attention.py 文件源码

def matrix2att(self, matrix):
        '''Input is vector of size (batch_size,5) in theano terms'''
        g_hat_x = matrix[:,0]
        g_hat_y = matrix[:,1]
        log_delta = matrix[:,2]
        log_sigma_sqr = matrix[:,3]
        log_gamma = matrix[:,4]

        g_x = (self.A + 1.0) / 2.0 * (g_hat_x + 1.0)
        g_y = (self.B + 1.0) / 2.0 * (g_hat_y + 1.0)

        delta = (max(self.A,self.B) - 1.0) / (self.N - 1) * T.exp(log_delta)
        gamma = T.exp(log_gamma).dimshuffle(0, 'x')
        sigma = T.exp(log_sigma_sqr/2.0)

        return g_y, g_x, delta, sigma, gamma