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NN_in_Trading/Experts/SAC_DICE/Net_SAC_DICE.mqh

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2026-03-12 15:02:23 +02:00
<EFBFBD><EFBFBD>//+------------------------------------------------------------------+
//| Net_SAC_DICE.mqh |
//| Copyright DNG<EFBFBD> |
//| https://www.mql5.com/ru/users/dng |
//+------------------------------------------------------------------+
#property copyright "Copyright DNG<00>"
#property link "https://www.mql5.com/ru/users/dng"
#property version "1.00"
//+------------------------------------------------------------------+
//| Includes |
//+------------------------------------------------------------------+
#include "..\RL\FQF.mqh"
//---
#define defSACDICE 0x7795 ///<Neuron Net
#define LogProbMultiplier 1.0e-5f
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
class CNet_SAC_DICE : protected CNet
{
protected:
CNet cActorExploer;
CNet cCritic1;
CNet cCritic2;
CNet cTargetCritic1;
CNet cTargetCritic2;
CNet cZeta;
CNet cNu;
CNet cTargetNu;
float fLambda;
float fLambda_m;
float fLambda_v;
int iLatentLayer;
//---
float fLoss1;
float fLoss2;
float fZeta;
//---
vector<float> GetLogProbability(CBufferFloat *Actions);
public:
//---
CNet_SAC_DICE(void);
~CNet_SAC_DICE(void) {}
//---
bool Create(CArrayObj *actor, CArrayObj *critic, CArrayObj *zeta, CArrayObj *nu, int latent_layer = -1);
//---
virtual bool Study(CArrayFloat *State, CArrayFloat *SecondInput, CBufferFloat *Actions, vector<float> &ActionsLogProbab, CBufferFloat *NextState, CBufferFloat *NextSecondInput, float reward, float discount, float tau);
virtual void GetLoss(float &loss1, float &loss2) { loss1 = fLoss1; loss2 = fLoss2; }
//---
virtual bool Save(string file_name, bool common = true);
bool Load(string file_name, bool common = true);
};
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
CNet_SAC_DICE::CNet_SAC_DICE(void) : fLambda(1.0e-5f),
fLambda_m(0),
fLambda_v(0),
fLoss1(0),
fLoss2(0),
fZeta(0)
{
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool CNet_SAC_DICE::Create(CArrayObj *actor, CArrayObj *critic, CArrayObj *zeta, CArrayObj *nu, int latent_layer = -1)
{
ResetLastError();
//---
if(!cActorExploer.Create(actor) || !CNet::Create(actor))
{
PrintFormat("Error of create Actor: %d", GetLastError());
return false;
}
//---
if(!opencl)
{
Print("Don't opened OpenCL context");
return false;
}
//---
if(!cCritic1.Create(critic) || !cCritic2.Create(critic))
{
PrintFormat("Error of create Critic: %d", GetLastError());
return false;
}
//---
if(!cZeta.Create(zeta) || !cNu.Create(nu))
{
PrintFormat("Error of create function nets: %d", GetLastError());
return false;
}
//---
if(!cTargetCritic1.Create(critic) || !cTargetCritic2.Create(critic) ||
!cTargetNu.Create(nu))
{
PrintFormat("Error of create target models: %d", GetLastError());
return false;
}
//---
cActorExploer.SetOpenCL(opencl);
cCritic1.SetOpenCL(opencl);
cCritic2.SetOpenCL(opencl);
cZeta.SetOpenCL(opencl);
cNu.SetOpenCL(opencl);
cTargetCritic1.SetOpenCL(opencl);
cTargetCritic2.SetOpenCL(opencl);
cTargetNu.SetOpenCL(opencl);
//---
if(!cTargetCritic1.WeightsUpdate(GetPointer(cCritic1), 1.0) ||
!cTargetCritic2.WeightsUpdate(GetPointer(cCritic2), 1.0) ||
!cTargetNu.WeightsUpdate(GetPointer(cNu), 1.0))
{
PrintFormat("Error of update target models: %d", GetLastError());
return false;
}
//---
fLambda = 1.0e-5f;
fLambda_m = 0;
fLambda_v = 0;
fZeta = 0;
iLatentLayer = latent_layer;
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool CNet_SAC_DICE::Study(CArrayFloat *State,
CArrayFloat *SecondInput,
CBufferFloat *Actions,
vector<float> &ActionsLogProbab,
CBufferFloat *NextState,
CBufferFloat *NextSecondInput,
float reward,
float discount,
float tau)
{
//---
if(!Actions || Actions.Total()!=ActionsLogProbab.Size())
return false;
//---
if(!CNet::feedForward(NextState, 1, false, NextSecondInput))
return false;
if(!cTargetCritic1.feedForward(GetPointer(this), iLatentLayer, GetPointer(this), layers.Total() - 1) ||
!cTargetCritic2.feedForward(GetPointer(this), iLatentLayer, GetPointer(this), layers.Total() - 1))
return false;
//---
if(!cTargetNu.feedForward(GetPointer(this), iLatentLayer, GetPointer(this), layers.Total() - 1))
return false;
if(!CNet::feedForward(State, 1, false, SecondInput))
return false;
CBufferFloat *output = ((CNeuronBaseOCL*)((CLayer*)layers.At(layers.Total() - 1)).At(0)).getOutput();
output.AssignArray(Actions);
output.BufferWrite();
if(!cNu.feedForward(GetPointer(this), iLatentLayer, GetPointer(this)))
return false;
if(!cZeta.feedForward(GetPointer(this), iLatentLayer, GetPointer(this)))
return false;
//---
vector<float> nu, next_nu, zeta, ones;
cNu.getResults(nu);
cTargetNu.getResults(next_nu);
cZeta.getResults(zeta);
ones = vector<float>::Ones(zeta.Size());
vector<float> log_prob = GetLogProbability(output);
float policy_ratio = MathExp((log_prob - ActionsLogProbab).Sum());
vector<float> bellman_residuals = next_nu * discount * policy_ratio - nu + policy_ratio * reward;
vector<float> zeta_loss = zeta * (MathAbs(bellman_residuals) - fLambda) * (-1) + MathPow(zeta, 2.0f) / 2;
vector<float> nu_loss = zeta * MathAbs(bellman_residuals) + MathPow(nu, 2.0f) / 2.0f;
float lambda_los = fLambda * (ones - zeta).Sum();
//--- update lambda
float grad_lambda = (ones - zeta).Sum() * (-lambda_los);
fLambda_m = b1 * fLambda_m + (1 - b1) * grad_lambda;
fLambda_v = b2 * fLambda_v + (1 - b2) * MathPow(grad_lambda, 2);
fLambda += lr * fLambda_m / (fLambda_v != 0.0f ? MathSqrt(fLambda_v) : 1.0f);
//---
CBufferFloat temp;
temp.BufferInit(MathMax(Actions.Total(), SecondInput.Total()), 0);
temp.BufferCreate(opencl);
//--- update nu
int last_layer = cNu.layers.Total() - 1;
CLayer *layer = cNu.layers.At(last_layer);
if(!layer)
return false;
CNeuronBaseOCL *neuron = layer.At(0);
if(!neuron)
return false;
CBufferFloat *buffer = neuron.getGradient();
if(!buffer)
return false;
vector<float> nu_grad = nu_loss * (zeta * bellman_residuals / MathAbs(bellman_residuals) + nu);
if(!buffer.AssignArray(nu_grad) || !buffer.BufferWrite())
return false;
if(!cNu.backPropGradient(output, GetPointer(temp)))
return false;
//--- update zeta
last_layer = cZeta.layers.Total() - 1;
layer = cZeta.layers.At(last_layer);
if(!layer)
return false;
neuron = layer.At(0);
if(!neuron)
return false;
buffer = neuron.getGradient();
if(!buffer)
return false;
vector<float> zeta_grad = zeta_loss * (zeta - MathAbs(bellman_residuals) + fLambda) * (-1);
if(!buffer.AssignArray(zeta_grad) || !buffer.BufferWrite())
return false;
if(!cZeta.backPropGradient(output, GetPointer(temp)))
return false;
//--- feed forward critics
if(!cCritic1.feedForward(GetPointer(this), iLatentLayer, output) ||
!cCritic2.feedForward(GetPointer(this), iLatentLayer, output))
return false;
//--- target
vector<float> result;
if(fZeta == 0)
fZeta = MathAbs(zeta[0]);
else
fZeta = 0.9f * fZeta + 0.1f * MathAbs(zeta[0]);
zeta[0] = MathPow(MathAbs(zeta[0]), 1.0f / 3.0f) / (10.0f * MathPow(fZeta, 1.0f / 3.0f));
cTargetCritic1.getResults(result);
float target = result[0];
cTargetCritic2.getResults(result);
target = reward + discount * (MathMin(result[0], target) - LogProbMultiplier * log_prob.Sum());
//--- update critic1
cCritic1.getResults(result);
float loss = zeta[0] * MathPow(result[0] - target, 2.0f);
if(fLoss1 == 0)
fLoss1 = MathSqrt(loss);
else
fLoss1 = MathSqrt(0.999f * MathPow(fLoss1, 2.0f) + 0.001f * loss);
float grad = loss * 2 * zeta[0] * (target - result[0]);
last_layer = cCritic1.layers.Total() - 1;
layer = cCritic1.layers.At(last_layer);
if(!layer)
return false;
neuron = layer.At(0);
if(!neuron)
return false;
buffer = neuron.getGradient();
if(!buffer)
return false;
if(!buffer.Update(0, grad) || !buffer.BufferWrite())
return false;
if(!cCritic1.backPropGradient(output, GetPointer(temp)) || !backPropGradient(SecondInput, GetPointer(temp), iLatentLayer))
return false;
//--- update critic2
cCritic2.getResults(result);
loss = zeta[0] * MathPow(result[0] - target, 2.0f);
if(fLoss2 == 0)
fLoss2 = MathSqrt(loss);
else
fLoss2 = MathSqrt(0.999f * MathPow(fLoss1, 2.0f) + 0.001f * loss);
grad = loss * 2 * zeta[0] * (target - result[0]);
last_layer = cCritic2.layers.Total() - 1;
layer = cCritic2.layers.At(last_layer);
if(!layer)
return false;
neuron = layer.At(0);
if(!neuron)
return false;
buffer = neuron.getGradient();
if(!buffer)
return false;
if(!buffer.Update(0, grad) || !buffer.BufferWrite())
return false;
if(!cCritic2.backPropGradient(output, GetPointer(temp)) || !backPropGradient(SecondInput, GetPointer(temp), iLatentLayer))
return false;
//--- update policy
cCritic1.getResults(result);
float mean = result[0];
float var = result[0];
cCritic2.getResults(result);
mean += result[0];
var -= result[0];
mean /= 2.0f;
var = MathAbs(var) / 2.0f;
target = zeta[0] * (mean - 2.5f * var + discount * log_prob.Sum() * LogProbMultiplier) + result[0];
CBufferFloat bTarget;
bTarget.Add(target);
cCritic2.TrainMode(false);
if(!cCritic2.backProp(GetPointer(bTarget), GetPointer(this)) ||
!backPropGradient(SecondInput, GetPointer(temp)))
{
cCritic2.TrainMode(true);
return false;
}
//--- update exploration policy
if(!cActorExploer.feedForward(State, 1, false, SecondInput))
{
cCritic2.TrainMode(true);
return false;
}
output = ((CNeuronBaseOCL*)((CLayer*)cActorExploer.layers.At(layers.Total() - 1)).At(0)).getOutput();
output.AssignArray(Actions);
output.BufferWrite();
cActorExploer.GetLogProbs(log_prob);
target = zeta[0] * (mean + 2.0f * var + discount * log_prob.Sum() * LogProbMultiplier) + result[0];
bTarget.Update(0, target);
if(!cCritic2.backProp(GetPointer(bTarget), GetPointer(cActorExploer)) ||
!cActorExploer.backPropGradient(SecondInput, GetPointer(temp)))
{
cCritic2.TrainMode(true);
return false;
}
cCritic2.TrainMode(true);
//---
if(!cTargetCritic1.WeightsUpdate(GetPointer(cCritic1), tau) ||
!cTargetCritic2.WeightsUpdate(GetPointer(cCritic2), tau) ||
!cTargetNu.WeightsUpdate(GetPointer(cNu), tau))
{
PrintFormat("Error of update target models: %d", GetLastError());
return false;
}
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
vector<float> CNet_SAC_DICE::GetLogProbability(CBufferFloat *Actions)
{
CBufferFloat temp;
vector<float> result = vector<float>::Zeros(0);
temp.AssignArray(Actions);
if(!CalcLogProbs(GetPointer(temp)))
return result;
temp.GetData(result);
//---
return result;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool CNet_SAC_DICE::Save(string file_name, bool common = true)
{
if(file_name == NULL)
return false;
//---
int handle = FileOpen(file_name + ".set", (common ? FILE_COMMON : 0) | FILE_BIN | FILE_WRITE);
if(handle == INVALID_HANDLE)
return false;
if(FileWriteFloat(handle, fLambda) < sizeof(fLambda) ||
FileWriteFloat(handle, fLambda_m) < sizeof(fLambda_m) ||
FileWriteFloat(handle, fLambda_v) < sizeof(fLambda_v) ||
FileWriteInteger(handle, iLatentLayer) < sizeof(iLatentLayer))
return false;
FileFlush(handle);
FileClose(handle);
//---
if(!CNet::Save(file_name + "Act.nnw", 0, 0, 0, TimeCurrent(), common))
return false;
//---
if(!cActorExploer.Save(file_name + "ActExp.nnw", 0, 0, 0, TimeCurrent(), common))
return false;
//---
if(!cTargetCritic1.Save(file_name + "Crt1.nnw", fLoss1, 0, 0, TimeCurrent(), common))
return false;
//---
if(!cTargetCritic2.Save(file_name + "Crt2.nnw", fLoss2, 0, 0, TimeCurrent(), common))
return false;
//---
if(!cZeta.Save(file_name + "Zeta.nnw", 0, 0, 0, TimeCurrent(), common))
return false;
//---
if(!cTargetNu.Save(file_name + "Nu.nnw", 0, 0, 0, TimeCurrent(), common))
return false;
//---
return true;
}
//+------------------------------------------------------------------+
//| |
//+------------------------------------------------------------------+
bool CNet_SAC_DICE::Load(string file_name, bool common = true)
{
if(file_name == NULL)
return false;
//---
int handle = FileOpen(file_name + ".set", (common ? FILE_COMMON : 0) | FILE_BIN | FILE_READ);
if(handle == INVALID_HANDLE)
return false;
if(FileIsEnding(handle))
return false;
fLambda = FileReadFloat(handle);
if(FileIsEnding(handle))
return false;
fLambda_m = FileReadFloat(handle);
if(FileIsEnding(handle))
return false;
fLambda_v = FileReadFloat(handle);
if(FileIsEnding(handle))
return false;
iLatentLayer = FileReadInteger(handle);;
FileClose(handle);
//---
float temp;
datetime dt;
if(!CNet::Load(file_name + "Act.nnw", temp, temp, temp, dt, common))
return false;
//---
if(!cActorExploer.Load(file_name + "ActExp.nnw", temp, temp, temp, dt, common))
return false;
//---
if(!cCritic1.Load(file_name + "Crt1.nnw", fLoss1, temp, temp, dt, common) ||
!cTargetCritic1.Load(file_name + "Crt1.nnw", temp, temp, temp, dt, common))
return false;
//---
if(!cCritic2.Load(file_name + "Crt2.nnw", fLoss2, temp, temp, dt, common) ||
!cTargetCritic2.Load(file_name + "Crt2.nnw", temp, temp, temp, dt, common))
return false;
//---
if(!cZeta.Load(file_name + "Zeta.nnw", temp, temp, temp, dt, common))
return false;
//---
if(!cNu.Load(file_name + "Nu.nnw", temp, temp, temp, dt, common) ||
!cTargetNu.Load(file_name + "Nu.nnw", temp, temp, temp, dt, common))
return false;
//---
cActorExploer.SetOpenCL(opencl);
cCritic1.SetOpenCL(opencl);
cCritic2.SetOpenCL(opencl);
cZeta.SetOpenCL(opencl);
cNu.SetOpenCL(opencl);
cTargetCritic1.SetOpenCL(opencl);
cTargetCritic2.SetOpenCL(opencl);
cTargetNu.SetOpenCL(opencl);
//---
return true;
}
//+------------------------------------------------------------------+
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