private void UpdateParameters(Encoder encoder, Encoder ReversEncoder, AttentionDecoder decoder, WeightMatrix Whd, WeightMatrix bd, WeightMatrix s_Embedding, WeightMatrix t_Embedding)
{
var model = encoder.getParams();
model.AddRange(decoder.getParams());
model.AddRange(ReversEncoder.getParams());
model.Add(s_Embedding);
model.Add(t_Embedding);
model.Add(Whd);
model.Add(bd);
solver.UpdateWeights(model, learning_rate, regc, clipval);
}
private void CleanWeightsCash(Encoder encoder, Encoder ReversEncoder, AttentionDecoder decoder, WeightMatrix Whd, WeightMatrix bd, WeightMatrix s_Embedding, WeightMatrix t_Embedding)
{
var model = encoder.getParams();
model.AddRange(decoder.getParams());
model.AddRange(ReversEncoder.getParams());
model.Add(s_Embedding);
model.Add(t_Embedding);
model.Add(Whd);
model.Add(bd);
solver.CleanCash(model);
}
private float UpdateParameters(float learningRate, Encoder encoder, Encoder ReversEncoder, AttentionDecoder decoder,
IWeightMatrix Whd, IWeightMatrix bd, IWeightMatrix s_Embedding, IWeightMatrix t_Embedding, int batchSize)
{
var model = encoder.getParams();
model.AddRange(decoder.getParams());
model.AddRange(ReversEncoder.getParams());
model.Add(s_Embedding);
model.Add(t_Embedding);
model.Add(Whd);
model.Add(bd);
return(m_solver.UpdateWeights(model, batchSize, learningRate, m_regc, m_clipvalue, m_archType));
}
