public override void Connect(Layer inLayer)
{
if (inLayer.Shape != InputShape)
{
throw new ShapeMismatchException(nameof(inLayer));
}
ShapedArray <Neuron> padded = Padder.PadArray(inLayer.Neurons.ToShape(Shape), Paddings, () => new Neuron()
{
OutVal = PadVal
});
var inConnections = new ShapedArray <List <Synapse> >(PaddedShape, () => new List <Synapse>());
IndexGen.ByStrides(PaddedShape, Strides, KernelShape).ForEach((idxKernel, i) =>
{
Neuron outN = base.Neurons[i];
outN.InSynapses = IndexGen.ByStart(KernelShape, Array <int> .FromRef(idxKernel)).Select((idx, j) =>
{
var S = new Synapse(padded[idx], outN);
inConnections[idx].Add(S);
return(S);
});
});
padded.ForEach((N, i) => N.OutSynapses = Array <Synapse> .FromRef(inConnections[i].ToArray()));
}
/// <inheritdoc/>
protected override Measurement Measure(RenderContext context, int maxWidth)
{
var child = new Padder(_child, Padding);
var childWidth = ((IRenderable)child).Measure(context, maxWidth);
return(new Measurement(
childWidth.Min + EdgeWidth,
childWidth.Max + EdgeWidth));
}
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());
}
public override void Connect(Layer inLayer)
{
if (inLayer.Shape != InputShape)
{
throw new ShapeMismatchException(nameof(inLayer));
}
ShapedArray <Neuron> padded = Padder.PadArray(inLayer.Neurons.ToShape(Shape), Paddings, () => new Neuron()
{
OutVal = PadVal
});
var inConnections = new ShapedArray <List <Synapse> >(PaddedShape, () => new List <Synapse>());
Kernels.ForEach((kernel, i) =>
{
int offset = i * Shape.Volume / KernelsNum;
IndexGen.ByStrides(PaddedShape, Strides, KernelShape).ForEach((idxKernel, j) =>
{
var outN = (CNeuron)Neurons[offset + j];
outN.KernelBias = kernel.Bias;
outN.InSynapses = IndexGen.ByStart(KernelShape, Array <int> .FromRef(idxKernel)).Select((idx, k) =>
{
var S = new CSynapse(padded[idx], outN)
{
KernelWeight = kernel.Weights[k]
};
inConnections[idx].Add(S);
return((Synapse)S);
});
});
});
padded.ForEach((N, i) => N.OutSynapses = Array <Synapse> .FromRef(inConnections[i].ToArray()));
}
/// <inheritdoc/>
protected override IEnumerable <Segment> Render(RenderContext context, int maxWidth)
{
var edgeWidth = EdgeWidth;
var border = BoxExtensions.GetSafeBorder(Border, !context.Unicode && UseSafeBorder);
var borderStyle = BorderStyle ?? Style.Plain;
var showBorder = true;
if (border is NoBoxBorder)
{
showBorder = false;
edgeWidth = 0;
}
var child = new Padder(_child, Padding);
var childWidth = maxWidth - edgeWidth;
if (!Expand)
{
var measurement = ((IRenderable)child).Measure(context, maxWidth - edgeWidth);
childWidth = measurement.Max;
}
var panelWidth = childWidth + edgeWidth;
panelWidth = Math.Min(panelWidth, maxWidth);
childWidth = panelWidth - edgeWidth;
var result = new List <Segment>();
if (showBorder)
{
// Panel top
AddTopBorder(result, context, border, borderStyle, panelWidth);
}
// Split the child segments into lines.
var childSegments = ((IRenderable)child).Render(context, childWidth);
foreach (var(_, _, last, line) in Segment.SplitLines(childSegments, childWidth).Enumerate())
{
if (line.Count == 1 && line[0].IsWhiteSpace)
{
// NOTE: This check might impact other things.
// Hopefully not, but there is a chance.
continue;
}
if (showBorder)
{
result.Add(new Segment(border.GetPart(BoxBorderPart.Left), borderStyle));
}
var content = new List <Segment>();
content.AddRange(line);
// Do we need to pad the panel?
var length = line.Sum(segment => segment.CellCount());
if (length < childWidth)
{
var diff = childWidth - length;
content.Add(Segment.Padding(diff));
}
result.AddRange(content);
if (showBorder)
{
result.Add(new Segment(border.GetPart(BoxBorderPart.Right), borderStyle));
}
// Don't emit a line break if this is the last
// line, we're not showing the border, and we're
// not rendering this inline.
var emitLinebreak = !(last && !showBorder && !Inline);
if (!emitLinebreak)
{
continue;
}
result.Add(Segment.LineBreak);
}
// Panel bottom
if (showBorder)
{
result.Add(new Segment(border.GetPart(BoxBorderPart.BottomLeft), borderStyle));
result.Add(new Segment(border.GetPart(BoxBorderPart.Bottom).Repeat(panelWidth - EdgeWidth), borderStyle));
result.Add(new Segment(border.GetPart(BoxBorderPart.BottomRight), borderStyle));
}
// TODO: Need a better name for this?
// If we're rendering this as part of an inline parent renderable,
// such as columns, we should not emit the last line break.
if (!Inline)
{
result.Add(Segment.LineBreak);
}
return(result);
}