67 lines
2.4 KiB
Bash
67 lines
2.4 KiB
Bash
#!/bin/bash
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# Phase 4A Stage 1 - Divider增强训练启动脚本
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# ✨ 特色: Adaptive Multi-Scale Fusion + Divider边界增强 + 增强权重
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set -e
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echo "══════════════════════════════════════════════════════════"
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echo "Phase 4A Stage 1 - Divider增强版训练"
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echo "══════════════════════════════════════════════════════════"
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echo ""
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echo "✨ 增强策略:"
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echo " 1. Adaptive Multi-Scale Fusion (每个类别学习最优尺度)"
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echo " 2. Divider边界增强模块 (专门针对线性特征)"
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echo " 3. 增强Divider权重 (3.0 → 5.0)"
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echo ""
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# 环境检查
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cd /workspace/bevfusion
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# 设置环境变量
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export PATH=/opt/conda/bin:$PATH
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export PYTHONPATH=/workspace/bevfusion:$PYTHONPATH
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# 验证环境
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/opt/conda/bin/python -c "import torch; print('✅ PyTorch:', torch.__version__)" || exit 1
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# 检查checkpoint
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if [ ! -f "/workspace/bevfusion/runs/run-326653dc-b7d0a4a4/epoch_8.pth" ]; then
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echo "❌ 错误: 未找到epoch_8.pth"
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exit 1
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fi
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echo "✅ 使用checkpoint: epoch_8.pth"
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ls -lh /workspace/bevfusion/runs/run-326653dc-b7d0a4a4/epoch_8.pth
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# 创建输出目录
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mkdir -p /data/runs/phase4a_divider_enhanced
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LOG_FILE="/data/runs/phase4a_divider_enhanced/train_$(date +%Y%m%d_%H%M%S).log"
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echo ""
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echo "=== 启动Divider增强训练 ==="
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echo "配置文件: multitask_BEV2X_phase4a_stage1_task_gca.yaml (已启用adaptive_multiscale)"
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echo "输出目录: /data/runs/phase4a_divider_enhanced"
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echo "日志文件: $LOG_FILE"
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echo ""
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# 启动训练
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nohup torchpack dist-run \
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-np 8 \
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/opt/conda/bin/python tools/train.py \
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configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_BEV2X_phase4a_stage1_task_gca.yaml \
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--load_from /workspace/bevfusion/runs/run-326653dc-b7d0a4a4/epoch_8.pth \
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--data.samples_per_gpu 1 \
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--data.workers_per_gpu 0 \
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> "$LOG_FILE" 2>&1 &
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TRAIN_PID=$!
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echo "✅ 训练已在后台启动 (PID: $TRAIN_PID)"
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echo ""
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echo "监控命令:"
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echo " tail -f $LOG_FILE"
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echo " tail -f $LOG_FILE | grep divider"
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echo ""
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echo "══════════════════════════════════════════════════════════"
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