Vratene na rekurenciu len na spodnej vrstve

mhozza · May 27, 2012 · 5fc5ffb · 5fc5ffb
1 parent edc53f6
commit 5fc5ffb
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Showing 4 changed files with 15 additions and 23 deletions.
diff --git a/NeuralNet/Makefile b/NeuralNet/Makefile
@@ -1,6 +1,6 @@
 #############################################################################
 # Makefile for building: NeuralNet
-# Generated by qmake (2.01a) (Qt 4.8.1) on: Wed May 23 17:02:40 2012
+# Generated by qmake (2.01a) (Qt 4.8.1) on: Sun May 27 20:21:49 2012
 # Project:  NeuralNet.pro
 # Template: app
 # Command: /usr/bin/qmake-qt4 -spec /usr/share/qt4/mkspecs/linux-g++ -o Makefile NeuralNet.pro

diff --git a/NeuralNet/distributedrecurrentnetwork.cpp b/NeuralNet/distributedrecurrentnetwork.cpp
@@ -17,28 +17,22 @@
 
 #include "distributedrecurrentnetwork.h"
 #include "distributedrecurrentlayer.h"
-#include "recurrentlayer.h"
 
 using namespace NeuralNET;
 
-DistributedRecurrentNetwork::DistributedRecurrentNetwork(unsigned layerCount, unsigned sizes[], unsigned firstLayerW, unsigned firstLayerH, unsigned dimensionW, unsigned dimensionH, float alpha)    
+DistributedRecurrentNetwork::DistributedRecurrentNetwork(unsigned layerCount, unsigned sizes[], unsigned firstLayerW, unsigned firstLayerH, unsigned dimensionW, unsigned dimensionH, float alpha)
+    :RecurrentNetwork(0)
 {
     layers.resize(layerCount);
     for(unsigned i = 0; i< layers.size();i++)
     {
       if(i==0)
       {
-//          if(i==recurrentLayerIndex)
-              layers[i] = new DistributedRecurrentLayer(sizes[i]/(firstLayerW*firstLayerH),firstLayerW,firstLayerH , dimensionW, dimensionH, alpha);
-//          else
-//              layers[i] = new DistributedNeuralLayer(sizes[i]/(firstLayerW*firstLayerH),firstLayerW,firstLayerH , dimensionW, dimensionH, alpha);
+        layers[i] = new DistributedRecurrentLayer(sizes[i]/(firstLayerW*firstLayerH),firstLayerW,firstLayerH , dimensionW, dimensionH, alpha);
       }
       else
       {
-//          if(i==recurrentLayerIndex)
-              layers[i] = new RecurrentLayer(sizes[i], sizes[i-1], alpha);
-//          else
-//              layers[i] = new NeuralLayer(sizes[i], sizes[i-1], alpha);
+        layers[i] = new NeuralLayer(sizes[i], sizes[i-1], alpha);
       }
     }
 }
diff --git a/NeuralNet/recurrentnetwork.cpp b/NeuralNet/recurrentnetwork.cpp
@@ -19,7 +19,8 @@
 
 using namespace NeuralNET;
 
-RecurrentNetwork::RecurrentNetwork(unsigned layerCount, unsigned sizes[], unsigned dimension, float alpha)
+RecurrentNetwork::RecurrentNetwork(unsigned layerCount, unsigned sizes[], unsigned dimension, float alpha, unsigned recurrentLayerIndex)
+    :recurrentLayerIndex(recurrentLayerIndex)
 {
     layers.resize(layerCount);
     for(unsigned i = 0; i< layers.size();i++)
@@ -37,16 +38,10 @@ RecurrentNetwork::RecurrentNetwork(unsigned layerCount, unsigned sizes[], unsign
 
 void RecurrentNetwork::update()
 {
-  for(unsigned i = 0; i< layers.size();i++)
-  {
-    dynamic_cast<RecurrentLayer*>(layers[i])->update();
-  }
+    dynamic_cast<RecurrentLayer*>(layers[recurrentLayerIndex])->update();
 }
 
 void RecurrentNetwork::reset()
 {
-  for(unsigned i = 0; i< layers.size();i++)
-  {
-    dynamic_cast<RecurrentLayer*>(layers[i])->reset();
-  }
+    dynamic_cast<RecurrentLayer*>(layers[recurrentLayerIndex])->reset();
 }
diff --git a/NeuralNet/recurrentnetwork.h b/NeuralNet/recurrentnetwork.h
@@ -25,11 +25,14 @@ namespace NeuralNET {
 
 class RecurrentNetwork : public NeuralNetwork
 {
-protected:
     unsigned recurrentLayerIndex;
-    RecurrentNetwork() {}
+protected:
+    RecurrentNetwork(unsigned recurrentLayerIndex = 0)
+    {
+        this->recurrentLayerIndex = recurrentLayerIndex;
+    }
 public:
-    RecurrentNetwork(unsigned layerCount, unsigned sizes[], unsigned dimension, float alpha = 0.25);
+    RecurrentNetwork(unsigned layerCount, unsigned sizes[], unsigned dimension, float alpha = 0.25, unsigned recurrentLayerIndex = 0);
     void update();
     void reset();
 };