//+------------------------------------------------------------------+
//|                                                       Warrior_EA |
//|                                                     AnimateDread |
//|                                                                  |
//+------------------------------------------------------------------+
#include "..\Expert\ExpertSignalAIBase.mqh"
// wizard description start
//+------------------------------------------------------------------+
//| Description of the class                                         |
//| Title=Signals of indicator 'LSTM AI'                             |
//| Type=SignalAdvanced                                              |
//| Name=LSTM AI                                                     |
//| ShortName=LSTM                                                   |
//| Class=CSignalLSTM                                                |
//| Page=signal_lstm                                                  |
//+------------------------------------------------------------------+
// wizard description end
//+------------------------------------------------------------------+
//| Class CSignalLSTM.                                               |
//| Purpose: Class of generator of trade signals based on            |
//|          the 'LSTM       AI' indicator.                          |
//| Is derived from the CExpertSignalAIBase class.                   |
//| Only the network topology differs from the other AI signals: an  |
//| input layer feeds a single LSTM layer before the common tapering  |
//| hidden-layer stack (see AddCustomLayers).                         |
//+------------------------------------------------------------------+
class CSignalLSTM : public CExpertSignalAIBase
  {
protected:
   virtual bool      AddCustomLayers(CArrayObj *topology) override;
   //--- keep the tapering Dense stack TANH-bounded, matching the LSTM layer's own bounded
   //--- output, instead of the base class's default PRELU (see the base declaration's comment)
   virtual ENUM_ACTIVATION HiddenLayerActivation(void) override { return TANH; }
public:
                     CSignalLSTM(void);
   //--- method of creating the indicator and timeseries
   virtual bool      InitIndicators(CIndicators *indicators) override;
  };
//+------------------------------------------------------------------+
//| Constructor                                                      |
//+------------------------------------------------------------------+
CSignalLSTM::CSignalLSTM(void)
  {
   SetIdentity("Recurrent", "LSTM");
  }
//+------------------------------------------------------------------+
//| Create indicators and bootstrap/load the network.                |
//+------------------------------------------------------------------+
bool CSignalLSTM::InitIndicators(CIndicators *indicators)
  {
   return InitNeuralNetwork(indicators);
  }
//+------------------------------------------------------------------+
//| LSTM layer inserted between the input layer and the common       |
//| tapering hidden-layer stack.                                      |
//+------------------------------------------------------------------+
bool CSignalLSTM::AddCustomLayers(CArrayObj *topology)
  {
   CLayerDescription *desc = new CLayerDescription();
   if(CheckPointer(desc) == POINTER_INVALID)
      return false;
   desc.count = m_hiddenLayersCount;
   desc.type = defNeuronLSTM;
   desc.activation = TANH;
   //--- CNeuronLSTMOCL now has an accelerated SGD+momentum kernel (LSTM_UpdateWeightsMomentum,
   //--- AI\Network.mqh/Network.cl/DirectML\WarriorCPU.cpp/WarriorDML.cpp) alongside the original
   //--- Adam one, so this layer honors the same TrainingOptimizer input as PAI/CONV - see
   //--- m_optimizationAlgo's declaration comment in ExpertSignalAIBase.mqh.
   desc.optimization = (ENUM_OPTIMIZATION)m_optimizationAlgo;
   desc.window = (int)m_historyBars * m_neuronsCount;
   desc.step = (int)m_historyBars / 2;
   return topology.Add(desc);
  }
//+------------------------------------------------------------------+