public Mult(ConvNetSharp <T> graph, Op <T> left, Op <T> right) : base(graph)
{
AddParent(left);
AddParent(right);
}
public Dense(ConvNetSharp <T> graph, Op <T> x, int neuronCount) : base(graph, x, 1, 1, neuronCount)
{
}
public Activation(ConvNetSharp <T> graph, Op <T> x, ActivationType type) : base(graph)
{
AddParent(x);
this.Type = type;
}
public LeakyReluGradient(ConvNetSharp <T> graph, Op <T> y, Op <T> derivate, T alpha) : base(graph)
{
this.Alpha = alpha;
this.AddParent(y);
this.AddParent(derivate);
}
public Sum(ConvNetSharp <T> graph, Op <T> x, Op <T> shape) : base(graph)
{
AddParent(x);
AddParent(shape);
}
public Softmax(Op <T> x)
{
AddParent(x);
}
public Negate(ConvNetSharp <T> graph, Op <T> x) : base(graph)
{
AddParent(x);
}
public Sum(ConvNetSharp <T> graph, Op <T> x, Shape shape) : base(graph)
{
AddParent(x);
this.OutputShape = shape;
}
public Shape(Op <T> x)
{
this._builder = BuilderInstance <T> .Create(); // we want to remain on host
AddParent(x);
}
public void RemoveParent(Op <T> parent)
{
this.Parents.Remove(parent);
parent.Children.Remove(this);
}
public ActivationGradient(ConvNetSharp <T> graph, Op <T> input, Op <T> output, Op <T> outputGradient, ActivationType type) : base(graph)
{
this.AddParent(input);
this.AddParent(output);
this.AddParent(outputGradient);
this.Type = type;
}
public ConvolutionFilterGradient(ConvNetSharp <T> graph, Convolution <T> convolution, Op <T> derivate) : base(graph)
{
this._convolution = convolution;
this.AddParent(convolution);
this.AddParent(derivate);
}
public Power(ConvNetSharp <T> graph, Op <T> u, Op <T> v) : base(graph)
{
AddParent(u);
AddParent(v);
}
