cpu-mode-assertions-torch
Assert CPU-only runtime inside a container using PyTorch (torch.cuda.is_available()==False) and optional env var checks. Use to prevent accidental GPU execution during CPU smoke tests.
安装与使用
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
查看来源 ↗使用指南技能说明
Skill Instructions
Inputs
-
SERVICE_CONTAINER(string): container name to exec into -
CPU_DEVICE_ENV(string, optional): env var to validate (e.g.ASR_DEVICE) -
CPU_DEVICE_EXPECTED(string, optional): expected value (e.g.cpu)
Procedure
set -euo pipefail
service_container="${SERVICE_CONTAINER:?SERVICE_CONTAINER is required}"
# 1) Env assertion (optional)
if [ -n "${CPU_DEVICE_ENV:-}" ]; then
docker exec "$service_container" printenv "$CPU_DEVICE_ENV"
fi
# 2) Runtime assertion (torch)
docker exec "$service_container" python - <<'PY'
import torch
print('torch_version=', torch.__version__)
print('torch_cuda_is_available=', torch.cuda.is_available())
print('torch_cuda_version=', getattr(torch.version, 'cuda', None))
PY
Acceptance Criteria
-
torch_cuda_is_availableprintsFalse - If
CPU_DEVICE_ENVis provided, its value equalsCPU_DEVICE_EXPECTED(orcpuif you standardize it)
Why
Prevents “silent GPU path” during CPU smoke testing (different behavior, heavier images, device-specific bugs).
使用示例
查看来源仓库中的使用示例与配置说明。
查看来源 ↗来源历史
- 收录时间
- 2026-01-20
- 索引更新时间
- 2026-01-26
- Branch
- main
收录与同步日期属于本站记录。源码修改历史请查看来源仓库。
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