recurrent_decoders.py 文件源码

def recurrent_as_activation_function(self, Wix, Uix, h_tm1, c_tm1, y_tm1):
        """ Implement the recurrent unit as an activation function. This function is called by self.__init__().

        :param Wix: it equals to W^{hx}x_{t}, as it does not relate with recurrent, pre-calculate the value for fast computation
        :type Wix: matrix
        :param h_tm1: contains the hidden activation from previous time step
        :type h_tm1: matrix, each row means a hidden activation vector of a time step
        :param c_tm1: this parameter is not used, just to keep the interface consistent with LSTM
        :returns: h_t is the hidden activation of current time step
        """

        h_t = T.tanh(Wix + T.dot(h_tm1, self.W_hi) + T.dot(y_tm1, self.W_yi) + self.b_i)  #

        # simple recurrent decoder
        #y_t = T.dot(h_t, self.U_hi) + self.b

        # recurrent output and additional input
        y_t = Uix + T.dot(h_t, self.U_hi) + T.dot(y_tm1, self.U_yi) + self.b

        c_t = h_t

        return h_t, c_t, y_t