開始使用 Windows ML

• .NET 6 或更新版本
• 以 Windows 10 特定 TFM 為目標，類似 net6.0-windows10.0.19041.0 或更新版本

C++20 或更新版本。

Python 3.10 至 3.13 版，適用於 x64 和 ARM64 裝置。

如需如何在 現有專案中使用 Windows 應用程式 SDK ，了解如何將 Windows 應用程式 SDK 新增至您的專案，或者如果您已經在使用 Windows 應用程式 SDK，請更新您的套件。

如需如何在 現有專案中使用 Windows 應用程式 SDK ，了解如何將 Windows 應用程式 SDK 新增至您的專案，或者如果您已經在使用 Windows 應用程式 SDK，請更新您的套件。

Python 繫結會利用 pywinrt 專案進行 Windows 應用程式 SDK 投影。 請確保你的 Python 安裝不是來自 Microsoft 商店（你可以從 python.org 或 winget 安裝未打包版本）。 範例依賴使用 Windows App SDK 動態相依 API，該 API 僅適用於未封裝的應用程式。

請使用以下命令安裝 python 套件：

pip install wasdk-Microsoft.Windows.AI.MachineLearning[all] wasdk-Microsoft.Windows.ApplicationModel.DynamicDependency.Bootstrap
# The onnxruntime-winml package is not published to PyPI yet. Please install it from the ort-nightly feed
pip install --pre --index-url https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/ORT-Nightly/pypi/simple/ --extra-index-url https://pypi.org/simple onnxruntime-winml

請確定 wasdk- 套件的版本符合 WindowsAppRuntime 的版本。

using Microsoft.ML.OnnxRuntime;
using Microsoft.Windows.AI.MachineLearning;

// First we create a new instance of EnvironmentCreationOptions
EnvironmentCreationOptions envOptions = new()
{
    logId = "WinMLDemo", // Use an ID of your own choice
    logLevel = OrtLoggingLevel.ORT_LOGGING_LEVEL_ERROR
};

// And then use that to create the ORT environment
using var ortEnv = OrtEnv.CreateInstanceWithOptions(ref envOptions);

// Get the default ExecutionProviderCatalog
var catalog = ExecutionProviderCatalog.GetDefault();

// Ensure and register all compatible execution providers with ONNX Runtime
// This downloads any necessary components and registers them
await catalog.EnsureAndRegisterCertifiedAsync();

#include <winrt/Microsoft.Windows.AI.MachineLearning.h>
#include <winml/onnxruntime_cxx_api.h>

// First we need to create an ORT environment
Ort::Env env(ORT_LOGGING_LEVEL_ERROR, "WinMLDemo"); // Use an ID of your own choice

// Get the default ExecutionProviderCatalog
winrt::Microsoft::Windows::AI::MachineLearning::ExecutionProviderCatalog catalog =
    winrt::Microsoft::Windows::AI::MachineLearning::ExecutionProviderCatalog::GetDefault();

// Ensure and register all compatible execution providers with ONNX Runtime
catalog.EnsureAndRegisterCertifiedAsync().get();

import sys
from pathlib import Path
import traceback

_winml_instance = None

class WinML:
    def __new__(cls, *args, **kwargs):
        global _winml_instance
        if _winml_instance is None:
            _winml_instance = super(WinML, cls).__new__(cls, *args, **kwargs)
            _winml_instance._initialized = False
        return _winml_instance

    def __init__(self):
        if self._initialized:
            return
        self._initialized = True

        self._fix_winrt_runtime()
        from winui3.microsoft.windows.applicationmodel.dynamicdependency.bootstrap import (
            InitializeOptions,
            initialize
        )
        import winui3.microsoft.windows.ai.machinelearning as winml
        self._win_app_sdk_handle = initialize(options=InitializeOptions.ON_NO_MATCH_SHOW_UI)
        self._win_app_sdk_handle.__enter__()
        catalog = winml.ExecutionProviderCatalog.get_default()
        self._providers = catalog.find_all_providers()
        self._ep_paths : dict[str, str] = {}
        for provider in self._providers:
            provider.ensure_ready_async().get()
            if provider.library_path == '':
                continue
            self._ep_paths[provider.name] = provider.library_path
        self._registered_eps : list[str] = []

    def __del__(self):
        self._providers = None
        self._win_app_sdk_handle.__exit__(None, None, None)

    def _fix_winrt_runtime(self):
        """
        This function removes the msvcp140.dll from the winrt-runtime package.
        So it does not cause issues with other libraries.
        """
        from importlib import metadata
        site_packages_path = Path(str(metadata.distribution('winrt-runtime').locate_file('')))
        dll_path = site_packages_path / 'winrt' / 'msvcp140.dll'
        if dll_path.exists():
            dll_path.unlink()

    def register_execution_providers_to_ort(self) -> list[str]:
        import onnxruntime as ort
        for name, path in self._ep_paths.items():
            if name not in self._registered_eps:
                try:
                    ort.register_execution_provider_library(name, path)
                    self._registered_eps.append(name)
                except Exception as e:
                    print(f"Failed to register execution provider {name}: {e}", file=sys.stderr)
                    traceback.print_exc()
        return self._registered_eps

WinML().register_execution_providers_to_ort()