core.py 文件源码

def backward_compute(self):
        m = np.size(self.images,0)
        self.delta = self.delta.reshape(m,self.channel,self.height,self.width)
        newDelta = np.zeros([m,self.last_layer.channel,self.last_layer.height,self.last_layer.width])
        for i in range(m):
            for j in range(self.channel):
                for h in range(self.height):
                    for w in range(self.width):
                        tmpLoc = self.maxIndex[i,j,h*self.width+w]
                        relativeH = tmpLoc//self.squareSize
                        relativeW = tmpLoc - relativeH * self.squareSize
                        lastW = w*self.stride+relativeW
                        lastH = h*self.stride+relativeH
                        newDelta[i,j,lastH,lastW] += self.delta[i,j,h,w]
        self.last_layer.delta = newDelta
        pass