/// <summary>
/// Creates the neural network object from the user's inputted data
/// </summary>
private void initNN()
{
if (!this.isSynchronousNetwork)
{
this.asyncNN = new AsyncNeuralNetwork(this.neuronCounts, this.biasValues, this.asyncActivationTypes, this.numIntBits, this.numFracBits, this.numWeightIntBits, this.isClassifier, this.classifierThresholds, this.weights);
this.syncNN = null;
}
else
{
this.syncNN = new SyncNeuralNetwork(this.neuronCounts, this.biasValues, this.syncActivationTypes, this.numIntBits, this.numFracBits, this.numWeightIntBits, this.isClassifier, this.classifierThresholds, this.weights);
this.asyncNN = null;
}
}
private void TestSyncNNBtn_Click(object sender, EventArgs e)
{
List <double> weights = new List <double>();
/*first layer*/
weights.Add(0.0);
weights.Add(1.0);
weights.Add(-1.0);
weights.Add(1.0);
weights.Add(0.5);
weights.Add(-0.5);
/*Second layer*/
weights.Add(0.0);
weights.Add(1.0);
weights.Add(-1.0);
weights.Add(1.0);
weights.Add(1.0);
weights.Add(0.5);
SyncNeuralNetwork snn = new SyncNeuralNetwork(new int[] { 2, 2, 2 }, new double[] { -1, 1, 0 }, new TransferFunctionWrapper.MemoryActivationType[] { TransferFunctionWrapper.MemoryActivationType.UNIPOLAR_SIGMOID, TransferFunctionWrapper.MemoryActivationType.UNIPOLAR_SIGMOID }, 4, 4, 4, false, null, weights);
string outFile = Directory.GetCurrentDirectory() + "\\proj\\";
System.IO.FileInfo f = new FileInfo(outFile);
if (!File.Exists(outFile + "\\fixed_pkg.vhd"))
{
File.Copy("fixed_float_types.vhd", outFile + "\\fixed_float_types.vhd");
File.Copy("fixed_pkg.vhd", outFile + "\\fixed_pkg.vhd");
}
f.Directory.Create();
if (!snn.writeVHDL(outFile))
{
MessageBox.Show("Problem writing sync neural network");
}
MessageBox.Show("File Written");
}
