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Barracuda.cs
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Barracuda.cs
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using System;
using System.Collections.Generic;
using UnityEngine;
using Unity.Barracuda;
public class Barracuda
{
private Model mRuntimeModel;
private string mInputName, mOutputName;
IWorker mWorker = null;
private static readonly Lazy<Barracuda> hInstance =
new Lazy<Barracuda>(() => new Barracuda());
public static Barracuda Instance
{
get {
return hInstance.Value;
}
}
protected Barracuda()
{
}
public void LoadModel(NNModel model)
{
mRuntimeModel = ModelLoader.Load(model);
mWorker = WorkerFactory.CreateWorker(WorkerFactory.Type.ComputePrecompiled, mRuntimeModel);
Debug.Log("model loaded");
}
public bool IsLoaded()
{
if(mWorker == null)
return false;
return true;
}
/*
private void CreateTensor()
{
float[] buffer = Enumerable.Repeat<float>(-1, size_node + (size_node * size_positions * 2)).ToArray<float>();
}
*/
public List<float> Execute_Shape1(List<float[]> tensor, int shape)
{
float[][] inputBuffer = tensor.ToArray();
var inputs = new Dictionary<string, Tensor>();
inputs[mRuntimeModel.inputs[0].name] = new Tensor(tensor.Count, shape, inputBuffer);
return Execute(inputs);
}
private List<float> Execute(Dictionary<string, Tensor> inputs)
{
/*
mInputName = mRuntimeModel.inputs[0].name;
mOutputName = mRuntimeModel.outputs[0];
*/
var output = mWorker.Execute(inputs).PeekOutput(mRuntimeModel.outputs[0]);
List<float> ret = new List<float>();
for (int n = 0; n < output.length; n++)
{
//Debug.Log(output[n].ToString());
ret.Add(output[n]);
}
inputs[mRuntimeModel.inputs[0].name].Dispose();
output.Dispose();
return ret;
}
public List<float> Execute_Shape3(float[] tensor, int[] shape)
{
var inputs = new Dictionary<string, Tensor>();
inputs[mRuntimeModel.inputs[0].name] = new Tensor(1, shape[0], shape[1], shape[2], tensor);
/*
mInputName = mRuntimeModel.inputs[0].name;
mOutputName = mRuntimeModel.outputs[0];
*/
var output = mWorker.Execute(inputs).PeekOutput(mRuntimeModel.outputs[0]);
List<float> ret = new List<float>();
for(int n = 0; n<output.length; n++)
{
//Debug.Log(output[n].ToString());
ret.Add(output[n]);
}
inputs[mRuntimeModel.inputs[0].name].Dispose();
output.Dispose();
return ret;
}
public List<float> Execute_Shape3(List<float[]> tensor, int[] shape)
{
var inputs = new Dictionary<string, Tensor>();
/*
float[] inputBuffer = new float[tensor[0].Length * tensor.Count];
for(int n=0; n < tensor.Count; n++)
{
tensor[n].CopyTo(inputBuffer, n * tensor[0].Length);
}
*/
float[][] inputBuffer = tensor.ToArray();
inputs[mRuntimeModel.inputs[0].name] = new Tensor(tensor.Count, shape[0], shape[1], shape[2], inputBuffer);
/*
mInputName = mRuntimeModel.inputs[0].name;
mOutputName = mRuntimeModel.outputs[0];
*/
var output = mWorker.Execute(inputs).PeekOutput(mRuntimeModel.outputs[0]);
List<float> ret = new List<float>();
for(int n = 0; n<output.length; n++)
{
//Debug.Log(output[n].ToString());
ret.Add(output[n]);
}
inputs[mRuntimeModel.inputs[0].name].Dispose();
output.Dispose();
return ret;
}
}