1205 lines
72 KiB
MQL5
1205 lines
72 KiB
MQL5
//+------------------------------------------------------------------+
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//| Trajectory.mqh |
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//| Copyright DNG® |
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//| https://www.mql5.com/ru/users/dng |
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//+------------------------------------------------------------------+
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#property copyright "Copyright DNG®"
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#property link "https://www.mql5.com/ru/users/dng"
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#property version "1.00"
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//+------------------------------------------------------------------+
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//| Rewards structure |
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//| 0 - Delta Balance |
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//| 1 - Delta Equity ( "-" Drawdown / "+" Profit) |
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//| 2 - Penalty for no open positions |
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//+------------------------------------------------------------------+
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#include "..\NeuroNet_DNG\NeuroNet.mqh"
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//---
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#define HistoryBars 120 //Depth of history
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#define Segments 8 //Segments number (must be HistoryBars % Segments == 0)
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#define BarDescr 9 //Elements for 1 bar description
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#define AccountDescr 12 //Account description
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#define NActions 6 //Number of possible Actions
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#define NRewards 3 //Number of rewards
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#define NForecast 30 //Number of forecast
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#define BatchSize 1e+4
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#define NSkills 24
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#define EmbeddingSize 32
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#define Buffer_Size 31000
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#define DiscFactor 0.2f
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#define FileName "TimeFound"
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#define SignalFile(agent) StringFormat("Signals\\Signal%d.csv",agent)
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#define LatentCount 256
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#define LatentLayer 5
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#define MaxSL 1000
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#define MaxTP 1000
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#define MaxReplayBuffer 500
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#define StartTargetIteration 200000
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#define STE_Multiplier 1.0f/2
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#define ActorUpdate 10
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#define TragetUpdate 60*24
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#define tau 0.9f
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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struct SState
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{
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float state[HistoryBars * BarDescr];
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float account[AccountDescr - 4];
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float action[NActions];
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float rewards[NRewards];
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//---
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SState(void);
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//---
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bool Save(int file_handle);
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bool Load(int file_handle);
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//--- overloading
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void operator=(const SState &obj)
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{
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ArrayCopy(state, obj.state);
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ArrayCopy(account, obj.account);
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ArrayCopy(action, obj.action);
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ArrayCopy(rewards, obj.rewards);
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}
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};
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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SState::SState(void)
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{
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ArrayInitialize(state, 0);
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ArrayInitialize(account, 0);
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ArrayInitialize(action, 0);
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ArrayInitialize(rewards, 0);
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool SState::Save(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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//---
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int total = ArraySize(state);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, state[i]) < sizeof(float))
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return false;
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//---
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total = ArraySize(account);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, account[i]) < sizeof(float))
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return false;
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//---
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total = ArraySize(action);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, action[i]) < sizeof(float))
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return false;
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total = ArraySize(rewards);
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if(FileWriteInteger(file_handle, total) < sizeof(int))
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return false;
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for(int i = 0; i < total; i++)
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if(FileWriteFloat(file_handle, rewards[i]) < sizeof(float))
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return false;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool SState::Load(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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if(FileIsEnding(file_handle))
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return false;
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//---
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int total = FileReadInteger(file_handle);
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if(total != ArraySize(state))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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state[i] = FileReadFloat(file_handle);
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}
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//---
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total = FileReadInteger(file_handle);
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if(total != ArraySize(account))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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account[i] = FileReadFloat(file_handle);
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}
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//---
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total = FileReadInteger(file_handle);
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if(total != ArraySize(action))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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action[i] = MathMin(MathMax(FileReadFloat(file_handle), 0), 1);
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}
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//---
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total = FileReadInteger(file_handle);
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if(total != ArraySize(rewards))
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return false;
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//---
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for(int i = 0; i < total; i++)
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{
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if(FileIsEnding(file_handle))
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return false;
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rewards[i] = FileReadFloat(file_handle);
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}
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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struct STrajectory
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{
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SState States[Buffer_Size];
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int Total;
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float DiscountFactor;
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bool CumCounted;
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//---
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STrajectory(void);
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//---
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bool Add(SState &state);
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void CumRevards(void);
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//---
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bool Save(int file_handle);
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bool Load(int file_handle);
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};
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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STrajectory::STrajectory(void) : Total(0),
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DiscountFactor(DiscFactor),
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CumCounted(false)
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{
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool STrajectory::Save(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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if(Total <= 0)
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return true;
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//---
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if(!CumCounted)
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CumRevards();
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Total = MathMin((int)States.Size(), Total);
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if(FileWriteInteger(file_handle, Total) < sizeof(int))
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return false;
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if(FileWriteFloat(file_handle, DiscountFactor) < sizeof(float))
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return false;
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for(int i = 0; i < Total; i++)
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if(!States[i].Save(file_handle))
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return false;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool STrajectory::Load(int file_handle)
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{
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if(file_handle == INVALID_HANDLE)
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return false;
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//---
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Total = FileReadInteger(file_handle);
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if(FileIsEnding(file_handle) || Total >= ArraySize(States))
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return false;
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DiscountFactor = FileReadFloat(file_handle);
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CumCounted = true;
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//---
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for(int i = 0; i < Total; i++)
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if(!States[i].Load(file_handle))
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return false;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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void STrajectory::CumRevards(void)
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{
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if(CumCounted)
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return;
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//---
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for(int i = Total - 2; i >= 0; i--)
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for(int r = 0; r < NRewards; r++)
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States[i].rewards[r] += States[i + 1].rewards[r] * DiscountFactor;
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CumCounted = true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool STrajectory::Add(SState &state)
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{
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if(Total + 1 >= ArraySize(States))
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return false;
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States[Total] = state;
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Total++;
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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#ifndef StudyOnline
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bool SaveTotalBase(void)
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{
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int total = ArraySize(Buffer);
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if(total < 0)
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return true;
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int handle = FileOpen(FileName + ".bd", FILE_WRITE | FILE_BIN | FILE_COMMON);
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if(handle < 0)
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return false;
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int start = MathMax(total - MaxReplayBuffer, 0);
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if(FileWriteInteger(handle, total - start) < INT_VALUE)
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{
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FileClose(handle);
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return false;
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}
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for(int i = start; i < total; i++)
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if(!Buffer[i].Save(handle))
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{
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FileClose(handle);
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return false;
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}
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FileFlush(handle);
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FileClose(handle);
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//---
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool LoadTotalBase(void)
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{
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int handle = FileOpen(FileName + ".bd", FILE_READ | FILE_BIN | FILE_COMMON | FILE_SHARE_READ);
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if(handle < 0)
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return false;
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int total = FileReadInteger(handle);
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if(total <= 0)
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{
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FileClose(handle);
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return false;
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}
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if(ArrayResize(Buffer, total) < total)
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{
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FileClose(handle);
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return false;
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}
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int load_false = 0;
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for(int i = 0; i < total; i++)
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if(!Buffer[i].Load(handle))
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{
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total = i;
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break;
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}
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FileClose(handle);
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//---
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if(ArrayResize(Buffer, total) < total)
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{
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FileClose(handle);
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return false;
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}
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//---
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return total > 0;
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}
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#endif
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CreateDescriptions(CArrayObj *&encoder,
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CArrayObj *&actor,
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CArrayObj *&director,
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CArrayObj *&critic
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)
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{
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//---
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CLayerDescription *descr;
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//---
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if(!encoder)
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{
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encoder = new CArrayObj();
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if(!encoder)
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return false;
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}
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if(!actor)
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{
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actor = new CArrayObj();
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if(!actor)
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return false;
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}
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if(!director)
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{
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director = new CArrayObj();
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if(!director)
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return false;
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}
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if(!critic)
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{
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critic = new CArrayObj();
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if(!critic)
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return false;
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}
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//--- Encoder
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encoder.Clear();
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//--- Input layer
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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uint prev_count = descr.count = (HistoryBars * BarDescr);
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descr.activation = None;
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descr.optimization = ADAM;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 1
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBatchNormWithNoise;
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descr.count = prev_count;
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descr.batch = BatchSize;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 2
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConcatDiff;
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prev_count = descr.count = HistoryBars;
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descr.layers = BarDescr;
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descr.step = 1;
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descr.batch = BatchSize;
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descr.optimization = ADAM;
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descr.activation = None;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 3
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defMamba4CastEmbeding;
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prev_count = descr.count = HistoryBars;
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descr.window = 2 * BarDescr;
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uint prev_out = descr.window_out = NSkills;
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{
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uint temp[] = {PeriodSeconds(PERIOD_H1), PeriodSeconds(PERIOD_D1)};
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if(ArrayCopy(descr.windows, temp) < (int)temp.Size())
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return false;
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}
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descr.batch = BatchSize;
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descr.optimization = ADAM;
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descr.activation = None;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 4
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronTimeFoundPatching;
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descr.count = prev_count;
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prev_count = descr.window = Segments;
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descr.variables = prev_out;
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descr.window_out = EmbeddingSize;
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descr.step = 8;
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descr.batch = BatchSize;
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descr.optimization = ADAM;
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descr.activation = None;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 5
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronTimeFoundTransformerUnit;
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descr.count = prev_count;
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descr.window = EmbeddingSize;
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descr.window_out = descr.window / 4;
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{
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int temp[] = {4, 2};
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if(ArrayCopy(descr.heads, temp) < ArraySize(temp))
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return false;
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}
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descr.layers = 3;
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descr.step = 3;
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descr.variables = prev_out;
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descr.batch = BatchSize;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 6
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConvOCL;
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descr.count = 1;
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descr.step = EmbeddingSize;
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prev_count = descr.layers = prev_out;
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descr.window = EmbeddingSize;
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prev_out = descr.window_out = NForecast;
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descr.batch = BatchSize;
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descr.optimization = ADAM;
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descr.activation = SoftPlus;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 7
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronTransposeOCL;
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descr.window = prev_out;
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descr.count = prev_count;
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descr.batch = BatchSize;
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descr.optimization = ADAM;
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descr.activation = None;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 8
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronConvOCL;
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descr.count = prev_out;
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descr.window = prev_count;
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descr.step = prev_count;
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descr.layers = 1;
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prev_out = descr.window_out = BarDescr;
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descr.batch = BatchSize;
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descr.optimization = ADAM;
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descr.activation = TANH;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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prev_count = descr.count;
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//--- layer 9
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronRevInDenormOCL;
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descr.count = prev_count * prev_out;
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descr.layers = 1;
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descr.activation = None;
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if(!encoder.Add(descr))
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{
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delete descr;
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return false;
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}
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//---
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CLayerDescription *latent = encoder.At(LatentLayer);
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//--- Actor
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actor.Clear();
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//--- Input layer
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBaseOCL;
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descr.count = AccountDescr;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!actor.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 1
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronBatchNormOCL;
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descr.count = AccountDescr;
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descr.batch = BatchSize;
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descr.activation = None;
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descr.optimization = ADAM;
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if(!actor.Add(descr))
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{
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delete descr;
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return false;
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}
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//--- layer 2
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if(!(descr = new CLayerDescription()))
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return false;
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descr.type = defNeuronCrossDMHAttention;
|
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{
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uint temp[] = {AccountDescr, // Inputs window
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latent.window // Cross window
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|
};
|
|
if(ArrayCopy(descr.windows, temp) < (int)temp.Size())
|
|
return false;
|
|
}
|
|
{
|
|
uint temp[] = {1, // Inputs units
|
|
latent.variables // Cross units
|
|
};
|
|
if(ArrayCopy(descr.units, temp) < (int)temp.Size())
|
|
return false;
|
|
}
|
|
descr.step = 4; // Heads
|
|
descr.window_out = 32;
|
|
descr.batch = 1e4;
|
|
descr.layers = 3;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!actor.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 3
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.batch = BatchSize;
|
|
descr.activation = TANH;
|
|
descr.optimization = ADAM;
|
|
if(!actor.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 4
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.activation = SoftPlus;
|
|
descr.batch = BatchSize;
|
|
descr.optimization = ADAM;
|
|
if(!actor.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 5
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
prev_count = descr.count = NActions;
|
|
descr.activation = SIGMOID;
|
|
descr.batch = BatchSize;
|
|
descr.optimization = ADAM;
|
|
if(!actor.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- Director
|
|
director.Clear();
|
|
//--- Input layer
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = NActions;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!director.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 1
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBatchNormOCL;
|
|
descr.count = NActions;
|
|
descr.batch = BatchSize;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!director.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 2
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronCrossDMHAttention;
|
|
{
|
|
uint temp[] = {NActions, // Inputs window
|
|
latent.window // Cross window
|
|
};
|
|
if(ArrayCopy(descr.windows, temp) < (int)temp.Size())
|
|
return false;
|
|
}
|
|
{
|
|
uint temp[] = {1, // Inputs units
|
|
latent.variables // Cross units
|
|
};
|
|
if(ArrayCopy(descr.units, temp) < (int)temp.Size())
|
|
return false;
|
|
}
|
|
descr.step = 4; // Heads
|
|
descr.window_out = 32;
|
|
descr.batch = 1e4;
|
|
descr.layers = 3;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!director.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 3
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.batch = BatchSize;
|
|
descr.activation = TANH;
|
|
descr.optimization = ADAM;
|
|
if(!director.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 4
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.activation = TANH;
|
|
descr.batch = BatchSize;
|
|
descr.optimization = ADAM;
|
|
if(!director.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 5
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
prev_count = descr.count = 1;
|
|
descr.activation = SIGMOID;
|
|
descr.batch = BatchSize;
|
|
descr.optimization = ADAM;
|
|
if(!director.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- Critic
|
|
critic.Clear();
|
|
//--- Input layer
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = NActions;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!critic.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 1
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBatchNormOCL;
|
|
descr.count = NActions;
|
|
descr.batch = BatchSize;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!critic.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 2
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronCrossDMHAttention;
|
|
{
|
|
uint temp[] = {NActions, // Inputs window
|
|
latent.window // Cross window
|
|
};
|
|
if(ArrayCopy(descr.windows, temp) < (int)temp.Size())
|
|
return false;
|
|
}
|
|
{
|
|
uint temp[] = {1, // Inputs units
|
|
latent.variables // Cross units
|
|
};
|
|
if(ArrayCopy(descr.units, temp) < (int)temp.Size())
|
|
return false;
|
|
}
|
|
descr.step = 4; // Heads
|
|
descr.window_out = 32;
|
|
descr.batch = 1e4;
|
|
descr.layers = 3;
|
|
descr.activation = None;
|
|
descr.optimization = ADAM;
|
|
if(!critic.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 3
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.batch = BatchSize;
|
|
descr.activation = TANH;
|
|
descr.optimization = ADAM;
|
|
if(!critic.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 4
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
descr.count = LatentCount;
|
|
descr.activation = SoftPlus;
|
|
descr.batch = BatchSize;
|
|
descr.optimization = ADAM;
|
|
if(!critic.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//--- layer 5
|
|
if(!(descr = new CLayerDescription()))
|
|
return false;
|
|
descr.type = defNeuronBaseOCL;
|
|
prev_count = descr.count = 1;
|
|
descr.activation = None;
|
|
descr.batch = BatchSize;
|
|
descr.optimization = ADAM;
|
|
if(!critic.Add(descr))
|
|
{
|
|
delete descr;
|
|
return false;
|
|
}
|
|
//---
|
|
return true;
|
|
}
|
|
#ifndef Study
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool IsNewBar(void)
|
|
{
|
|
static datetime last_bar = 0;
|
|
if(last_bar >= iTime(Symb.Name(), TimeFrame, 0))
|
|
return false;
|
|
//---
|
|
last_bar = iTime(Symb.Name(), TimeFrame, 0);
|
|
return true;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool CloseByDirection(ENUM_POSITION_TYPE type)
|
|
{
|
|
int total = PositionsTotal();
|
|
bool result = true;
|
|
for(int i = total - 1; i >= 0; i--)
|
|
{
|
|
if(PositionGetSymbol(i) != Symb.Name())
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TYPE) != type)
|
|
continue;
|
|
result = (Trade.PositionClose(PositionGetInteger(POSITION_TICKET)) && result);
|
|
}
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool TrailPosition(ENUM_POSITION_TYPE type, double sl, double tp)
|
|
{
|
|
int total = PositionsTotal();
|
|
bool result = true;
|
|
datetime time = TimeCurrent() - 5 * PeriodSeconds(TimeFrame);
|
|
//---
|
|
for(int i = 0; i < total; i++)
|
|
{
|
|
if(PositionGetSymbol(i) != Symb.Name())
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TYPE) != type)
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TIME_UPDATE) > time)
|
|
continue;
|
|
bool modify = false;
|
|
double psl = PositionGetDouble(POSITION_SL);
|
|
double ptp = PositionGetDouble(POSITION_TP);
|
|
switch(type)
|
|
{
|
|
case POSITION_TYPE_BUY:
|
|
if((sl - psl) >= Symb.Point())
|
|
{
|
|
psl = sl;
|
|
modify = true;
|
|
}
|
|
if(MathAbs(tp - ptp) >= Symb.Point())
|
|
{
|
|
ptp = tp;
|
|
modify = true;
|
|
}
|
|
break;
|
|
case POSITION_TYPE_SELL:
|
|
if((psl - sl) >= Symb.Point())
|
|
{
|
|
psl = sl;
|
|
modify = true;
|
|
}
|
|
if(MathAbs(tp - ptp) >= Symb.Point())
|
|
{
|
|
ptp = tp;
|
|
modify = true;
|
|
}
|
|
break;
|
|
}
|
|
if(modify)
|
|
result = (Trade.PositionModify(PositionGetInteger(POSITION_TICKET), psl, ptp) && result);
|
|
}
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool ClosePartial(ENUM_POSITION_TYPE type, double value)
|
|
{
|
|
if(value <= 0)
|
|
return true;
|
|
//---
|
|
for(int i = 0; (i < PositionsTotal() && value > 0); i++)
|
|
{
|
|
if(PositionGetSymbol(i) != Symb.Name())
|
|
continue;
|
|
if(PositionGetInteger(POSITION_TYPE) != type)
|
|
continue;
|
|
double pvalue = PositionGetDouble(POSITION_VOLUME);
|
|
if(pvalue <= value)
|
|
{
|
|
if(Trade.PositionClose(PositionGetInteger(POSITION_TICKET)))
|
|
{
|
|
value -= pvalue;
|
|
i--;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if(Trade.PositionClosePartial(PositionGetInteger(POSITION_TICKET), value))
|
|
value = 0;
|
|
}
|
|
}
|
|
//---
|
|
return (value <= 0);
|
|
}
|
|
#endif
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
vector<float> GetProbTrajectories(STrajectory &buffer[], double lambda)
|
|
{
|
|
ulong total = buffer.Size();
|
|
vector<float> result = vector<float>::Zeros(total);
|
|
vector<float> temp;
|
|
for(ulong i = 0; i < total; i++)
|
|
{
|
|
temp.Assign(buffer[i].States[0].rewards);
|
|
result[i] = temp.Sum();
|
|
if(!MathIsValidNumber(result[i]))
|
|
result[i] = -FLT_MAX;
|
|
}
|
|
float max_reward = result.Max();
|
|
//---
|
|
vector<float> sorted = result;
|
|
bool sort = true;
|
|
int iter = 0;
|
|
while(sort)
|
|
{
|
|
sort = false;
|
|
for(ulong i = 0; i < sorted.Size() - 1; i++)
|
|
if(sorted[i] > sorted[i + 1])
|
|
{
|
|
float temp = sorted[i];
|
|
sorted[i] = sorted[i + 1];
|
|
sorted[i + 1] = temp;
|
|
sort = true;
|
|
}
|
|
iter++;
|
|
}
|
|
//---
|
|
float min = result.Min() - 0.1f * MathAbs(max_reward);
|
|
if(max_reward > min)
|
|
{
|
|
float k = sorted.Percentile(80) - max_reward;
|
|
vector<float> multipl = MathExp(MathAbs(result - max_reward) / (k == 0 ? -1 : k));
|
|
result = (result - min) / (max_reward - min);
|
|
result = result / (result + lambda) * multipl;
|
|
result.ReplaceNan(0);
|
|
}
|
|
else
|
|
result.Fill(1);
|
|
result = result / result.Sum();
|
|
result = result.CumSum();
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
int SampleTrajectory(vector<float> &probability)
|
|
{
|
|
//--- check
|
|
ulong total = probability.Size();
|
|
if(total <= 0)
|
|
return -1;
|
|
//--- randomize
|
|
float rnd = float(MathRand() / 32767.0);
|
|
//--- search
|
|
if(rnd <= probability[0] || total == 1)
|
|
return 0;
|
|
if(rnd > probability[total - 2])
|
|
return int(total - 1);
|
|
int result = int(rnd * total);
|
|
if(probability[result] < rnd)
|
|
while(probability[result] < rnd)
|
|
result++;
|
|
else
|
|
{
|
|
if(result <= 0)
|
|
Sleep(0);
|
|
while(probability[result - 1] >= rnd)
|
|
result--;
|
|
}
|
|
//--- return result
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
class CDeal : public CObject
|
|
{
|
|
public:
|
|
datetime OpenTime;
|
|
datetime CloseTime;
|
|
ENUM_POSITION_TYPE Type;
|
|
double Volume;
|
|
double OpenPrice;
|
|
double StopLos;
|
|
double TakeProfit;
|
|
double point;
|
|
//---
|
|
CDeal(void);
|
|
~CDeal(void) {};
|
|
//---
|
|
vector<float> Action(datetime current, double ask, double bid, int period_seconds);
|
|
};
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
void CDeal::CDeal(void) : OpenTime(0),
|
|
CloseTime(0),
|
|
Type(POSITION_TYPE_BUY),
|
|
Volume(0),
|
|
OpenPrice(0),
|
|
StopLos(0),
|
|
TakeProfit(0),
|
|
point(1e-5)
|
|
{
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
vector<float> CDeal::Action(datetime current, double ask, double bid, int period_seconds)
|
|
{
|
|
vector<float> result = vector<float>::Zeros(NActions);
|
|
if((OpenTime - period_seconds) > current || CloseTime <= current)
|
|
return result;
|
|
//---
|
|
switch(Type)
|
|
{
|
|
case POSITION_TYPE_BUY:
|
|
result[0] = float(Volume);
|
|
if(TakeProfit > 0)
|
|
result[1] = float((TakeProfit - ask) / (MaxTP * point));
|
|
if(StopLos > 0)
|
|
result[2] = float((ask - StopLos) / (MaxSL * point));
|
|
break;
|
|
case POSITION_TYPE_SELL:
|
|
result[3] = float(Volume);
|
|
if(TakeProfit > 0)
|
|
result[4] = float((bid - TakeProfit) / (MaxTP * point));
|
|
if(StopLos > 0)
|
|
result[5] = float((StopLos - bid) / (MaxSL * point));
|
|
break;
|
|
}
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
class CDeals
|
|
{
|
|
protected:
|
|
CArrayObj Deals;
|
|
public:
|
|
CDeals(void) { Deals.Clear(); }
|
|
~CDeals(void) { Deals.Clear(); }
|
|
//---
|
|
bool LoadDeals(string file_name, string symbol, double point);
|
|
vector<float> Action(datetime current, double ask, double bid, int period_seconds);
|
|
};
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool CDeals::LoadDeals(string file_name, string symbol, double point)
|
|
{
|
|
if(file_name == NULL || !FileIsExist(file_name, FILE_COMMON))
|
|
{
|
|
PrintFormat("File %s not exist", file_name);
|
|
return false;
|
|
}
|
|
if(symbol == NULL)
|
|
{
|
|
symbol = _Symbol;
|
|
point = _Point;
|
|
}
|
|
//---
|
|
ResetLastError();
|
|
int handle = FileOpen(file_name, FILE_READ | FILE_ANSI | FILE_CSV | FILE_COMMON, short(';'), CP_ACP);
|
|
if(handle == INVALID_HANDLE)
|
|
{
|
|
PrintFormat("Error of open file %s: %d", file_name, GetLastError());
|
|
return false;
|
|
}
|
|
FileSeek(handle, 0, SEEK_SET);
|
|
while(!FileIsEnding(handle))
|
|
{
|
|
string s = FileReadString(handle);
|
|
datetime open_time = StringToTime(s);
|
|
string type = FileReadString(handle);
|
|
double volume = StringToDouble(FileReadString(handle));
|
|
string deal_symbol = FileReadString(handle);
|
|
double open_price = StringToDouble(FileReadString(handle));
|
|
volume = MathMin(volume, StringToDouble(FileReadString(handle)));
|
|
datetime close_time = StringToTime(FileReadString(handle));
|
|
double close_price = StringToDouble(FileReadString(handle));
|
|
s = FileReadString(handle);
|
|
s = FileReadString(handle);
|
|
s = FileReadString(handle);
|
|
if(StringFind(deal_symbol, symbol, 0) < 0)
|
|
continue;
|
|
//---
|
|
ResetLastError();
|
|
CDeal *deal = new CDeal();
|
|
if(!deal)
|
|
{
|
|
PrintFormat("Error of create new deal object: %d", GetLastError());
|
|
return false;
|
|
}
|
|
deal.OpenTime = open_time;
|
|
deal.CloseTime = close_time;
|
|
deal.OpenPrice = open_price;
|
|
deal.Volume = volume;
|
|
deal.point = point;
|
|
if(type == "Sell")
|
|
{
|
|
deal.Type = POSITION_TYPE_SELL;
|
|
if(close_price < open_price)
|
|
{
|
|
deal.TakeProfit = close_price;
|
|
deal.StopLos = 0;
|
|
}
|
|
else
|
|
{
|
|
deal.TakeProfit = 0;
|
|
deal.StopLos = close_price;
|
|
}
|
|
}
|
|
else
|
|
{
|
|
deal.Type = POSITION_TYPE_BUY;
|
|
if(close_price > open_price)
|
|
{
|
|
deal.TakeProfit = close_price;
|
|
deal.StopLos = 0;
|
|
}
|
|
else
|
|
{
|
|
deal.TakeProfit = 0;
|
|
deal.StopLos = close_price;
|
|
}
|
|
}
|
|
//---
|
|
ResetLastError();
|
|
if(!Deals.Add(deal))
|
|
{
|
|
PrintFormat("Error of add new deal: %d", GetLastError());
|
|
return false;
|
|
}
|
|
}
|
|
//---
|
|
FileClose(handle);
|
|
//---
|
|
return true;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
vector<float> CDeals::Action(datetime current, double ask, double bid, int period_seconds)
|
|
{
|
|
vector<float> result = vector<float>::Zeros(NActions);
|
|
for(int i = 0; i < Deals.Total(); i++)
|
|
{
|
|
CDeal *deal = Deals.At(i);
|
|
if(!deal)
|
|
continue;
|
|
vector<float> action = deal.Action(current, ask, bid, period_seconds);
|
|
result[0] += action[0];
|
|
result[3] += action[3];
|
|
result[1] = MathMax(result[1], action[1]);
|
|
result[2] = MathMax(result[2], action[2]);
|
|
result[4] = MathMax(result[4], action[4]);
|
|
result[5] = MathMax(result[5], action[5]);
|
|
}
|
|
//---
|
|
return result;
|
|
}
|
|
//+------------------------------------------------------------------+
|