Exemplo n.º 1
0
        /// <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));
        }
Exemplo n.º 2
0
        /// <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));
        }
Exemplo n.º 3
0
        // 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);
        }
Exemplo n.º 4
0
 /// <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));
 }
Exemplo n.º 5
0
 /// <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));
 }