인터페이스는 현지화되어 있으며, Skill 소개와 설명 문서는 선택한 언어로 AI가 자동 번역합니다. 코드·명령어·경로·전문 용어는 원문을 유지하며 원작자 문서가 우선합니다.
Skills 둘러보기
생산성 및 협업 · SKILL.md

runtime-ops

runtime-ops

Route Det3D installation, import, CUDA extension, PyTorch ABI, optional dependency, distributed-runtime, and checkpoint filesystem troubleshooting.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: runtime-ops description: "Route Det3D installation, import, CUDA extension, PyTorch ABI, optional dependency, distributed-runtime, and checkpoint filesystem troubleshooting." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

Runtime Operations

Use this route whenever Det3D fails during installation, package import, CUDA operator loading/building, distributed initialization, or filesystem setup. Run scripts/check_runtime.py first; it is read-only and reports JSON.

Workflow

  1. Read installation.md for historical version constraints and installation order.
  2. Run the runtime diagnostic and separate framework CUDA availability from nvcc, compiler, extension, and spconv availability.
  3. Read custom-ops.md before rebuilding any extension; match Python, torch, CUDA toolkit, compiler, and GPU ABI.
  4. Check runtime-diagnostics.md for import classification and distributed environment checks.
  5. Apply troubleshooting.md and preserve the first actionable error.

Do not call a CPU import a successful GPU capability check. Do not repair a user-owned environment by silently changing torch, setuptools, CUDA, or compiled packages. Training/evaluation and data conversion remain separate side-effectful workflows.

저장한 Skills