/// <summary>Creates an instance of the <code>DeConvolutionalNN</code> class.</summary>
/// <param name="firstPart">First part of the network.</param>
/// <param name="cnn">Second part of the network.</param>
/// <param name="createIO">Whether the input array and the output image of the netwok are to be created.</param>
public DeConvolutionalNN(FeedForwardNN firstPart, PurelyConvolutionalNN cnn, bool createIO = true)
{
this.firstPart = firstPart;
this.a2i = new ArrayToImage(cnn.InputDepth, cnn.InputWidth, cnn.InputHeight, false);
this.cnn = cnn;
this.errorArray = Backbone.CreateArray <float>(cnn.InputDepth * cnn.InputWidth * cnn.InputHeight);
this.errorImage = new Image(cnn.InputDepth, cnn.InputWidth, cnn.InputHeight);
this.layersConnected = false;
if (createIO)
{
this.SetInputGetOutput(Backbone.CreateArray <float>(firstPart.InputSize));
}
this.siameseID = new object();
}
/// <summary>Either creates a siamese of the given <code>ArrayToImage</code> instance or clones it.</summary>
/// <param name="original">The original instance to be created a siamese of or cloned.</param>
/// <param name="siamese"><code>true</code> if a siamese is to be created, <code>false</code> if a clone is.</param>
protected ArrayToImage(ArrayToImage original, bool siamese)
{
this.inputSize = original.InputSize;
this.outputDepth = original.OutputDepth;
this.outputWidth = original.OutputWidth;
this.outputHeight = original.OutputHeight;
if (siamese)
{
this.siameseID = original.SiameseID;
}
else
{
this.siameseID = new object();
}
}
/// <summary>Either creates a siamese or clones the given <code>DeConvolutionalNN</code> instance.</summary>
/// <param name="original">The original instance to be created a siamese of or cloned.</param>
/// <param name="siamese"><code>true</code> if a siamese is to be created, <code>false</code> if a clone is.</param>
protected DeConvolutionalNN(DeConvolutionalNN original, bool siamese)
{
this.errorArray = Backbone.CreateArray <float>(original.cnn.InputDepth * original.cnn.InputWidth * original.cnn.InputHeight);
this.errorImage = new Image(original.cnn.InputDepth, original.cnn.InputWidth, original.cnn.InputHeight);
this.layersConnected = false;
if (siamese)
{
this.firstPart = (FeedForwardNN)original.firstPart.CreateSiamese();
this.a2i = (ArrayToImage)original.a2i.CreateSiamese();
this.cnn = (PurelyConvolutionalNN)original.cnn.CreateSiamese();
this.siameseID = original.SiameseID;
}
else
{
this.firstPart = (FeedForwardNN)original.firstPart.Clone();
this.a2i = (ArrayToImage)original.a2i.Clone();
this.cnn = (PurelyConvolutionalNN)original.cnn.Clone();
this.siameseID = new object();
}
}