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Content same as #103948 @svekars the PR content is updated per your comment, but when trying to solve the conflict the original PR was closed by a mis-operation. Would you help handle this new one? sorry for the inconvenience. Pull Request resolved: https://github.com/pytorch/pytorch/pull/105051 Approved by: https://github.com/svekars
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1.8 KiB
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42 lines
1.8 KiB
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Technical Overview
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====================
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**TorchDynamo** is a Python-level JIT compiler designed to make unmodified
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PyTorch programs faster. TorchDynamo hooks into the frame evaluation API
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in CPython (`PEP 523 <https://peps.python.org/pep-0523/>`__) to
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dynamically modify Python bytecode right before it is executed. It
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rewrites Python bytecode in order to extract sequences of PyTorch
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operations into an `FX Graph <https://pytorch.org/docs/stable/fx.html>`__
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which is then just-in-time compiled with a customizable backend.
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It creates this FX Graph through bytecode analysis and is designed to
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mix Python execution with compiled backends to get the best of both
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worlds — usability and performance.
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TorchDynamo makes it easy to experiment with different compiler
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backends to make PyTorch code faster with a single line decorator
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``torch._dynamo.optimize()`` which is wrapped for convenience by ``torch.compile()``
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.. image:: ../_static/img/dynamo/TorchDynamo.png
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`TorchInductor` is one of the backends
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supported by `TorchDynamo Graph <https://pytorch.org/docs/stable/fx.html>`__
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into `Triton <https://github.com/openai/triton>`__ for GPUs or
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`C++/OpenMP <https://www.openmp.org/>`__ for CPUs. We have a
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`training performance dashboard <https://github.com/pytorch/torchdynamo/issues/681#issuecomment-1233828468>`__
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that provides performance comparison for different training backends. You can read
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more in the `TorchInductor post on PyTorch
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dev-discuss <https://dev-discuss.pytorch.org/t/torchinductor-a-pytorch-native-compiler-with-define-by-run-ir-and-symbolic-shapes/747>`__.
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.. seealso::
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* `TorchDynamo deep-dive video <https://www.youtube.com/watch?v=egZB5Uxki0I>`__
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* `dev-discuss topics <https://dev-discuss.pytorch.org/search?q=TorchDynamo%20order%3Alatest>`__
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.. toctree::
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:maxdepth: 1
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guards-overview
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best-practices-for-backends
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custom-backends
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deep-dive
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