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Torch Spyre uses CRCR and agent-selected tests to integrate with PyTorch CI

pytorch.org 14 min read Editor score 7/10

Torch Spyre combines CRCR, an agentic pipeline that selects and re-buckets tests from code and execution evidence, and declarative YAML adaptations to integrate with PyTorch’s upstream CI. The approach offers concrete patterns for maintaining downstream accelerator compatibility as upstream code and tests change.

What: • PyTorch’s Cross-Repository CI Relay lets out-of-tree accelerators run downstream CI on upstream PyTorch changes and report results to reviewers.
How: • Torch Spyre uses agentic test selection and re-bucketing plus declarative YAML to adapt upstream tests without patching them; it reached L2 integration.
Why it matters: • Backend-owned test selection and reusable integration patterns help accelerator teams keep relevant hardware coverage current as PyTorch and its tests evolve.

CRCR dispatches upstream changes to out-of-tree repositories and routes their results to the HUD. Sketched from the article's own text.

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