package org.ea.javacnn.layers;

import org.ea.javacnn.data.BackPropResult;
import org.ea.javacnn.data.DataBlock;
import org.ea.javacnn.data.OutputDefinition;
import java.io.Serializable; 
import java.util.ArrayList;
import java.util.List;

/**
 * This is a layer of neurons that applies the non-saturating activation
 * function f(x)=max(0,x). It increases the nonlinear properties of the
 * decision function and of the overall network without affecting the
 * receptive fields of the convolution layer.
 *
 * @author Daniel Persson (mailto.woden@gmail.com)
 */
public class RectifiedLinearUnitsLayer implements Layer,Serializable {
    private DataBlock in_act, out_act;

    @Override
    public DataBlock forward(DataBlock db, boolean training) {
        this.in_act = db;
        DataBlock V2 = db.clone();
        int N = db.getWeights().length;
        double[] V2w = V2.getWeights();
        for(int i=0; i getBackPropagationResult() {
        return new ArrayList<>();
    }
}