//+------------------------------------------------------------------+
//| Layer.mqh                                                         |
//|                                                                   |
//| CLayer - neuron container: element construction from a topology   |
//| descriptor or a .nnw stream.                                      |
//|                                                                   |
//| Included from AI\Network.mqh AFTER every class declaration -      |
//| bodies only, no declarations. Relocation is behaviour-neutral by  |
//| construction: nothing here is reachable until Network.mqh ends.   |
//+------------------------------------------------------------------+
#ifndef WARRIOR_AI_IMPL_LAYER_MQH
#define WARRIOR_AI_IMPL_LAYER_MQH
//+------------------------------------------------------------------+
//|                                                                   |
//+------------------------------------------------------------------+
bool CLayer::CreateElementScaled(int index, double weighScale)
  {
   if(index >= m_data_max)
      return false;
//---
   bool result = false;
   CNeuronBase *temp = NULL;
   CNeuronPool *temp_p = NULL;
   CNeuronBaseOCL *temp_ocl = NULL;
   if(iFileHandle <= 0)
     {
      temp = new CNeuron();
      if(CheckPointer(temp) == POINTER_INVALID || !temp.Init(iOutputs, index, SGD, weighScale))
         return false;
      result = true;
     }
   else
     {
      int type = FileReadInteger(iFileHandle);
      switch(type)
        {
         case  defNeuron:
            temp = new CNeuron();
            if(CheckPointer(temp) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            result = temp.Init(iOutputs, index, ADAM);
            break;
         case  defNeuronPool:
            temp_p = new CNeuronPool();
            if(CheckPointer(temp_p) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            if(temp_p.Init(iOutputs, index, 1, 1, 1, ADAM))
              {
               temp = temp_p;
               result = true;
              }
            break;
         case  defNeuronConv:
            temp_p = new CNeuronConv();
            if(CheckPointer(temp_p) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            if(temp_p.Init(iOutputs, index, 1, 1, 1, ADAM))
              {
               temp = temp_p;
               result = true;
              }
            break;
         case  defNeuronLSTM:
            temp_p = new CNeuronLSTM();
            if(CheckPointer(temp_p) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            if(temp_p.Init(iOutputs, index, 1, 1, 1, ADAM))
              {
               temp = temp_p;
               result = true;
              }
            break;
         case  defNeuronBaseOCL:
            temp_ocl = new CNeuronBaseOCL();
            if(CheckPointer(temp_ocl) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            //--- Pure-MQL5 inference (no backend): construct host-only. Load() restores the weights into
            //--- the host buffers and CNeuronBaseOCL::feedForwardCPU() computes on them. The device Init()
            //--- below REQUIRES a backend, so it only runs when one exists (training/optimization/GPU run).
            if(CheckPointer(OpenCL) == POINTER_INVALID && CheckPointer(DirectML) == POINTER_INVALID)
              {
               m_data[index] = temp_ocl;
               return true;
              }
            if(CheckPointer(OpenCL) != POINTER_INVALID
               ? temp_ocl.Init(iOutputs, index, OpenCL, 1, ADAM)
               : temp_ocl.Init(iOutputs, index, DirectML, 1, ADAM))
              {
               m_data[index] = temp_ocl;
               return true;
              }
            break;
         case  defNeuronConvOCL:
           {
            //--- placeholder dims; the real window/step/units are restored by Load() right after
            CNeuronConvOCL *temp_conv = new CNeuronConvOCL();
            if(CheckPointer(temp_conv) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            //--- Pure-MQL5 inference (no backend): construct host-only, Load() fills the host buffers,
            //--- CNeuronConvOCL::feedForwardCPU() computes on them (device Init below needs a backend).
            if(CheckPointer(OpenCL) == POINTER_INVALID && CheckPointer(DirectML) == POINTER_INVALID)
              {
               m_data[index] = temp_conv;
               return true;
              }
            if(CheckPointer(OpenCL) != POINTER_INVALID
               ? temp_conv.Init(iOutputs, index, OpenCL, 1, 1, 1, 1, ADAM)
               : temp_conv.Init(iOutputs, index, DirectML, 1, 1, 1, 1, ADAM))
              {
               m_data[index] = temp_conv;
               return true;
              }
            break;
           }
         case  defNeuronBatchNormOCL:
           {
            //--- Placeholder width of 1; CNeuronBatchNormOCL::Load() replaces both the buffers and the
            //--- whole gamma/beta/statistics block with the real ones, then verifies they agree.
            CNeuronBatchNormOCL *temp_bn = new CNeuronBatchNormOCL();
            if(CheckPointer(temp_bn) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            //--- Pure-MQL5 inference (no backend): construct host-only (see the defNeuronConvOCL note).
            if(CheckPointer(OpenCL) == POINTER_INVALID && CheckPointer(DirectML) == POINTER_INVALID)
              {
               m_data[index] = temp_bn;
               return true;
              }
            if(CheckPointer(OpenCL) != POINTER_INVALID
               ? temp_bn.Init(iOutputs, index, OpenCL, 1, 1, ADAM)
               : temp_bn.Init(iOutputs, index, DirectML, 1, 1, ADAM))
              {
               m_data[index] = temp_bn;
               return true;
              }
            break;
           }
         case  defNeuronPoolOCL:
           {
            CNeuronPoolOCL *temp_pool = new CNeuronPoolOCL();
            if(CheckPointer(temp_pool) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            //--- Pure-MQL5 inference (no backend): construct host-only (see the defNeuronConvOCL note).
            if(CheckPointer(OpenCL) == POINTER_INVALID && CheckPointer(DirectML) == POINTER_INVALID)
              {
               m_data[index] = temp_pool;
               return true;
              }
            if(CheckPointer(OpenCL) != POINTER_INVALID
               ? temp_pool.Init(iOutputs, index, OpenCL, 1, 1, 1, ADAM)
               : temp_pool.Init(iOutputs, index, DirectML, 1, 1, 1, ADAM))
              {
               m_data[index] = temp_pool;
               return true;
              }
            break;
           }
         case  defNeuronLSTMOCL:
           {
            CNeuronLSTMOCL *temp_lstm = new CNeuronLSTMOCL();
            if(CheckPointer(temp_lstm) == POINTER_INVALID)
              {
               result = false;
               break;
              }
            //--- Pure-MQL5 inference (no backend): construct host-only (see the defNeuronConvOCL note).
            if(CheckPointer(OpenCL) == POINTER_INVALID && CheckPointer(DirectML) == POINTER_INVALID)
              {
               m_data[index] = temp_lstm;
               return true;
              }
            if(CheckPointer(OpenCL) != POINTER_INVALID
               ? temp_lstm.Init(iOutputs, index, OpenCL, 1, ADAM)
               : temp_lstm.Init(iOutputs, index, DirectML, 1, ADAM))
              {
               m_data[index] = temp_lstm;
               return true;
              }
            break;
           }
         default:
            result = false;
            break;
        }
     }
   if(result)
      m_data[index] = temp;
//---
   return (result);
  }
//+------------------------------------------------------------------+
//|                                                                   |
//+------------------------------------------------------------------+
CLayer::CLayer(uint outputs = 0, int handle = -1, COpenCLMy *opencl = NULL, CDirectMLMy *directml = NULL)
  {
   iOutputs = outputs;
   iFileHandle = handle;
   OpenCL = opencl;
   DirectML = directml;
  }
//+------------------------------------------------------------------+
//|                                                                   |
//+------------------------------------------------------------------+
bool CLayer::Load(const int file_handle)
  {
   iFileHandle = file_handle;
   if(!CArrayObj::Load(file_handle))
      return false;
   // A corrupt/truncated save can produce a 0-element layer here - CArrayObj::Load itself would
   // still return true for it, so m_data[0] must be guarded before indexing or MQL5 raises an
   // "array out of range" runtime error that aborts the whole CNet::Load call.
   if(Total() <= 0 || CheckPointer(m_data[0]) == POINTER_INVALID)
     {
      Print(__FUNCTION__ + ": layer loaded with no elements (corrupt or truncated save file)");
      return false;
     }
//---
   switch(m_data[0].Type())
     {
      case defNeuronBaseOCL:
      case defNeuronConvOCL:
      case defNeuronPoolOCL:
      case defNeuronLSTMOCL:
      case defNeuronBatchNormOCL:
        {
         CNeuronBaseOCL *temp = m_data[0];
         iOutputs = temp.getConnections();
         break;
        }
      default:
        {
         CNeuronBase *temp = m_data[0];
         iOutputs = temp.getConnections().Total();
         break;
        }
     }
//---
   return true;
  }
#endif