/// <summary>
/// Initializes a new instance of the <see cref="OnnxModel"/> class.
/// </summary>
/// <param name="configuration">The configuration for the onnx model runner.</param>
public OnnxModel(OnnxModelConfiguration configuration)
{
this.configuration = configuration;
// The schemaDefinition is a ML.NET construct that allows us to specify the form
// of the inputs. In this case we construct a schema definition programmatically
// to reflect that the input is a vector of floats, of the sizes specified in the
// configuration
this.schemaDefinition = SchemaDefinition.Create(typeof(OnnxInputVector));
this.schemaDefinition[nameof(OnnxInputVector.Vector)].ColumnType = new VectorDataViewType(NumberDataViewType.Single, this.configuration.InputVectorSize);
this.schemaDefinition[nameof(OnnxInputVector.Vector)].ColumnName = this.configuration.InputVectorName;
// We create the onnxTransformer which will be used to score inputs
var onnxEmptyInputDataView = this.context.Data.LoadFromEnumerable(new List <OnnxInputVector>(), this.schemaDefinition);
var scoringEstimator =
this.context.Transforms.ApplyOnnxModel(
modelFile: configuration.ModelFileName,
outputColumnNames: new[] { configuration.OutputVectorName },
inputColumnNames: new[] { configuration.InputVectorName },
shapeDictionary: configuration.ShapeDictionary,
gpuDeviceId: configuration.GpuDeviceId,
fallbackToCpu: false);
this.onnxTransformer = scoringEstimator.Fit(onnxEmptyInputDataView);
}
/// <summary>
/// Initializes a new instance of the <see cref="OnnxModelRunner"/> class, based on a given configuration.
/// </summary>
/// <param name="pipeline">The pipeline to add the component to.</param>
/// <param name="configuration">The component configuration.</param>
/// <param name="name">An optional name for the component.</param>
/// <remarks>The configuration parameter specifies the model filename, the
/// name of the input and output vectors in that ONNX model, as well as
/// the input vector size.</remarks>
public OnnxModelRunner(Pipeline pipeline, OnnxModelConfiguration configuration, string name = nameof(OnnxModelRunner))
: base(pipeline, name)
{
this.inputVectorSize = configuration.InputVectorSize;
this.onnxModel = new OnnxModel(configuration);
}
/// <summary>
/// Initializes a new instance of the <see cref="OnnxModelRunner"/> class, based on a given configuration.
/// </summary>
/// <param name="pipeline">The pipeline to add the component to.</param>
/// <param name="configuration">The component configuration.</param>
/// <remarks>The configuration parameter specifies the model filename, the
/// name of the input and output vectors in that ONNX model, as well as
/// the input vector size.</remarks>
public OnnxModelRunner(Pipeline pipeline, OnnxModelConfiguration configuration)
: base(pipeline)
{
this.inputVectorSize = configuration.InputVectorSize;
this.onnxModel = new OnnxModel(configuration);
}
