TorchDynamo

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Questions and Answers

Which programming language is TorchDynamo designed to work with?

  • Python (correct)
  • Java
  • C++
  • JavaScript

What does TorchDynamo do to Python bytecode?

  • It extracts sequences of PyTorch operations (correct)
  • It dynamically modifies it
  • It compiles it into GPU code
  • It replaces it with C++ code

What is the purpose of TorchInductor in relation to TorchDynamo?

  • It is a customizable backend
  • It is a Python-level JIT compiler
  • It is a training performance dashboard
  • It is a training backend for GPUs (correct)

Match the following components of TorchDynamo with their descriptions:

<p>TorchDynamo = A Python-level JIT compiler designed to make unmodified PyTorch programs faster FX Graph = Extracted sequences of PyTorch operations that are just-in-time compiled with a customizable backend torch._dynamo.optimize() = A single line decorator used to make PyTorch code faster TorchInductor = A backend supported by TorchDynamo that transforms Graph into Triton for GPUs or C++/OpenMP for CPUs</p> Signup and view all the answers

Match the following processes in TorchDynamo with their functions:

<p>Bytecode analysis = Creates the FX Graph Frame evaluation API in CPython = Dynamically modifies Python bytecode right before it is executed Customizable backend = Just-in-time compiles the FX Graph torch.compile() = Wraps torch._dynamo.optimize() for convenience</p> Signup and view all the answers

Match the following components with their usage in TorchDynamo:

<p>PEP 523 = The API into which TorchDynamo hooks to dynamically modify Python bytecode FX Graph = Made through bytecode analysis and used to mix Python execution with compiled backends torch._dynamo.optimize() = Used to experiment with different compiler backends to make PyTorch code faster TorchInductor = Transforms TorchDynamo Graph into Triton for GPUs or C++/OpenMP for CPUs</p> Signup and view all the answers

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