LightGlueProject/LightGlue_Deployment/check_tensorrt_usage.py

#!/usr/bin/env python3
"""
检查程序运行时是否使用了 TensorRT
"""

import sys
import re

def check_log_for_tensorrt(log_file=None):
    """检查日志文件中是否有 TensorRT 相关信息"""
    
    if log_file:
        try:
            with open(log_file, 'r', encoding='utf-8') as f:
                content = f.read()
        except:
            print(f"无法读取日志文件: {log_file}")
            return False
    else:
        print("请提供日志文件路径，或直接查看程序输出")
        return None
    
    # 检查 TensorRT 相关关键词
    tensorrt_indicators = [
        r"Compiling models with TensorRT",
        r"TensorRT optimization completed",
        r"SuperPoint compiled with TensorRT",
        r"Precision: (fp16|fp32|int8)",  # TensorRT 精度设置
    ]
    
    found = False
    for pattern in tensorrt_indicators:
        if re.search(pattern, content, re.IGNORECASE):
            print(f"✓ 找到 TensorRT 使用证据: {pattern}")
            found = True
    
    if not found:
        # 检查是否有警告信息
        if "Warning: TensorRT" in content or "Failed to compile with TensorRT" in content:
            print("✗ TensorRT 编译失败或未启用")
        else:
            print("✗ 未找到 TensorRT 使用证据")
            print("  可能原因：")
            print("  1. 运行时未使用 --use_tensorrt 参数")
            print("  2. TensorRT 编译失败，回退到 PyTorch")
            print("  3. 程序在 CPU 上运行（TensorRT 需要 CUDA）")
    
    return found

def check_command_line():
    """检查命令行参数"""
    print("="*60)
    print("如何判断是否使用了 TensorRT：")
    print("="*60)
    print()
    print("1. 查看程序启动时的输出：")
    print("   如果使用了 TensorRT，会看到：")
    print("   ============================================================")
    print("   Compiling models with TensorRT...")
    print("   Precision: fp16")
    print("   This may take several minutes on first run...")
    print("   ============================================================")
    print()
    print("2. 编译成功后会看到：")
    print("   ✓ SuperPoint compiled with TensorRT")
    print("   ✓ TensorRT optimization completed")
    print()
    print("3. 检查运行命令：")
    print("   必须包含 --use_tensorrt 参数")
    print()
    print("4. 性能对比：")
    print("   - PyTorch FP16: ~22 FPS")
    print("   - TensorRT FP16: ~35-45 FPS")
    print("   如果 FPS 明显提升，说明使用了 TensorRT")
    print()
    print("="*60)
    print("正确的运行命令应该是：")
    print("="*60)
    print()
    print('python demo_lightglue_camera_position_async.py ^')
    print('    --input "udp://0.0.0.0:12346" ^')
    print('    --max_keypoints 128 ^')
    print('    --use_fp16 ^')
    print('    --use_tensorrt ^')
    print('    --tensorrt_precision fp16')
    print()

if __name__ == "__main__":
    if len(sys.argv) > 1:
        log_file = sys.argv[1]
        check_log_for_tensorrt(log_file)
    else:
        check_command_line()