TorchDynamo

Python (correct)

Java

C++

JavaScript

It extracts sequences of PyTorch operations (correct)

It dynamically modifies it

It compiles it into GPU code

It replaces it with C++ code

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)

<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

<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

<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