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ONNX iyo Model Interoperability Quiz

Tijaabi fikradaha muhiimka ah ee ka dambeeya garaafyada ONNX, hawl-wadeenada, bixiyayaasha fulinta, iswaydaarsiga moodeelka, iyo hagaajinta garaafka wakhtiyada runtimes.

Wadooyinka haga ee la xidhiidhaOnnx iyo Model Interoperability
Su'aal 1 ee 8

Mushkiladda xudunta u ah ee ONNX xalliso waa maxay?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Mushkiladda xudunta u ah ee ONNX xalliso waa maxay?
    • U guurista moodooyinka u dhexeeya qaab-dhismeedka kala duwan iyo wakhtiyada runtimes iyadoo loo marayo qaab caadi ah
    • Calaamadaynta xogta tababarka si toos ah
    • Soo saarista qaab-dhismeedyada shabakada neural ee cusub
    • Sirta miisaannada moodeelka ee amniga
  2. Sidee faylka ONNX u matalaa qaab?
    • Sida xogta tababarka ceeriin
    • Sida garaaf xisaabeedka hawl wadeenada heerka sare ah
    • Sida hal lambar oo sabbaynaya
    • Sida koodka isha ee Python
  3. What does the acronym ONNX stand for?
    • Optimized Network Node Execution
    • Open Neural Network Extension
    • Open Neural Network Exchange
    • Operator Network Normalization Exchange
  4. Waqtiga Runtime-ga ONNX, waa maxay 'bixiye bixiye'?
    • Koontada biilasha daruuraha
    • Qofka u tababaray qaabka
    • Nooca shaqada khasaaraha
    • Dhabar dambe oo ku shaqeysa hawl wadeenada la taageeray qalab gaar ah sida CPU, CUDA, ama TensorRT
  5. Muxuu qeexayaa nooca 'opset' (operator set) ee qaabka ONNX?
    • Waa kuwee nooca hawlwadeenada jaangooyada ah ee garaafku isticmaalo
    • Saxnaanta moodeelka ee go'aanka tijaabada ah
    • Tirada GPU-yada loo baahan yahay
    • Heerka waxbarasho ee tababarka
  6. Which graph-level operations can ONNX Runtime apply?
    • Automatic retraining and label correction
    • Constant folding and node fusion, among other optimizations
    • Changing a model’s architecture to a new framework
    • Generating new training examples from inference requests
  7. What can happen when an ONNX Runtime execution provider supports only part of a model graph?
    • The provider must execute every node or fail by definition
    • Qaabka si toos ah ayaa dib loogu tababaray
    • The runtime can assign supported nodes or subgraphs to that provider and others to a different provider
    • All unsupported operators are deleted
  8. Why should an ONNX deployment check the model’s opset against the target runtime?
    • The opset specifies the model’s training dataset size
    • An opset number guarantees identical performance
    • The opset controls the number of GPU devices
    • The graph uses versioned operator definitions that the runtime must support