109 lines
3.4 KiB
Bash
Executable File
109 lines
3.4 KiB
Bash
Executable File
#!/bin/bash
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# Phase 4B 单Batch推理脚本 - 只推理一组数据
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# 用于快速验证模型是否正常工作
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set -e
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export PATH=/opt/conda/bin:$PATH
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export LD_LIBRARY_PATH=/opt/conda/lib/python3.8/site-packages/torch/lib:/opt/conda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH
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export PYTHONPATH=/workspace/bevfusion:$PYTHONPATH
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cd /workspace/bevfusion
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echo "========================================================================"
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echo "Phase 4B 单Batch推理测试"
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echo "========================================================================"
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echo "只推理1个batch的数据 (2个样本)"
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echo "用于快速验证模型和配置是否正常"
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echo "========================================================================"
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echo ""
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# 创建推理输出目录
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INFER_DIR="/data/infer_test/$(date +%Y%m%d_%H%M%S)"
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mkdir -p "$INFER_DIR"
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CONFIG="configs/nuscenes/det/transfusion/secfpn/camera+lidar/swint_v0p075/multitask_BEV2X_phase4b_rmtppad_segmentation.yaml"
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CHECKPOINT="runs/run-4c8ec7e5-fabdc997/epoch_1.pth"
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echo "配置文件: $CONFIG"
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echo "Checkpoint: $CHECKPOINT"
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echo "输出目录: $INFER_DIR"
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echo ""
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# 检查文件存在
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if [ ! -f "$CONFIG" ]; then
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echo "❌ 配置文件不存在: $CONFIG"
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exit 1
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fi
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if [ ! -f "$CHECKPOINT" ]; then
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echo "❌ Checkpoint不存在: $CHECKPOINT"
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exit 1
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fi
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echo "✓ 文件检查通过"
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echo ""
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# 单GPU单Batch推理
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echo "开始单Batch推理..."
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echo "只推理1个batch (2个样本)"
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echo "预计时间: 10-30秒"
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echo "日志文件: $INFER_DIR/infer_test.log"
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echo ""
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torchpack dist-run \
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-np 1 \
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/opt/conda/bin/python tools/test.py \
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"$CONFIG" \
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"$CHECKPOINT" \
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--out "$INFER_DIR/one_batch_results.pkl" \
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--cfg-options data.test.load_interval=6018 data.test.samples_per_gpu=1 data.workers_per_gpu=0 \
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2>&1 | tee "$INFER_DIR/infer_test.log"
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echo ""
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echo "========================================================================"
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echo "单Batch推理完成！"
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echo "========================================================================"
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echo "结果文件: $INFER_DIR/one_batch_results.pkl"
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echo "日志文件: $INFER_DIR/infer_test.log"
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echo ""
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# 检查结果文件
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if [ -f "$INFER_DIR/one_batch_results.pkl" ]; then
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echo "✅ 推理成功！结果文件已生成"
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# 显示结果文件大小
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FILE_SIZE=$(du -h "$INFER_DIR/one_batch_results.pkl" | cut -f1)
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echo "结果文件大小: $FILE_SIZE"
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# 检查是否有推理输出
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/opt/conda/bin/python -c "
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import pickle
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import torch
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try:
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with open('$INFER_DIR/one_batch_results.pkl', 'rb') as f:
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results = pickle.load(f)
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print(f'推理结果数量: {len(results)}')
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if len(results) > 0:
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sample = results[0]
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print(f'第一个样本的keys: {list(sample.keys())}')
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if 'masks_bev' in sample:
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print(f'BEV分割形状: {sample[\"masks_bev\"].shape}')
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if 'boxes_3d' in sample:
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print(f'3D检测框数量: {len(sample[\"boxes_3d\"])}')
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print('✅ 结果格式正确！')
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except Exception as e:
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print(f'❌ 结果文件读取失败: {e}')
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"
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else
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echo "❌ 推理失败，未生成结果文件"
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echo "关键错误信息:"
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grep -E "(ERROR|Error|Exception|KeyError|ImportError|RuntimeError)" "$INFER_DIR/infer_test.log" | tail -5
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exit 1
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fi
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echo ""
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echo "✅ 单Batch推理测试完成！模型配置正确"
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echo "========================================================================"
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