public void OnStartCompute()
{
// Only continue if the server is not already computing:
if (isComputing)
{
return;
}
isComputing = true;
if (pointAtManager)
{
pointAtManager.WriteToConfig();
}
if (UI)
{
UI.UpdateProgressText(" Processing...");
}
else
{
Debug.LogError("ERROR: No UI Object found. ");
}
if (evalSimple)
{
CLayerType[] layers = new CLayerType[Layers.Count];
for (int i = 0; i < Layers.Count; i++)
{
layers[i] = Layers[i].layerType;
}
StartCoroutine(evalSimple.Evaluate(layers));
}
}
public IEnumerator Evaluate(CLayerType[] simpleLayers)
{
if (modelHandler)
{
modelHandler.ShowGPUs(true);
}
EvaluateRequest req = new EvaluateRequest {
};
bool flat = false;
for (int i = 0; i < simpleLayers.Length; i++)
{
CLayerType l = simpleLayers[i];
switch (l)
{
case CLayerType.Conv:
if (flat)
{
throw new System.ArgumentException("tried to add multidimensional layer after flatten");
}
req.Layers.Add(new Evaluator.Layer {
Convolution = new Evaluator.ConvolutionLayer {
Filters = 32
}
});
break;
case CLayerType.Full:
case CLayerType.Dense:
if (!flat)
{
req.Layers.Add(new Evaluator.Layer {
Flatten = new Evaluator.FlattenLayer {
}
});
flat = true;
}
req.Layers.Add(new Evaluator.Layer {
Dense = new Evaluator.DenseLayer {
Neurons = 128
}
});
break;
case CLayerType.Pool:
if (flat)
{
throw new System.ArgumentException("tried to add multidimensional layer after flatten");
}
req.Layers.Add(new Evaluator.Layer {
Maxpooling = new Evaluator.MaxpoolingLayer {
}
});
break;
case CLayerType.Dropout:
req.Layers.Add(new Evaluator.Layer {
Dropout = new Evaluator.DropoutLayer {
Dimension = 0.5f
}
});
break;
default:
throw new System.ArgumentException("unknown layer type: " + l);
}
}
if (!flat)
{
//req.Layers.Add(new Evaluator.Layer { Convolution = new Evaluator.ConvolutionLayer { Filters = 32 } });
req.Layers.Add(new Evaluator.Layer {
Flatten = new Evaluator.FlattenLayer {
}
});
}
bIsCalculating = true;
using (var call = client.EvaluateAsync(req)) {
//StartCoroutine(UpdateProgress());
while (!call.ResponseAsync.IsCompleted)
{
//accuracy = call.ResponseAsync.Result.Accuracy;
yield return(new WaitForSeconds(0.5f));
}
bIsCalculating = false;
accuracy = call.ResponseAsync.Result.Accuracy;
if (manager)
{
manager.CompleteComputation(accuracy);
}
yield return(new WaitForSeconds(0.5f));
if (modelHandler)
{
modelHandler.Reset();
}
}
}
public IEnumerator Evaluate(CLayerType[] simpleLayers)
{
yield return(null);
string args = "";
bool flat = false;
for (int i = 0; i < simpleLayers.Length; i++)
{
CLayerType l = simpleLayers[i];
switch (l)
{
case CLayerType.Conv:
if (flat)
{
throw new System.ArgumentException("tried to add multidimensional layer after flatten");
}
args += "Conv2D:" + "32,"; // :filters
break;
case CLayerType.Full:
case CLayerType.Dense:
if (!flat)
{
args += "Flatten,";
flat = true;
}
args += "Dense:128,";
break;
case CLayerType.Pool:
if (flat)
{
throw new System.ArgumentException("tried to add multidimensional layer after flatten");
}
args += "Pool,";
break;
case CLayerType.Dropout:
args += "Dropout:0.5,";
break;
default:
throw new System.ArgumentException("unknown layer type: " + l);
}
}
if (!flat)
{
args += "Flatten,";
}
args += "$"; // End of stream
// Send to python as string
bIsCalculating = true;
RunPythonScript("python evaluator.py", args);
/*using (var call = client.EvaluateAsync(req))
* {
* StartCoroutine(UpdateProgress());
* while (!call.ResponseAsync.IsCompleted)
* {
* //accuracy = call.ResponseAsync.Result.Accuracy;
* yield return new WaitForSeconds(0.5f);
* }
* bIsCalculating = false;
* accuracy = call.ResponseAsync.Result.Accuracy;
* if (manager) manager.CompleteComputation(accuracy);
* }*/
}
private void Start()
{
type = Layer.layerType;
}
