#!/bin/bash
# 简化版评估脚本 - 使用单GPU快速评估
# 使用GPU 7，最小资源占用

set -e

export PATH=/opt/conda/bin:$PATH
export LD_LIBRARY_PATH=/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH
export PYTHONPATH=/workspace/bevfusion:$PYTHONPATH

cd /workspace/bevfusion

echo "========================================================================"
echo "Phase 3 Epoch 23 快速评估 (单GPU)"
echo "========================================================================"
echo "Checkpoint: epoch_23.pth"
echo "使用GPU: 7 (不影响训练)"
echo "========================================================================"
echo ""

# 创建评估输出目录
EVAL_DIR="eval_results/phase3_epoch23_quick_$(date +%Y%m%d_%H%M%S)"
mkdir -p "$EVAL_DIR"

CONFIG="configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_enhanced_phase1_HIGHRES.yaml"
CHECKPOINT="runs/enhanced_from_epoch19/epoch_23.pth"

echo "开始评估..."
echo ""

# 使用GPU 4-7进行分布式评估（4卡，避免与训练GPU 0-3冲突）
CUDA_VISIBLE_DEVICES=4,5,6,7 \
LD_LIBRARY_PATH=/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
PATH=/opt/conda/bin:$PATH \
/opt/conda/bin/torchpack dist-run -np 4 /opt/conda/bin/python tools/test.py \
  "$CONFIG" \
  "$CHECKPOINT" \
  --eval bbox \
  --out "$EVAL_DIR/results.pkl" \
  2>&1 | tee "$EVAL_DIR/eval.log"

echo ""
echo "========================================================================"
echo "评估完成！结果保存在: $EVAL_DIR"
echo "========================================================================"