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D-RoboticsD-Robotics/dsh-plugin-rdk/skills/oe-skills-x5/x5-router/SKILL.md

x5-router

Skill1 starsChanged 3 months agoApache-2.0View on GitHub

路由 X5 环境、OE Mapper PTQ、Plugin QAT、Runtime、板端 Python 和诊断请求;当目标芯片明确为 X5 或请求包含 bayes-e、hb_mapper、X5 .bin、March.BAYES_E 时使用。只选择一个主 Skill 并生成 route.json;不执行 HAT、X3 或 S 系列工作流。

The file

Files
SKILL.md

X5 路由

目标与边界

  • 读取 .drobotics/platforms/x5/skill-index.json,以输入、产物、环境和风险选择一个主 Skill。
  • 用户只说“X 系列”时先确认 X5/X3;X3 和其他 X 芯片在专属 Pack 可用前返回 blocked。
  • HAT、HAT config、Trainer、Model Zoo 和 tools/compile_perf.py 不在范围内。
  • 不调用 s-*、HBDK4、HMCT、UCP、nash-* 或 March.BAYES。

输入合同

  • 用户结果目标、目标芯片、模型/代码路径和期望产物。
  • 已知模型格式、输入输出合同、板端信息和失败收据。
  • 是否允许安装、训练、生成模型、上传或覆盖文件。

前置检查

  1. 用芯片型号、模型后缀和工具名确认平台;.bin 不能单独证明 X5,仍需 hb_model_info 或来源证据。
  2. 区分 PTQ 与 QAT:ONNX/Caffe 浮点模型走 PTQ;可训练 PyTorch + Plugin 走 QAT。
  3. 区分 Runtime:.bin C/C++/命令行走 Runtime;板端 HB_HBMRuntime Python 走 Python API。
  4. 环境未知时先选 x5-environment-probe,不要直接选安装或执行 Skill。

执行步骤

目标主 Skill典型后续交接
检查/准备环境x5-environment-setupprobe → install(如获确认)
ONNX/Caffe 到 X5 .binx5-ptq-deploypreflight → data → config → compile → Runtime
Plugin calibration/QATx5-qat-deployadaptation → training → compile
.bin C/C++/上板/性能x5-runtime-deployC++ → perf → monitor
X5 板端 Pythonx5-bpu-python-apienvironment/diagnostics
已有失败证据x5-model-diagnosticsaccuracy/consistency/performance

将候选、拒绝理由、主 Skill 和有序 handoff 写入运行目录的 route.json。多个关键词命中时也只保留一个主 Skill。

产物与完成标准

  • route.json 符合 Pack 的 route schema,且 selected_skill 在 X5 注册表中。
  • 明确说明拒绝 S、X3、HAT 或格式不兼容候选的理由。
  • 环境、输入或授权不足时只路由到预检/探测,不生成执行成功结论。

风险与确认

路由本身为低风险。不得把用户对“分析”的同意解释为对安装、训练、覆盖、上传或停止进程的授权。

失败与交接

  • 芯片不明:只问一个最小问题“目标板卡是 X5、X3 还是其他型号?”
  • HAT 请求:说明当前 Pack 明确排除 HAT,不迁移配置。
  • 无合法候选:保存拒绝理由并以 blocked 结束。

按需参考

  • .drobotics/platforms/x5/policies/compatibility.md
  • .drobotics/platforms/x5/policies/risk-policy.md
  • .drobotics/platforms/x5/references/run-contract.md

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