forked from animatedread/Warrior_EA
6a687cda41
Replace hardcoded lr and momentum with new input variables for Adam and SGD+momentum. Add OpenCL kernel LSTM_UpdateWeightsMomentum alongside the existing Adam kernel. Update comments and revert beta1 to book default 0.9.
74 lines
4 KiB
MQL5
74 lines
4 KiB
MQL5
//+------------------------------------------------------------------+
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//| Warrior_EA |
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//| AnimateDread |
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//| |
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//+------------------------------------------------------------------+
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#include "..\Expert\ExpertSignalAIBase.mqh"
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// wizard description start
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//+------------------------------------------------------------------+
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//| Description of the class |
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//| Title=Signals of indicator 'LSTM AI' |
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//| Type=SignalAdvanced |
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//| Name=LSTM AI |
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//| ShortName=LSTM |
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//| Class=CSignalLSTM |
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//| Page=signal_lstm |
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//+------------------------------------------------------------------+
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// wizard description end
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//+------------------------------------------------------------------+
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//| Class CSignalLSTM. |
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//| Purpose: Class of generator of trade signals based on |
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//| the 'LSTM AI' indicator. |
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//| Is derived from the CExpertSignalAIBase class. |
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//| Only the network topology differs from the other AI signals: an |
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//| input layer feeds a single LSTM layer before the common tapering |
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//| hidden-layer stack (see AddCustomLayers). |
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//+------------------------------------------------------------------+
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class CSignalLSTM : public CExpertSignalAIBase
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{
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protected:
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virtual bool AddCustomLayers(CArrayObj *topology) override;
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//--- keep the tapering Dense stack TANH-bounded, matching the LSTM layer's own bounded
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//--- output, instead of the base class's default PRELU (see the base declaration's comment)
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virtual ENUM_ACTIVATION HiddenLayerActivation(void) override { return TANH; }
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public:
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CSignalLSTM(void);
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//--- method of creating the indicator and timeseries
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virtual bool InitIndicators(CIndicators *indicators) override;
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};
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//+------------------------------------------------------------------+
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//| Constructor |
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//+------------------------------------------------------------------+
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CSignalLSTM::CSignalLSTM(void)
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{
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SetIdentity("Recurrent", "LSTM");
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}
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//+------------------------------------------------------------------+
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//| Create indicators and bootstrap/load the network. |
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//+------------------------------------------------------------------+
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bool CSignalLSTM::InitIndicators(CIndicators *indicators)
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{
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return InitNeuralNetwork(indicators);
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}
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//+------------------------------------------------------------------+
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//| LSTM layer inserted between the input layer and the common |
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//| tapering hidden-layer stack. |
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//+------------------------------------------------------------------+
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bool CSignalLSTM::AddCustomLayers(CArrayObj *topology)
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{
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CLayerDescription *desc = new CLayerDescription();
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if(CheckPointer(desc) == POINTER_INVALID)
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return false;
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desc.count = m_hiddenLayersCount;
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desc.type = defNeuronLSTM;
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desc.activation = TANH;
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//--- CNeuronLSTMOCL now has an accelerated SGD+momentum kernel (LSTM_UpdateWeightsMomentum,
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//--- AI\Network.mqh/Network.cl/DirectML\WarriorCPU.cpp/WarriorDML.cpp) alongside the original
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//--- Adam one, so this layer honors the same TrainingOptimizer input as PAI/CONV - see
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//--- m_optimizationAlgo's declaration comment in ExpertSignalAIBase.mqh.
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desc.optimization = (ENUM_OPTIMIZATION)m_optimizationAlgo;
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desc.window = (int)m_historyBars * m_neuronsCount;
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desc.step = (int)m_historyBars / 2;
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return topology.Add(desc);
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}
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//+------------------------------------------------------------------+
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