LearningModelDevice Classe

Definizione

public ref class LearningModelDevice sealed

/// [Windows.Foundation.Metadata.Activatable(Windows.AI.MachineLearning.ILearningModelDeviceFactory, 65536, "Windows.AI.MachineLearning.MachineLearningContract")]
/// [Windows.Foundation.Metadata.ContractVersion(Windows.AI.MachineLearning.MachineLearningContract, 65536)]
/// [Windows.Foundation.Metadata.MarshalingBehavior(Windows.Foundation.Metadata.MarshalingType.Agile)]
/// [Windows.Foundation.Metadata.Threading(Windows.Foundation.Metadata.ThreadingModel.Both)]
class LearningModelDevice final

[Windows.Foundation.Metadata.Activatable(typeof(Windows.AI.MachineLearning.ILearningModelDeviceFactory), 65536, "Windows.AI.MachineLearning.MachineLearningContract")]
[Windows.Foundation.Metadata.ContractVersion(typeof(Windows.AI.MachineLearning.MachineLearningContract), 65536)]
[Windows.Foundation.Metadata.MarshalingBehavior(Windows.Foundation.Metadata.MarshalingType.Agile)]
[Windows.Foundation.Metadata.Threading(Windows.Foundation.Metadata.ThreadingModel.Both)]
public sealed class LearningModelDevice

function LearningModelDevice(deviceKind)

Public NotInheritable Class LearningModelDevice

Ereditarietà

Object Platform::Object IInspectable LearningModelDevice

Attributi

ActivatableAttribute ContractVersionAttribute MarshalingBehaviorAttribute ThreadingAttribute

Requisiti Windows

Esempio

L'esempio seguente carica un modello, seleziona il dispositivo in cui valutare il modello e crea una sessione di valutazione.

private async Task LoadModelAsync(string _modelFileName, bool _useGPU)
{
    LearningModel _model;
    LearningModelSession _session;

    try
    {
        // Load and create the model
        var modelFile = 
            await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Assets/{_modelFileName}"));
        _model = await LearningModel.LoadFromStorageFileAsync(modelFile);

        // Select the device to evaluate on
        LearningModelDevice device = null;
        if (_useGPU)
        {
            // Use a GPU or other DirectX device to evaluate the model.
            device = new LearningModelDevice(LearningModelDeviceKind.DirectX);
        }
        else
        {
            // Use the CPU to evaluate the model.
            device = new LearningModelDevice(LearningModelDeviceKind.Cpu);
        }

        // Create the evaluation session with the model and device.
        _session = new LearningModelSession(_model, device);

    }
    catch (Exception ex)
    {
        StatusBlock.Text = $"error: {ex.Message}";
        _model = null;
    }
}

Commenti

Windows Server

Per usare questa API in Windows Server, è necessario usare Windows Server 2019 con Esperienza desktop.

Thread safety

Questa API è thread-safe.

Costruttori

Proprietà

Metodi

Si applica a

Vedi anche

• Windows ML
• Esempi di Windows ML (GitHub)