MyLayers.py 文件源码

def get_output_for(self, inputs, **kwargs):
        s_hat_t = inputs[0]
        h_hat_t = inputs[1]
        # s_hat_t = s_hat_t.dimshuffle(1, 0)
        # h_hat_t = h_hat_t.dimshuffle(1, 0)
        H = inputs[2]
        # H = H.dimshuffle(2, 0, 1)
        # H_len = H.shape[-1]
        # z_t 1*none*k
        zt = T.dot(
            self.nonlinearity(
                T.dot(H, self.W_v_to_attenGate) +
                T.dot(
                    T.dot(h_hat_t, self.W_g_to_attenGate).dimshuffle(0, 1, 'x'),
                    T.ones((1, self.num_inputs))
                )
            ),
            self.W_h_to_attenGate
        )[:, :, 0]
        vt = T.dot(
            self.nonlinearity(
                T.dot(
                    s_hat_t, self.W_s_to_attenGate
                ) +
                T.dot(
                    h_hat_t, self.W_g_to_attenGate
                )
            ),
            self.W_h_to_attenGate
        )

        alpha_hat_t = self.nonlinearity_atten(T.concatenate(
            [zt, vt],
            axis=-1
        ))
        feature = T.concatenate(
            [H, s_hat_t.dimshuffle(0, 'x', 1)],
            axis=1
        ).dimshuffle(2, 0, 1)
        c_hat_t = T.sum(alpha_hat_t*feature, axis=-1)
        out = T.dot(
            (c_hat_t.T+h_hat_t), self.W_p
        )

        return nonlinearities.softmax(out)