bp: refactored

include/NeuralNetwork/Learning/BackPropagation.h

@@ -37,6 +37,7 @@ namespace Learning {
 
 			void setMomentumWeight(const float& m) {
 				momentumWeight=m;
+				resize();
 			}
 
 			float getWeightDecay() const {
@@ -47,6 +48,14 @@ namespace Learning {
 				weightDecay=wd;
 			}
 
+			std::size_t getBatchSize() const {
+				return batchSize;
+			}
+
+			void setBatchSize(std::size_t size) {
+				batchSize = size;
+			}
+
 		protected:
 
 			virtual inline void resize() {
@@ -58,25 +67,40 @@ namespace Learning {
 						slopes[i].resize(network[i].size());
 				}
 
-				if(lastDeltas.size()!=network.size())
-					lastDeltas.resize(network.size());
+				if(deltas.size() != network.size())
+					deltas.resize(network.size());
 
-				for(std::size_t i=0; i < network.size(); i++) {
-					if(lastDeltas[i].size()!=network[i].size()) {
-						lastDeltas[i].resize(network[i].size());
+				bool resized = false;
 
-						for(std::size_t j = 0; j < lastDeltas[i].size(); j++) {
-							lastDeltas[i][j] = 0.0;
+				for(std::size_t i = 0; i < network.size(); i++) {
+					if(deltas[i].size() != network[i].size()) {
+						deltas[i].resize(network[i].size());
+						resized = true;
+
+						if(i > 0) {
+							for(std::size_t j = 0; j < deltas[i].size(); j++) {
+								deltas[i][j].resize(network[i - 1].size());
+								std::fill(deltas[i][j].begin(),deltas[i][j].end(),0.0);
+							}
 						}
 					}
 				}
-				deltas= lastDeltas;
+
+				if(momentumWeight > 0.0 && (resized || lastDeltas.size() != deltas.size())) {
+					lastDeltas = deltas;
+				}
 			}
 
-			virtual void updateWeights(const std::vector<float> &input);
+			virtual void computeDeltas(const std::vector<float> &input);
+
+			void updateWeights();
 
 			virtual void computeSlopes(const std::vector<float> &expectation);
 
+			virtual void endBatch() {
+
+			}
+
 			FeedForward::Network &network;
 
 			CorrectionFunction::CorrectionFunction *correctionFunction;
@@ -87,9 +111,13 @@ namespace Learning {
 
 			float weightDecay = 0.0;
 
+			std::size_t batchSize = 1;
+			std::size_t currentBatchSize = 0;
+
 			std::vector<std::vector<float>> slopes;
-			std::vector<std::vector<float>> deltas;
-			std::vector<std::vector<float>> lastDeltas;
+			std::vector<std::vector<std::vector<float>>> deltas = {};
+			std::vector<std::vector<std::vector<float>>> lastDeltas = {};
+
 	};
 }
 }