/// <summary>
/// Create a worker that will execute `asset` using the best backend that is available for a given `device` type.
/// This is just a convenience function that internally calls `ModelLoader.Load` followed by ``WorkerFactory.CreateWorker`.
/// `asset` is the associated NNModel asset.
/// `additionalOutputs` are the additional outputs to track but not directly specified by the model.
/// `trimOutputs` are the outputs not discard even if they are specified by the model.
/// `device` is the device type to run worker on. For example `WorkerFactory.Device.GPU` specifies the fast GPU path.
/// `verbose` will log scheduling of layers execution to the console (default == false)
/// </summary>
public static IWorker CreateWorker(this NNModel asset,
string[] additionalOutputs, string[] trimOutputs, WorkerFactory.Device device = WorkerFactory.Device.Auto, bool verbose = false)
{
var model = ModelLoader.Load(asset);
return(WorkerFactory.CreateWorker(model, additionalOutputs, trimOutputs, device, verbose));
}
/// <summary>
/// Create a worker that will execute `asset` using the best backend that is available for a given `device` type.
/// This is just a convenience function that internally calls `ModelLoader.Load` followed by ``WorkerFactory.CreateWorker`.
/// `asset` is the associated NNModel asset.
/// `device` is the preferred device for execution. For example `WorkerFactory.Device.GPU` specifies the fast GPU path.
/// `verbose` will log scheduling of layers execution to the console.
/// </summary>
public static IWorker CreateWorker(this NNModel asset,
WorkerFactory.Device device = WorkerFactory.Device.Auto, bool verbose = false)
{
var model = ModelLoader.Load(asset);
return(WorkerFactory.CreateWorker(model, device, verbose));
}
// Asset importer callback
public override void OnImportAsset(AssetImportContext ctx)
{
var onnxModel = new ModelProto();
using (var readStream = new FileStream(ctx.assetPath, FileMode.Open))
using (var inputStream = new CodedInputStream(readStream))
onnxModel.MergeFrom(inputStream);
var model = ConvertOnnxModel(onnxModel);
D.Log($"ONNX v{model.IrVersion}. Producer: {model.ProducerName}. Asset path: {ctx.assetPath}");
D.Log($"Barracuda model: {model}");
NNModelData assetData = ScriptableObject.CreateInstance <NNModelData>();
using (var memoryStream = new MemoryStream())
using (var writer = new BinaryWriter(memoryStream))
{
ModelWriter.Save(writer, model);
assetData.Value = memoryStream.ToArray();
}
assetData.name = "Data";
assetData.hideFlags = HideFlags.HideInHierarchy;
NNModel asset = ScriptableObject.CreateInstance <NNModel>();
asset.modelData = assetData;
ctx.AddObjectToAsset("main obj", asset, LoadIconTexture());
ctx.AddObjectToAsset("model data", assetData);
ctx.SetMainObject(asset);
}
/// <summary>
/// Return an object oriented representation (aka: `Model`) of a neural network from a binary representation of type `NNModel`.
/// By default details are logged to the console, set `verbose` to false to load silently.
/// </summary>
public static Model Load(NNModel model, bool verbose = true)
{
return(Load(model.Value, verbose));
}
/// <summary>
/// Return an object oriented representation (aka: `Model`) of a neural network from a binary representation of type `NNModel`.
/// By default details are not logged to the console, set `verbose` to true to see loading details.
/// </summary>
public static Model Load(NNModel model, bool verbose = false)
{
return(Load(model.modelData.Value, verbose));
}
