fix(pybot×actpred): v3 审计 P2 清零——验收链 fixed_range + 导出断言 + overrun 节流
- v3-P2-1: _npu_test/_onnx_validate 按 normalize_mode 分支(fixed_range 免 stats, HailoPredictor 透传模式,torch 参考同口径反归一化) - v3-P2-2: export_deploy/export_onnx 一致性 diff 超 1e-4 即 sys.exit(P2-f 闭环) - v3-P2-3: run_loop overrun 告警节流(第1次+每100次),降 hz 建议仅 >10% 输出 - P2-a1: default_column_weights 扩展列(action_dim>18)默认 1.0 - P2-c: 补 predictor 异常清理路径测试(异常传播 + finally 落盘) - P2-d/P2-e: Resize 口径与 resume scheduler T_max 语义文档化 - R2-4: _set.sh 安装后断言 CPU 版 torch,误装 CUDA 即拦截 测试: pybot 89 passed (+1)、actpred 148 passed/18 skipped
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@@ -16,6 +16,17 @@ pip install onnxscript onnxruntime -i https://pypi.tuna.tsinghua.edu.cn/simple
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pip check
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mkdir -p checkpoints data
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# R2-4 防呆:确认装到的是 CPU 版 torch——requirements.txt 含 torch,
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# 若被镜像源重装成 CUDA 版(无 GPU 部署会被 CUDA 依赖拖垮)在此拦截
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python3 -c "
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import torch
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assert torch.version.cuda is None, (
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f'检测到 CUDA 版 torch({torch.__version__}),'
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'请用 _set.sh 的 CPU 源重装: pip install torch torchvision '
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'--index-url https://download.pytorch.org/whl/cpu --force-reinstall')
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print('torch CPU build OK:', torch.__version__)
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"
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# Pre-download MobileNetV2 weights for offline fine-tuning (optional, skip if backbone=simple)
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python3 -c "
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import torch, sys, os
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