private void Init(ConnectedLayer connectedLayer)
{
ConnectedLayerIndex = connectedLayer.Index;
InitInputValueAccessItems(connectedLayer);
OutputBuffer = connectedLayer.OutputBuffer;
BiasValueIndex = connectedLayer.BiasValueIndex;
InnerItarationOutputValueStack = connectedLayer.InnerItarationOutputValueStack;
IsOutput = connectedLayer.IsOutput;
if ((connectedLayer.StructuralElementFlags & NNStructuralElement.RTLRInformation) != 0)
{
Method = ForwardComputationMethod.RTLR;
UpperNonInputLayerInfos = connectedLayer.UpperNonInputLayerInfos;
PBiasBuffers = connectedLayer.PBiasBuffers;
PWeightBuffers = connectedLayer.PWeightBuffers;
PrevPBiasBuffers = connectedLayer.PrevPBiasBuffers;
PrevPWeightBuffers = connectedLayer.PrevPWeightBuffers;
NetDerivBuffer = connectedLayer.NetDerivBuffer;
GradientBuffers = connectedLayer.GradientBuffers;
GradientSumBuffers = connectedLayer.GradientSumBuffers;
BiasGradientValueIndex = connectedLayer.BiasGradientValueIndex;
BiasGradientSumValueIndex = connectedLayer.BiasGradientSumValueIndex;
}
else if (connectedLayer.InnerItarationOutputValueStack != null)
{
Debug.Assert(connectedLayer.InnerItarationInputValueStacks != null);
Method = ForwardComputationMethod.BPTT;
}
else
{
Method = ForwardComputationMethod.FeedForward;
}
}
protected LayerBackwardCompute(LayerForwardCompute forwardCompute, ConnectedLayer connectedLayer)
{
Contract.Requires(forwardCompute != null);
Contract.Requires(connectedLayer != null);
Contract.Requires((connectedLayer.StructuralElementFlags & NNStructuralElement.BackwardImplementation) != 0 &&
(connectedLayer.StructuralElementFlags & NNStructuralElement.GradientInformation) != 0);
Init(forwardCompute, connectedLayer);
}
private void Init(LayerForwardCompute forwardCompute, ConnectedLayer connectedLayer)
{
ForwardCompute = forwardCompute;
InitLowerErrorValueAccessItems(connectedLayer);
ErrorBuffer = connectedLayer.ErrorBuffer;
GradientBuffers = connectedLayer.GradientBuffers;
GradientSumBuffers = connectedLayer.GradientSumBuffers;
BiasGradientValueIndex = connectedLayer.BiasGradientValueIndex;
BiasGradientSumValueIndex = connectedLayer.BiasGradientSumValueIndex;
OutputErrorBuffer = connectedLayer.OutputErrorBuffer;
}
internal void InitializeAlgo(BufferAllocator allocator, LearningRule rule, ConnectedLayer[] connectedLayers, ManagedNNInitParameters initPars)
{
Contract.Requires(rule != null);
Contract.Requires(connectedLayers != null);
Contract.Requires(connectedLayers.Length > 0);
Contract.Requires(initPars != null);
Rule = rule;
ConnectedLayers = connectedLayers;
RunParallel = initPars.RunParallel;
Ininitalize(allocator);
}
public ActivationLayerBackwardCompute(ActivationLayerForwardCompute forwardCompute, ConnectedLayer connectedLayer)
: base(forwardCompute, connectedLayer)
{
Contract.Requires(forwardCompute != null);
Contract.Requires(connectedLayer != null);
Contract.Requires((connectedLayer.StructuralElementFlags & NNStructuralElement.BackwardImplementation) != 0 &&
(connectedLayer.StructuralElementFlags & NNStructuralElement.GradientInformation) != 0);
Function = forwardCompute.Function;
forwardCompute.FeedForwardOps.Initialize(this);
forwardCompute.BPTTOps.Initialize(this);
}
public ActivationLayerForwardCompute(NeuralNetworkFactory factory, ConnectedLayer connectedLayer)
: base(factory, connectedLayer)
{
Contract.Requires(connectedLayer != null);
Contract.Requires(connectedLayer.Layer is ActivationLayer);
FeedForwardOps = factory.CreateFeedForwardOps();
FeedForwardOps.Initialize(this);
BPTTOps = factory.CreateBPTTOps();
BPTTOps.Initialize(this);
RTLROps = factory.CreateRTLROps();
RTLROps.Initialize(this);
Function = ((ActivationLayer)connectedLayer.Layer).Function;
}
protected LayerBackwardComputeBase(LayerForwardComputeBase forwardCompute, ConnectedLayer connectedLayer)
{
Contract.Requires(forwardCompute != null);
Contract.Requires(connectedLayer != null);
Contract.Requires((connectedLayer.StructuralElementFlags & NNStructuralElement.BackwardImplementation) != 0 &&
(connectedLayer.StructuralElementFlags & NNStructuralElement.GradientInformation) != 0);
ForwardCompute = forwardCompute;
InitLowerErrorValueAccessItems(connectedLayer);
ErrorBuffer = connectedLayer.ErrorBuffer;
GradientBuffers = connectedLayer.GradientBuffers;
GradientSumBuffers = connectedLayer.GradientSumBuffers;
BiasGradientValueIndex = connectedLayer.BiasGradientValueIndex;
BiasGradientSumValueIndex = connectedLayer.BiasGradientSumValueIndex;
OutputErrorBuffer = connectedLayer.OutputErrorBuffer;
}
private void InitLowerErrorValueAccessItems(ConnectedLayer connectedLayer)
{
if (connectedLayer.WeightedOutputErrorBuffers == null) return;
var items = new LinkedList<ErrorValueAccess>();
for (int outputErrorBufferIndex = 0; outputErrorBufferIndex < connectedLayer.WeightedOutputErrorBuffers.Length; outputErrorBufferIndex++)
{
var weightedOutputErrorBuffer = connectedLayer.WeightedOutputErrorBuffers[outputErrorBufferIndex];
int wibValueBufferSize = weightedOutputErrorBuffer.ValueBuffer.Size;
items.AddLast(
new ErrorValueAccess(
weightedOutputErrorBuffer.ValueBuffer.Size,
weightedOutputErrorBuffer.ValueBuffer.MinValue,
weightedOutputErrorBuffer.WeightBuffer.MinValue));
}
LowerErrorValueAccessItems = items.ToArray();
}
private void InitInputValueAccessItems(ConnectedLayer connectedLayer)
{
int count = connectedLayer.WeightedInputBuffers.Length;
var items = new InputValueAccess[count];
for (int inputBufferIndex = 0; inputBufferIndex < count; inputBufferIndex++)
{
var weightedInputBuffer = connectedLayer.WeightedInputBuffers[inputBufferIndex];
int wibValueBufferSize = weightedInputBuffer.ValueBuffer.Size;
items[inputBufferIndex] =
new InputValueAccess(
weightedInputBuffer.ValueBuffer.Size,
weightedInputBuffer.ValueBuffer.MinValue,
weightedInputBuffer.WeightBuffer.MinValue,
connectedLayer.InnerItarationInputValueStacks != null ? connectedLayer.InnerItarationInputValueStacks[inputBufferIndex] : null);
}
InputValueAccessItems = items;
}
protected internal virtual LayerBackwardCompute CreateBackwardCompute(ConnectedLayer connectedLayer)
{
Contract.Requires(connectedLayer != null);
throw new InvalidOperationException("Backward computation is not supported.");
}
protected LayerForwardCompute(NeuralNetworkFactory factory, ConnectedLayer connectedLayer)
{
Contract.Requires(connectedLayer != null);
Init(connectedLayer);
}
protected internal override LayerBackwardCompute CreateBackwardCompute(ConnectedLayer connectedLayer)
{
return new ActivationLayerBackwardCompute(this, connectedLayer);
}
private void InitInputValueAccessItems(ConnectedLayer connectedLayer)
{
var items = new LinkedList<InputValueAccess>();
for (int inputBufferIndex = 0; inputBufferIndex < connectedLayer.WeightedInputBuffers.Length; inputBufferIndex++)
{
var weightedInputBuffer = connectedLayer.WeightedInputBuffers[inputBufferIndex];
int wibValueBufferSize = weightedInputBuffer.ValueBuffer.Size;
items.AddLast(
new InputValueAccess(
weightedInputBuffer.ValueBuffer.Size,
weightedInputBuffer.ValueBuffer.MinValue,
weightedInputBuffer.WeightBuffer.MinValue,
connectedLayer.InnerItarationInputValueStacks != null ? connectedLayer.InnerItarationInputValueStacks[inputBufferIndex] : null));
}
InputValueAccessItems = items.ToArray();
}
internal void InitializeAlgo(BufferAllocator allocator, LearningRule learningRule, ConnectedLayer[] connectedLayer)
{
throw new NotImplementedException();
}
