rtsp_tensorrt/tests/test_cuda_helper.cpp

#include <gtest/gtest.h>
#include "pipeline/inference/cuda_helper.hpp"
#include <thread>
#include <chrono>
#include <cstring>
#include <iostream>

using namespace pipeline;
using namespace pipeline::detail;

class CudaHelperTest : public ::testing::Test {
protected:
    void SetUp() override {
        // 检查CUDA设备
        int device_count;
        cudaError_t err = cudaGetDeviceCount(&device_count);
        if (err != cudaSuccess) {
            std::cerr << "CUDA Error: " << cudaGetErrorString(err) << std::endl;
        }
        ASSERT_EQ(err, cudaSuccess);
        ASSERT_GT(device_count, 0);
        
        // 设置设备
        err = cudaSetDevice(0);
        if (err != cudaSuccess) {
            std::cerr << "CUDA Error: " << cudaGetErrorString(err) << std::endl;
        }
        ASSERT_EQ(err, cudaSuccess);
    }

    void TearDown() override {
        cudaDeviceSynchronize();
        cudaDeviceReset();
    }
};

// 测试CUDA流
TEST_F(CudaHelperTest, CudaStream) {
    // 创建流
    CudaStream stream;
    EXPECT_NE(stream.get(), nullptr);
    
    // 测试同步
    EXPECT_TRUE(stream.sync());
}

// 测试CUDA内存缓冲区
TEST_F(CudaHelperTest, CudaBuffer) {
    const size_t size = 1024;  // 1KB
    const size_t num_elements = size / sizeof(float);
    
    try {
        // 创建缓冲区
        CudaBuffer buffer(size);
        ASSERT_NE(buffer.devicePtr(), nullptr) << "Device memory allocation failed";
        ASSERT_NE(buffer.hostPtr(), nullptr) << "Host memory allocation failed";
        ASSERT_EQ(buffer.size(), size);
        
        // 测试内存拷贝
        float* host_data = static_cast<float*>(buffer.hostPtr());
        for (size_t i = 0; i < num_elements; ++i) {
            host_data[i] = static_cast<float>(i);
        }
        
        // 主机到设备
        ASSERT_TRUE(buffer.copyH2D()) << "Host to Device copy failed";
        
        // 清空主机内存
        memset(host_data, 0, size);
        
        // 验证主机内存已清空
        for (size_t i = 0; i < num_elements; ++i) {
            ASSERT_FLOAT_EQ(host_data[i], 0.0f) << "Host memory clear failed at index " << i;
        }
        
        // 设备到主机
        ASSERT_TRUE(buffer.copyD2H()) << "Device to Host copy failed";
        
        // 验证数据
        for (size_t i = 0; i < num_elements; ++i) {
            if (host_data[i] != static_cast<float>(i)) {
                std::cerr << "Data mismatch at index " << i 
                         << ": expected " << static_cast<float>(i)
                         << ", got " << host_data[i] << std::endl;
            }
            ASSERT_FLOAT_EQ(host_data[i], static_cast<float>(i))
                << "Data verification failed at index " << i;
        }
        
        // 同步设备
        ASSERT_EQ(cudaDeviceSynchronize(), cudaSuccess) << "Device synchronization failed";
        
    } catch (const std::exception& e) {
        FAIL() << "Exception caught: " << e.what();
    }
}

// 测试异步操作
TEST_F(CudaHelperTest, AsyncOperations) {
    const size_t size = 1024;  // 减小测试数据大小
    const size_t num_elements = size / sizeof(float);
    
    try {
        CudaStream stream;
        CudaBuffer buffer(size);
        
        // 填充测试数据
        float* host_data = static_cast<float*>(buffer.hostPtr());
        for (size_t i = 0; i < num_elements; ++i) {
            host_data[i] = static_cast<float>(i);
        }
        
        // 异步拷贝
        ASSERT_TRUE(buffer.copyH2D(stream.get())) << "Async H2D copy failed";
        ASSERT_TRUE(buffer.copyD2H(stream.get())) << "Async D2H copy failed";
        
        // 同步并验证
        ASSERT_TRUE(stream.sync()) << "Stream synchronization failed";
        for (size_t i = 0; i < num_elements; ++i) {
            ASSERT_FLOAT_EQ(host_data[i], static_cast<float>(i))
                << "Async data verification failed at index " << i;
        }
    } catch (const std::exception& e) {
        FAIL() << "Exception caught: " << e.what();
    }
}

// 测试TensorRT日志器
TEST_F(CudaHelperTest, Logger) {
    pipeline::detail::Logger logger;
    
    // 测试不同级别的日志
    logger.log(nvinfer1::ILogger::Severity::kINFO, "Info message");
    logger.log(nvinfer1::ILogger::Severity::kWARNING, "Warning message");
    logger.log(nvinfer1::ILogger::Severity::kERROR, "Error message");
}

// 测试多线程场景
TEST_F(CudaHelperTest, MultiThread) {
    const size_t num_threads = 2;  // 减少线程数
    const size_t size = 1024;      // 减小每个线程的数据大小
    std::vector<std::thread> threads;
    
    try {
        for (size_t i = 0; i < num_threads; ++i) {
            threads.emplace_back([size]() {
                CudaStream stream;
                CudaBuffer buffer(size);
                
                float* host_data = static_cast<float*>(buffer.hostPtr());
                for (size_t j = 0; j < size / sizeof(float); ++j) {
                    host_data[j] = static_cast<float>(j);
                }
                
                EXPECT_TRUE(buffer.copyH2D(stream.get()));
                EXPECT_TRUE(buffer.copyD2H(stream.get()));
                EXPECT_TRUE(stream.sync());
            });
        }
        
        // 等待所有线程完成
        for (auto& thread : threads) {
            thread.join();
        }
    } catch (const std::exception& e) {
        FAIL() << "Exception caught in thread: " << e.what();
    }
}