executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
Explorer les Skills
Productivité · SKILL.md
runtime-ops
runtime-opsRoute Det3D installation, import, CUDA extension, PyTorch ABI, optional dependency, distributed-runtime, and checkpoint filesystem troubleshooting.
Independent GitHub snapshot · Automated classification · Original documentation governs
Documentation de la Skill
GitHubname: 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
- Read installation.md for historical version constraints and installation order.
- Run the runtime diagnostic and separate framework CUDA availability from
nvcc, compiler, extension, andspconvavailability. - Read custom-ops.md before rebuilding any extension; match Python, torch, CUDA toolkit, compiler, and GPU ABI.
- Check runtime-diagnostics.md for import classification and distributed environment checks.
- 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.