我需要上面的C++代码

好的，以下是使用C++调用ONNX Runtime的TensorRT执行器的示例代码：

#include <iostream>
#include <vector>
#include <chrono>
#include <onnxruntime_cxx_api.h>

int main()
{
    // Load the ONNX model
    Ort::SessionOptions session_options;
    session_options.SetIntraOpNumThreads(1); // Set the number of threads
    session_options.SetExecutionMode(ORT_SEQUENTIAL); // Set the execution mode
    session_options.SetOptimizedModelFilePath("path/to/your/optimized/onnx/model"); // Set the path to optimized ONNX model
    session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_ALL); // Set the optimization level
    session_options.AddConfigEntry("session.gpus", "0"); // Set the GPU device ID
    const char* model_path = "path/to/your/onnx/model";
    Ort::Session session(env, model_path, session_options);

    // Get the input and output names
    std::vector<const char*> input_names = session.GetInputNames();
    std::vector<const char*> output_names = session.GetOutputNames();
    Ort::TypeInfo input_type_info = session.GetInputTypeInfo(0);
    Ort::TypeInfo output_type_info = session.GetOutputTypeInfo(0);
    auto input_tensor_info = input_type_info.GetTensorTypeAndShapeInfo();
    auto output_tensor_info = output_type_info.GetTensorTypeAndShapeInfo();

    // Prepare the input tensor
    std::vector<int64_t> input_shape = input_tensor_info.GetShape();
    std::vector<float> input_data(input_shape[0] * input_shape[1] * input_shape[2] * input_shape[3]);
    float* input_data_ptr = input_data.data();
    Ort::MemoryInfo input_memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
    size_t input_tensor_size = input_data.size() * sizeof(float);
    Ort::Value input_tensor = Ort::Value::CreateTensor<float>(input_memory_info, input_data_ptr, input_tensor_size, input_shape.data(), input_shape.size());
    void* input_data_buffer = input_tensor.GetTensorMutableData<float>();

    // Run the model
    std::vector<Ort::Value> inputs;
    std::vector<Ort::Value> outputs;
    inputs.push_back(input_tensor);
    auto start = std::chrono::high_resolution_clock::now();
    session.Run(Ort::RunOptions{ nullptr }, input_names.data(), inputs.data(), inputs.size(), output_names.data(), outputs.size());
    auto end = std::chrono::high_resolution_clock::now();
    std::chrono::duration<double> elapsed_seconds = end - start;
    std::cout << "Inference time: " << elapsed_seconds.count() << " s" << std::endl;

    // Get the output tensor
    std::vector<int64_t> output_shape = output_tensor_info.GetShape();
    std::vector<float> output_data(output_shape[0] * output_shape[1] * output_shape[2] * output_shape[3]);
    float* output_data_ptr = output_data.data();
    Ort::MemoryInfo output_memory_info = Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
    size_t output_tensor_size = output_data.size() * sizeof(float);
    Ort::Value output_tensor = Ort::Value::CreateTensor<float>(output_memory_info, output_data_ptr, output_tensor_size, output_shape.data(), output_shape.size());
    void* output_data_buffer = output_tensor.GetTensorMutableData<float>();
    outputs.push_back(output_tensor);
}

你需要根据你的需求调整会话选项，例如设置线程数、优化级别以及GPU设备ID等。