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

x5-accuracy-diagnostics

Skill1 starsChanged 3 months agoApache-2.0View on GitHub

定位 X5 PTQ 或 Plugin QAT 的首次精度掉点阶段;当有浮点、校准、QAT、定点、编译或板端指标及固定输入时使用。只读比较并设计单变量实验,不自动重训或重编译。

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SKILL.md

X5 精度诊断

目标与边界

把精度问题拆成数据/前处理、校准、伪量化、定点转换、编译和 Runtime 输出阶段,先找首次分歧,再决定是否调整数据、qconfig 或 YAML。

输入合同

  • 同一评测集上的浮点与各量化阶段指标。
  • 固定样本、逐阶段输出或 dump、校准 manifest、YAML/QAT 源码和日志。
  • 评价代码、阈值、模型/数据哈希和环境快照。

前置检查

  1. 确认所有指标使用同一前处理、后处理、标签映射和评价口径。
  2. 检查 dtype/layout/色彩、mean/scale 是否重复或遗漏。
  3. 分开 PTQ .bin 与 QAT .hbm/.hbir,不跨合同比较工具参数。

执行步骤

  1. 对固定样本建立阶段矩阵:float → calibration/fake-quant → quantized → compile/runtime。
  2. 计算任务指标和数值差异(如 cosine、最大绝对误差、top-k/检测指标)。
  3. 找首个超过阈值的层/输出/阶段,并关联校准分布、饱和、异常值和 CPU/BPU 分配。
  4. 设计一个单变量实验:更换代表性校准集、修正前处理、调整一项校准/qconfig 或延长 QAT。
  5. 明确预期变化、停止条件和回滚。

产物与完成标准

  • 首次分歧阶段、受影响样本/节点、数值证据和根因置信度。
  • accuracy-report 给出一个优先实验和一个备选,不给无序参数清单。
  • 若无法定位,列出缺失的最小 dump/指标并保持 blocked。

风险与确认

分析为低风险。重新生成校准集、训练或编译必须交接对应 Workflow 并重新确认成本和输出目录。

失败与交接

数据问题 → x5-calibration-data-prepare;PTQ 参数 → x5-ptq-config-authoring;QAT → x5-qat-training。同一假设最多两次。

按需参考

  • _sources/oe_mapper/source/ptq/ptq_tool/accuracy_debug.rst.txt
  • _sources/plugin/source/user_guide/quant_analysis.md.txt

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