şundan çatallanmış animatedread/Warrior_EA
e4a154aa5e
AI/Network.mqh was 5,805 lines / 18 classes in one file. Investigation found method implementations for several classes (CNeuronBase/Pool/Conv, CNeuronBaseOCL) hand-interleaved across thousands of lines - not safe to split without risky manual reassembly. But 8 classes turned out to be genuinely self-contained (declaration + every method body physically contiguous, and only ever depended upon, never depending on anything declared later): CConnection/CArrayCon, CNeuron, CDirectMLMy (+ its WarriorDML.dll/WarriorCPU.dll #import blocks), CArrayLayer, CLayerDescription, CBufferDouble, and CNeuronConvOCL/CNeuronPoolOCL. Extracted each verbatim, via exact line-range extraction (not manual retyping) to eliminate transcription risk, into its own AI/*.mqh file, included from Network.mqh at the exact point each class used to sit - preserving original declaration order exactly. Mathematically verified byte-for-byte: reconstructing the original file from the 7 new files' bodies + Network.mqh's remaining segments is line-for-line identical to the pre-split git history. Compiled clean (MetaEditor, 0 errors/0 warnings) both before and after. The remaining tangled classes (CNeuronBase, CNeuronPool, CNeuronConv, CNet, CNeuronLSTM, CNeuronBaseOCL, CNeuronConvOCL/PoolOCL's shared base, CNeuronLSTMOCL, COpenCLMy) stay in Network.mqh (now ~4,450 lines) - splitting those safely needs deliberate per-method surgery, deferred to a future dedicated pass rather than rushed into this one. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
100 satır
4,2 KiB
MQL5
100 satır
4,2 KiB
MQL5
//+------------------------------------------------------------------+
|
|
//| NeuronPrimitives.mqh |
|
|
//| AnimateDread |
|
|
//| https://www.mql5.com |
|
|
//+------------------------------------------------------------------+
|
|
//| CConnection/CArrayCon - the per-synapse weight (+ Adam moment) |
|
|
//| storage and its owning array, used by the CPU-only CNeuronBase/ |
|
|
//| CNeuron neuron family (AI\NeuronCPU.mqh) as their fallback last- |
|
|
//| resort weight representation (no DLL import, no OpenCL/DirectML).|
|
|
//| Extracted verbatim out of AI\Network.mqh's own god-file (SOLID |
|
|
//| cleanup) - no logic changes, this is the exact original code. |
|
|
//+------------------------------------------------------------------+
|
|
#include <Arrays\ArrayObj.mqh>
|
|
class CConnection : public CObject
|
|
{
|
|
public:
|
|
double weight;
|
|
double deltaWeight;
|
|
double mt;
|
|
double vt;
|
|
|
|
CConnection(double w) { weight = w; deltaWeight = 0; mt = 0; vt = 0; }
|
|
~CConnection() {};
|
|
//--- methods for working with files
|
|
virtual bool Save(int const file_handle);
|
|
virtual bool Load(int const file_handle);
|
|
virtual int Type(void) const { return defConnect; }
|
|
};
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool CConnection::Save(int file_handle)
|
|
{
|
|
if(file_handle == INVALID_HANDLE)
|
|
return false;
|
|
//---
|
|
if(FileWriteDouble(file_handle, weight) <= 0)
|
|
return false;
|
|
if(FileWriteDouble(file_handle, deltaWeight) <= 0)
|
|
return false;
|
|
if(FileWriteDouble(file_handle, mt) <= 0)
|
|
return false;
|
|
if(FileWriteDouble(file_handle, vt) <= 0)
|
|
return false;
|
|
//---
|
|
return true;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool CConnection::Load(int file_handle)
|
|
{
|
|
if(file_handle == INVALID_HANDLE)
|
|
return false;
|
|
//---
|
|
weight = FileReadDouble(file_handle);
|
|
deltaWeight = FileReadDouble(file_handle);
|
|
mt = FileReadDouble(file_handle);
|
|
vt = FileReadDouble(file_handle);
|
|
//---
|
|
return true;
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
class CArrayCon : public CArrayObj
|
|
{
|
|
public:
|
|
CArrayCon(void) {};
|
|
~CArrayCon(void) {};
|
|
//---
|
|
virtual bool CreateElement(int const index);
|
|
virtual void IncreaseTotal() { m_data_total++; }
|
|
virtual int Type(void) const { return defArrayConnects; }
|
|
};
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|
|
bool CArrayCon::CreateElement(int index)
|
|
{
|
|
if(index < 0 || index >= m_data_max)
|
|
return false;
|
|
//---
|
|
// Not fan-in-scaled like the CNeuronBaseOCL/CNeuronConvOCL/CNeuronLSTMOCL weight-init sites below
|
|
// (see those for the LeCun-uniform rationale) - this legacy per-connection constructor has no
|
|
// visibility into how many neurons share its (sending) layer, and this class family is only ever
|
|
// reached as the deepest last-resort fallback (no DLL import, no OpenCL, no DirectML), not by the
|
|
// live WarriorCPU.dll/WarriorDML.dll/OpenCL tiers this EA actually trains on.
|
|
double weigh = (MathRand() + 1) / 32768.0 - 0.5;
|
|
if(weigh == 0)
|
|
weigh = 0.001;
|
|
m_data[index] = new CConnection(weigh);
|
|
if(CheckPointer(m_data[index]) == POINTER_INVALID)
|
|
return false;
|
|
//---
|
|
return (true);
|
|
}
|
|
//+------------------------------------------------------------------+
|
|
//| |
|
|
//+------------------------------------------------------------------+
|