebenzisana kwemodeli ekusebenzeni
Ukusheshisa i-transformer ethunyelwe nge-NVIDIA TensorRT njengomhlinzeki wokusebenzisa we-ONNX Runtime ukuze uthole ukubambezeleka okuphansi.
Ukusheshisa i-transformer ethunyelwe nge-NVIDIA TensorRT njengomhlinzeki wokubulala we-ONNX Runtime wamaThimba we-latency aphansi ngokuvamile athola imiphumela engcono uma echaza imikhawulo yekhwalithi ngaphambili, egcina indlela yokukhuphuka komuntu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
I-ONNX kanye nokusebenzisana kwemodeli ekusebenzeni
Ukulinganisa imodeli ye-ONNX ibe yi-int8 ukuze kuncishiswe usayizi wayo futhi kusheshiswe ukucabanga kuma-CPU onqenqema.
Ukulinganisa imodeli ye-ONNX ibe yi-int8 ukuze kuncishiswe usayizi wayo futhi kusheshiswe ukucatshangelwa kuma-CPU asonqenqemeni Amaqembu ngokuvamile athola imiphumela engcono uma echaza ikhwalithi ephezulu ngaphambili, egcina indlela yokukhuphuka yabantu yamakesi asemaphethelweni, futhi alandelele kokubili izinzuzo zokukhiqiza nezindleko zamaphutha ngokuhamba kwesikhathi.
Izingozi & Guardrails
Ukuthuthukisa ibhentshimakhi eyodwa kungafihla ubuthakathaka obubanzi besistimu.
Izindleko zengqalasizinda nezokulungisa zivame ukubukelwa phansi.
Izikhala zokuphepha nokubonakala zingakhula njengoba izinhlelo ziba nzima kakhulu.
Ukuqalisa Umhlahlandlela
Chaza ukubambezeleka, ikhwalithi, nezindleko ezihlosiwe ngaphambi kokuqaliswa.
Chaza ukubambezeleka, ikhwalithi, nezindleko ezihlosiwe ngaphambi kokuqaliswa. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha.
Ibhentshimakhi ngaphansi komthwalo wangempela nezimo zedatha. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi.
Ukuqapha amathuluzi amaphutha, ukukhukhuleka, nomthelela wabasebenzisi. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala.
Lungiselela izindlela zokuhlehlisa nezigameko ngaphambi kokukala. Phatha isinyathelo ngasinye njengesango lobufakazi: uma imibandela ingafinyelelwa, misa ukukhishwa, vala igebe, bese unweba ukusetshenziswa.