package org.dromara.easyai.rnnNerveEntity;

import org.dromara.easyai.matrixTools.Matrix;
import org.dromara.easyai.i.ActiveFunction;
import org.dromara.easyai.i.OutBack;

import java.util.Map;

/**
 * @author lidapeng
 * 隐层神经元
 * @date 9:30 上午 2019/12/21
 */
public class HiddenNerve extends Nerve {
    private final int depth;//所处深度

    public HiddenNerve(int id, int depth, int upNub, int downNub, float studyPoint,
                       boolean init, ActiveFunction activeFunction, int rzType, float lParam, int rnnOutNumber) throws Exception {//隐层神经元
        super(id, upNub, "HiddenNerve", downNub, studyPoint,
                init, activeFunction, rzType, lParam, rnnOutNumber);
        this.depth = depth;
    }

    @Override
    public void input(long eventId, float parameter, boolean isKernelStudy, Map<Integer, Float> E
            , OutBack outBack, boolean isEmbedding, Matrix rnnMatrix) throws Exception {//接收上一层的输入
        boolean allReady = insertParameter(eventId, parameter, isEmbedding);
        if (allReady) {//参数齐了，开始计算 sigma - threshold
            if (isEmbedding && !isKernelStudy) {
                outBack.getWordVector(getId(), getWOne(eventId));
                destoryParameter(eventId);
            } else {
                float sigma = calculation(eventId, isEmbedding);
                float out = activeFunction.function(sigma);//激活函数输出数值
                if (rnnMatrix != null) {//rnn 1改输出值，2查看是否需要转向
                    out = out + rnnMatrix.getNumber(depth, getId() - 1);
                }
                if (isKernelStudy) {
                    outNub = out;
                } else {
                    destoryParameter(eventId);
                }
                if (rnnMatrix != null && rnnMatrix.getX() == depth + 1) {//转向输出
                    sendRnnMessage(eventId, out, isKernelStudy, E, outBack, false, rnnMatrix);
                } else {
                    sendMessage(eventId, out, isKernelStudy, E, outBack, false, rnnMatrix);
                }
            }
        }
    }

}