#!/bin/bash
# Phase 4B 单Batch推理脚本 - 只推理一组数据
# 用于快速验证模型是否正常工作

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 4B 单Batch推理测试"
echo "========================================================================"
echo "只推理1个batch的数据 (2个样本)"
echo "用于快速验证模型和配置是否正常"
echo "========================================================================"
echo ""

# 创建推理输出目录
INFER_DIR="/data/infer_test/$(date +%Y%m%d_%H%M%S)"
mkdir -p "$INFER_DIR"

CONFIG="configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_BEV2X_phase4b_rmtppad_segmentation.yaml"
CHECKPOINT="runs/run-4c8ec7e5-fabdc997/epoch_1.pth"

echo "配置文件: $CONFIG"
echo "Checkpoint: $CHECKPOINT"
echo "输出目录: $INFER_DIR"
echo ""

# 检查文件存在
if [ ! -f "$CONFIG" ]; then
    echo "❌ 配置文件不存在: $CONFIG"
    exit 1
fi

if [ ! -f "$CHECKPOINT" ]; then
    echo "❌ Checkpoint不存在: $CHECKPOINT"
    exit 1
fi

echo "✓ 文件检查通过"
echo ""

# 单GPU单Batch推理
echo "开始单Batch推理..."
echo "只推理1个batch (2个样本)"
echo "预计时间: 10-30秒"
echo "日志文件: $INFER_DIR/infer_test.log"
echo ""

torchpack dist-run \
    -np 1 \
    /opt/conda/bin/python tools/test.py \
    "$CONFIG" \
    "$CHECKPOINT" \
    --out "$INFER_DIR/one_batch_results.pkl" \
    --cfg-options data.test.load_interval=6018 data.test.samples_per_gpu=1 data.workers_per_gpu=0 \
    2>&1 | tee "$INFER_DIR/infer_test.log"

echo ""
echo "========================================================================"
echo "单Batch推理完成！"
echo "========================================================================"
echo "结果文件: $INFER_DIR/one_batch_results.pkl"
echo "日志文件: $INFER_DIR/infer_test.log"
echo ""

# 检查结果文件
if [ -f "$INFER_DIR/one_batch_results.pkl" ]; then
    echo "✅ 推理成功！结果文件已生成"

    # 显示结果文件大小
    FILE_SIZE=$(du -h "$INFER_DIR/one_batch_results.pkl" | cut -f1)
    echo "结果文件大小: $FILE_SIZE"

    # 检查是否有推理输出
    /opt/conda/bin/python -c "
import pickle
import torch
try:
    with open('$INFER_DIR/one_batch_results.pkl', 'rb') as f:
        results = pickle.load(f)
    print(f'推理结果数量: {len(results)}')
    if len(results) > 0:
        sample = results[0]
        print(f'第一个样本的keys: {list(sample.keys())}')
        if 'masks_bev' in sample:
            print(f'BEV分割形状: {sample[\"masks_bev\"].shape}')
        if 'boxes_3d' in sample:
            print(f'3D检测框数量: {len(sample[\"boxes_3d\"])}')
    print('✅ 结果格式正确！')
except Exception as e:
    print(f'❌ 结果文件读取失败: {e}')
"

else
    echo "❌ 推理失败，未生成结果文件"
    echo "关键错误信息:"
    grep -E "(ERROR|Error|Exception|KeyError|ImportError|RuntimeError)" "$INFER_DIR/infer_test.log" | tail -5
    exit 1
fi

echo ""
echo "✅ 单Batch推理测试完成！模型配置正确"
echo "========================================================================"