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)); }