181 lines
3.5 KiB
Markdown
181 lines
3.5 KiB
Markdown
# BEVFusion训练状态报告
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**生成时间**: 2025-10-30 15:15
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**训练任务**: Phase 4A Stage 1 (600×600分辨率)
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---
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## 📊 当前训练状态
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### 基本信息
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```
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任务: Phase 4A Stage 1
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配置: 600×600分辨率, 4层Decoder, Deep Supervision + Dice Loss
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GPU: 4张 (GPU 0-3)
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从checkpoint: epoch_23.pth
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目标epochs: 10
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```
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### 训练进度
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```
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当前Epoch: 1 / 10
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迭代进度: 正在进行
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总迭代数: 30,895 iters/epoch
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```
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### Loss趋势
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```
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起始Loss: ~6.9
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当前Loss: ~4.5
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下降幅度: ~35%
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趋势: 持续稳定下降 ✅
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Grad Norm: 正常 (8-13范围)
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```
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### GPU状态
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```
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GPU 0: 30.4 GB / 32 GB (93%) @ 100%利用率
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GPU 1: 30.9 GB / 32 GB (94%) @ 100%利用率
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GPU 2: 30.7 GB / 32 GB (94%) @ 100%利用率
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GPU 3: 30.7 GB / 32 GB (94%) @ 100%利用率
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温度: 47-50°C (正常)
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显存使用: 稳定在93-94%
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利用率: 100% (满载)
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```
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### 训练效率
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```
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时间/iter: ~2.61秒
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数据加载: ~0.44秒/iter
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计算时间: ~2.17秒/iter
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预计完成:
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Epoch 1: ~21小时 (从启动开始)
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10 epochs: ~8.5天
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当前ETA: 18天15小时 (会随训练加速递减到实际~8.5天)
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```
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### 性能指标进展 (iter 2600)
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```
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分割Loss:
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Drivable Area: dice=0.33 ↓, focal=0.043
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Ped Crossing: dice=0.63 ↓, focal=0.032
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Walkway: dice=0.54 ↓, focal=0.044
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Stop Line: dice=0.74 ↓, focal=0.041 ⭐
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Carpark: dice=0.63 ↓, focal=0.020
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Divider: dice=0.86 ↓, focal=0.029 ⭐
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3D检测Loss:
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Heatmap: 0.224
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Classification: 0.035
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BBox: 0.318
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Matched IoU: 0.622 ✅
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总Loss: 4.583 (从6.9下降)
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```
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---
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## 🎯 与Phase 3对比
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### Phase 3 (Epoch 23) Baseline
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```
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配置: 400×400, 2层Decoder, 无Deep Sup
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3D检测: NDS 0.6941, mAP 0.6446
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BEV分割: mIoU 0.4130
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- Stop Line: 0.2657
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- Divider: 0.1903
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```
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### Stage 1当前训练 (Epoch 1 进行中)
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```
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配置: 600×600, 4层Decoder, Deep Sup + Dice
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Loss: 持续下降 ✅
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预期: Stop Line和Divider显著提升
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```
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---
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## 📁 重要文件位置
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### Checkpoint
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```
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Phase 3: runs/enhanced_from_epoch19/epoch_23.pth (516MB)
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Stage 1: runs/run-326653dc-c038af2c/
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→ latest.pth (将在epoch完成时保存)
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```
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### 配置文件
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```
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Stage 1: configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/
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└─ multitask_BEV2X_phase4a_stage1.yaml
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```
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### 日志文件
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```
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训练日志: phase4a_stage1_20251030_130707.log
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训练目录: runs/run-326653dc-c038af2c/20251030_130713.log
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```
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---
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## ✅ 训练健康状态
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### 稳定性检查
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```
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✅ Loss稳定下降 (6.9 → 4.5)
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✅ Grad norm正常 (无nan或爆炸)
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✅ GPU利用率100% (满载)
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✅ 显存使用稳定 (93-94%)
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✅ 无错误或警告
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✅ 数据加载正常
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```
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### 性能指标健康度
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```
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✅ 3D检测IoU保持: 0.622 (vs Phase 3的0.633)
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✅ 分割dice loss下降: 各类别都在改善
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✅ Stop Line和Divider loss下降趋势明显
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```
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---
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## 🔄 GPU资源分配
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### 当前使用
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```
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GPU 0-3: Stage 1训练 (93-94%显存, 100%利用)
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GPU 4-7: 完全空闲 (可用于epoch23评估)
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```
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### 训练不受影响的保证
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```
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✓ GPU物理隔离 (0-3 vs 4-7)
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✓ CUDA_VISIBLE_DEVICES强制隔离
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✓ 独立进程空间
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✓ 独立显存分配
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```
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---
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## ⏭️ 下一步
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### 训练方面 (继续)
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- 🔄 Epoch 1继续训练
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- ⏸️ ~21小时后Epoch 1完成
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- ⏸️ 验证性能提升
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### 评估方面 (新Docker)
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- 📋 准备新Docker环境指南
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- 📋 配置部署测试环境
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- 📋 运行epoch_23评估
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---
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**训练状态**: ✅ 优秀！Loss稳定下降，GPU满载，无异常
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**可用资源**: GPU 4-7完全空闲
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**下一步**: 为您准备新Docker评估指南
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