/// <summary>
/// Records the network activity
/// </summary>
/// <param name="context">Graph context</param>
/// <param name="output">The output signal</param>
/// <param name="backpropagation">Backpropagation creator (optional)</param>
protected void _AddHistory(IContext context, IMatrix output,
Func <IBackpropagation> backpropagation)
{
context.AddForward(
new TrainingAction(this, new MatrixGraphData(output),
new[] { _primarySource, _secondarySource }), backpropagation);
}
public override void ExecuteForward(IContext context)
{
var curr = context.BatchSequence;
var batch = curr.MiniBatch;
var reversed = batch.GetSequenceAtIndex(batch.SequenceCount - curr.SequenceIndex - 1).Input;
context.AddForward(new TrainingAction(this, reversed[_inputIndex], context.Source), null);
}
/// <summary>
/// Records the network activity
/// </summary>
/// <param name="context">The graph context</param>
/// <param name="data">The list of incoming signals</param>
/// <param name="output">Output signal</param>
/// <param name="backpropagation">Backpropagation creator (optional)</param>
protected void _AddHistory(IContext context, IReadOnlyList <IncomingChannel> data,
IMatrix output, Func <IBackpropagation> backpropagation)
{
var sources = data.Select(d => d.Source).ToList();
context.AddForward(new TrainingAction(this, new MatrixGraphData(output), sources),
backpropagation);
}
public void AddForward(IExecutionHistory action, Func <IBackpropagation> callback)
{
// TODO: wrap the backpropagation?
_context.AddForward(new TrainingAction(_wrapper, action.Data, action.Source), callback);
}
/// <summary>
/// Records the node execution and queues the output nodes for execution
/// </summary>
/// <param name="context"></param>
/// <param name="data"></param>
/// <param name="backProp"></param>
protected void _AddNextGraphAction(IContext context, IGraphData data, Func <IBackpropagation> backProp)
{
context.AddForward(new TrainingAction(this, data, context.Source), backProp);
}
