AttentionNet.py 文件源码

def get_output_for(self, arguments, **kwargs):
        input, hprev, Cprev = arguments
        i = nl.sigmoid(self.Wi * input + self.Ui* hprev + self.bi)
        cand = nl.tanh(self.Wc *input + self.Uc * hprev + self.bc)
        f = nl.sigmoid(self.Wf*input + self.Uf*hprev + self.bf)
        C = i*cand + f * Cprev
        o = nl.sigmoid(self.Wo*input + self.Uo*hprev + self.Vo*C + self.bo)
        h = o*nl.tanh(C)
        return h, C