#!/bin/bash
# 启动Phase 4: 完整Enhanced版本
# 前提：Phase 3 (epoch_29.pth) 已完成

set -e

export PATH=/opt/conda/bin:$PATH
cd /workspace/bevfusion

echo "=========================================="
echo "Phase 4: 完整Enhanced版本"
echo "=========================================="
echo ""
echo "增强内容："
echo "  ✅ ASPP (Phase 1)"
echo "  ✅ Dice Loss (Phase 2)"
echo "  ✅ Deep Supervision (Phase 3)"
echo "  ✅ 提高分割权重 (map loss×3.0)"
echo ""
echo "训练设置："
echo "  基础模型: epoch_29.pth"
echo "  目标: epoch_34.pth"
echo "  学习率: 8e-5 (稍微提高)"
echo "  预期提升: mIoU +12-18% (累计)"
echo "  最终目标: mIoU 50-55%"
echo ""
echo "=========================================="
echo ""

EPOCH_29_PATH=$(find runs/ -name "epoch_29.pth" -type f | sort -r | head -1)

if [ -z "$EPOCH_29_PATH" ]; then
    echo "错误: 找不到epoch_29.pth"
    echo "请先完成Phase 3训练"
    exit 1
fi

echo "找到Phase 3模型: $EPOCH_29_PATH"
echo ""
echo "开始Phase 4训练（最终版本）..."
echo ""

LOG_FILE="training_phase4_final_$(date +%Y%m%d_%H%M%S).log"

torchpack dist-run -np 8 python tools/train.py \
  configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_enhanced_phase4.yaml \
  --model.encoders.camera.backbone.init_cfg.checkpoint pretrained/swint-nuimages-pretrained.pth \
  --load_from "$EPOCH_29_PATH" \
  --data.workers_per_gpu 0 \
  2>&1 | tee "$LOG_FILE"

echo ""
echo "=========================================="
echo "🎉 Phase 4训练完成！"
echo "=========================================="
echo ""
echo "✅ 所有增强阶段已完成！"
echo ""
echo "日志: $LOG_FILE"
echo ""
echo "下一步："
echo "  1. 评估最终性能"
echo "  2. 对比各Phase提升"
echo "  3. 准备部署"
echo ""
echo "=========================================="