机器学习 -- ONNX 问题总结

// Imports from api-ms-win-core-heap-l2-1-0.dll

// ; Exported entry  17. LocalAlloc
// LocalAlloc      db 'kernel32.LocalAlloc',0
// ; Exported entry  18. LocalFree
// LocalFree       db 'kernel32.LocalFree',0

HLOCAL __stdcall LocalFree(HLOCAL hMem)
{
    return __imp_LocalFree(hMem);
}

#include <Windows.h>

HLOCAL WINAPI MyLocalFree(HLOCAL hMem) {
    if (hMem == NULL) {
        return NULL; // 如果指针为空，直接返回
    }

    // 使用 Windows 的 HeapFree 函数来释放内存
    HANDLE hHeap = GetProcessHeap(); // 获取默认的进程堆
    if (!HeapFree(hHeap, 0, hMem)) {
        SetLastError(ERROR_INVALID_HANDLE); // 设置错误码
        return hMem; // 返回非 NULL 表示释放失败
    }

    return NULL; // 返回 NULL 表示释放成功
}

#include <onnxruntime/core/session/onnxruntime_cxx_api.h>

// 示例修改输入数据类型
Ort::AllocatorWithDefaultOptions allocator;

// 获取模型输入信息
auto input_info = session.GetInputTypeInfo(0).GetTensorTypeAndShapeInfo();
auto input_type = input_info.GetElementType();

// 确保输入数据类型是 float16
if (input_type == ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT16) {
    std::cout << "Model input type is float16." << std::endl;
} else {
    throw std::runtime_error("Unexpected input type. Expected float16.");
}

#include <onnxruntime/core/common/float16.h>

// 示例 float32 转 float16
std::vector<float> input_data_float32 = {1.0f, 2.0f, 3.0f}; // 假设输入是 float32
std::vector<uint16_t> input_data_float16(input_data_float32.size());

for (size_t i = 0; i < input_data_float32.size(); ++i) {
    input_data_float16[i] = onnxruntime::math::floatToHalf(input_data_float32[i]);
}

Ort::MemoryInfo memory_info = Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault);

Ort::Value input_tensor = Ort::Value::CreateTensor<uint16_t>(
    memory_info, input_data_float16.data(), input_data_float16.size(),
    input_dims.data(), input_dims.size());