/// <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(model.CreateWorker(device, verbose));
}
internal static WorkerFactory.Type GetBestTypeForDevice(WorkerFactory.Device device)
{
switch (device)
{
case WorkerFactory.Device.Auto:
case WorkerFactory.Device.GPU:
return(WorkerFactory.Type.ComputePrecompiled);
default:
return(WorkerFactory.Type.CSharpBurst);
}
}
/// <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(model.CreateWorker(additionalOutputs, trimOutputs, device, verbose));
}
/// <summary>
/// Create a worker that will execute `model` 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`.
/// `model` is the associated Model to execute.
/// `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 Model model,
string[] additionalOutputs, string[] trimOutputs, WorkerFactory.Device device = WorkerFactory.Device.Auto, bool verbose = false)
{
return(WorkerFactory.CreateWorker(model, additionalOutputs, trimOutputs, device, verbose));
}
/// <summary>
/// Create a worker that will execute `model` 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`.
/// `model` is the associated Model to execute.
/// `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 Model model,
WorkerFactory.Device device = WorkerFactory.Device.Auto, bool verbose = false)
{
return(WorkerFactory.CreateWorker(model, device, verbose));
}
