What is recorded here?
Integrated TorchDynamo bytecode rewriting and guarded graph caching with graph-break continuations, AOTAutograd forward/backward capture and TorchInductor code generation for PyTorch programs.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Separate compiler contribution from the inherited2019imperative PyTorch framework. Unsupported/data-dependent behavior can run outside compiled graphs; guards, recompilation and graph breaks have costs. Source-level conditional soundness reasoning is not a machine-checked proof of every handler/backend. Triton, CPython hooks and other reused components retain credit.
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People and systems
Jason Ansel; Edward Yang; Horace He; Natalia Gimelshein; Animesh Jain; Michael Voznesensky; Bin Bao; Peter Bell; David Berard; Evgeni Burovski; Geeta Chauhan; Anjali Chourdia; Will Constable; Alban Desmaison; Zachary DeVito; Elias Ellison; Will Feng; Jiong Gong; Michael Gschwind; Brian Hirsh; Sherlock Huang; Kshiteej Kalambarkar; Laurent Kirsch; Michael Lazos; Mario Lezcano; Yanbo Liang; Jason Liang; Yinghai Lu; CK Luk; Bert Maher; Yunjie Pan; Christian Puhrsch; Matthias Reso; Mark Saroufim; Marcos Yukio Siraichi; Helen Suk; Michael Suo; Phil Tillet; Eikan Wang; Xiaodong Wang; William Wen; Shunting Zhang; Xu Zhao; Keren Zhou; Richard Zou; Ajit Mathews; Gregory Chanan; Peng Wu; Soumith Chintala
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Research locations and affiliations
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English catalogue narrative
PyTorch 2: guarded bytecode graph capture and compiler execution
Integrated TorchDynamo bytecode rewriting and guarded graph caching with graph-break continuations, AOTAutograd forward/backward capture and TorchInductor code generation for PyTorch programs.
Scientific scope
Separate compiler contribution from the inherited2019imperative PyTorch framework. Unsupported/data-dependent behavior can run outside compiled graphs; guards, recompilation and graph breaks have costs. Source-level conditional soundness reasoning is not a machine-checked proof of every handler/backend. Triton, CPython hooks and other reused components retain credit.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Jason Ansel; Edward Yang; Horace He; Natalia Gimelshein; Animesh Jain; Michael Voznesensky; Bin Bao; Peter Bell; David Berard; Evgeni Burovski; Geeta Chauhan; Anjali Chourdia; Will Constable; Alban Desmaison; Zachary DeVito; Elias Ellison; Will Feng; Jiong Gong; Michael Gschwind; Brian Hirsh; Sherlock Huang; Kshiteej Kalambarkar; Laurent Kirsch; Michael Lazos; Mario Lezcano; Yanbo Liang; Jason Liang; Yinghai Lu; CK Luk; Bert Maher; Yunjie Pan; Christian Puhrsch; Matthias Reso; Mark Saroufim; Marcos Yukio Siraichi; Helen Suk; Michael Suo; Phil Tillet; Eikan Wang; Xiaodong Wang; William Wen; Shunting Zhang; Xu Zhao; Keren Zhou; Richard Zou; Ajit Mathews; Gregory Chanan; Peng Wu; Soumith Chintala
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.