private float DecodeOutput(string[] OutputSentence, IComputeGraph g, float cost, SparseWeightMatrix sparseInput, List <WeightMatrix> encoded, AttentionDecoder decoder, WeightMatrix Whd, WeightMatrix bd, WeightMatrix Embedding)
{
int ix_input = (int)SENTTAGS.START;
for (int i = 0; i < OutputSentence.Length + 1; i++)
{
int ix_target = (int)SENTTAGS.UNK;
if (i == OutputSentence.Length)
{
ix_target = (int)SENTTAGS.END;
}
else
{
if (t_wordToIndex.ContainsKey(OutputSentence[i]))
{
ix_target = t_wordToIndex[OutputSentence[i]];
}
}
var x = g.PeekRow(Embedding, ix_input);
var eOutput = decoder.Decode(sparseInput, x, encoded, g);
if (UseDropout)
{
eOutput = g.Dropout(eOutput, 0.2f);
}
var o = g.muladd(eOutput, Whd, bd);
if (UseDropout)
{
o = g.Dropout(o, 0.2f);
}
var probs = g.SoftmaxWithCrossEntropy(o);
cost += (float)-Math.Log(probs.Weight[ix_target]);
o.Gradient = probs.Weight;
o.Gradient[ix_target] -= 1;
ix_input = ix_target;
}
return(cost);
}