LearningModel.OutputFeatures 属性

public:
 property IVectorView<ILearningModelFeatureDescriptor ^> ^ OutputFeatures { IVectorView<ILearningModelFeatureDescriptor ^> ^ get(); };

IVectorView<ILearningModelFeatureDescriptor> OutputFeatures();

public IReadOnlyList<ILearningModelFeatureDescriptor> OutputFeatures { get; }

var iVectorView = learningModel.outputFeatures;

Public ReadOnly Property OutputFeatures As IReadOnlyList(Of ILearningModelFeatureDescriptor)

属性值

模型的输出特征列表。

示例

以下示例加载模型，使用模型创建评估会话，并获取模型的输入和输出功能。

private async Task LoadModelAsync(string _modelFileName)
{
    LearningModel _model;
    LearningModelSession _session;
    ImageFeatureDescriptor _inputImageDescription;
    TensorFeatureDescriptor _outputImageDescription;

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

        // Create the evaluation session with the model
        _session = new LearningModelSession(_model);

        //Get input and output features of the model
        List<ILearningModelFeatureDescriptor> inputFeatures = _model.InputFeatures.ToList();
        List<ILearningModelFeatureDescriptor> outputFeatures = _model.OutputFeatures.ToList();

        // Retrieve the first input feature which is an image
        _inputImageDescription = inputFeatures.FirstOrDefault(
            feature => feature.Kind == LearningModelFeatureKind.Image) as ImageFeatureDescriptor;

        // Retrieve the first output feature which is a tensor
        _outputImageDescription = outputFeatures.FirstOrDefault(
            feature => feature.Kind == LearningModelFeatureKind.Tensor) as TensorFeatureDescriptor;
    }
    catch (Exception ex)
    {
        StatusBlock.Text = $"error: {ex.Message}";
        _model = null;
    }
}

注解

Windows Server

若要在 Windows Server 上使用此 API，必须使用具有桌面体验的 Windows Server 2019。

线程安全

此 API 是线程安全的。

适用于