public Pooling(Shape inputShape, Shape outputShape, Shape kernelShape, Array <int> strides, IOperation poolOp, double padVal = 0.0) : base(outputShape)
{
InputShape = inputShape;
KernelShape = kernelShape;
Strides = strides;
PoolOp = poolOp;
PadVal = padVal;
Paddings = Padder.CalcPadding(inputShape, outputShape, kernelShape, strides, true);
PaddedShape = inputShape.Pad(Paddings);
}
public Convolutional(Shape inputShape, Shape outputShape, Shape kernelShape, Array <int> strides, IActivation activation,
IInitializer?weightInit = null, IInitializer?biasInit = null, double padVal = 0.0)
: base(outputShape, activation, weightInit, biasInit)
{
ValidateChannels(inputShape, outputShape, kernelShape, strides);
InputShape = inputShape;
KernelShape = kernelShape;
Strides = strides;
PadVal = padVal;
Paddings = Padder.CalcPadding(inputShape, outputShape, kernelShape, strides, false);
PaddedShape = inputShape.Pad(Paddings);
KernelsNum = outputShape.Dims[0] / inputShape.Dims[0];
Kernels = new Array <Kernel>(KernelsNum, () => new Kernel(kernelShape));
Neurons = new Array <Neuron>(outputShape.Volume, () => new CNeuron());
}
