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開発・技術 · SKILL.md

internals-maintenance

internals-maintenance

Guides FCOS source internals, model/loss/postprocess components, compiled layers, focused tests, and legacy PyTorch compatibility maintenance.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: internals-maintenance description: "Guides FCOS source internals, model/loss/postprocess components, compiled layers, focused tests, and legacy PyTorch compatibility maintenance." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

FCOS Internals and Maintenance

Use this sub-skill when the user is editing or debugging FCOS internals, including FCOSHead, FCOSModule, loss/postprocessing, BoxList, compiled C++/CUDA layers, test selection, or porting the legacy package to a newer PyTorch stack.

Start here

  1. Read references/architecture.md for how FCOS fits into the maskrcnn-benchmark detector stack.
  2. Read references/api-reference.md for component signatures and config keys consumed by internals.
  3. Read references/testing-reference.md before selecting native tests.
  4. Run scripts/inspect_fcos_components.py for safe import/config/component diagnostics.
  5. Read references/troubleshooting.md for _C, compiler, CUDA, NumPy, and PyTorch API drift.

Boundaries

Maintenance principle

Use tests and source inspection to isolate a component before running expensive COCO jobs. Many unit tests are CPU-safe, but model/layer tests may depend on the compiled extension and legacy PyTorch compatibility.

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