convnade.py 文件源码

def nll_of_x_given_o(self, input, ordering):
        """ Returns the theano graph that computes $-ln p(\bx|o)$.

        Parameters
        ----------
        input: 1D vector
            One image with shape (nb_channels * images_height * images_width).

        ordering: 1D vector of int
            List of pixel indices representing the input ordering.
        """

        D = int(np.prod(self.image_shape))
        mask_o_d = T.zeros((D, D), dtype=theano.config.floatX)
        mask_o_d = T.set_subtensor(mask_o_d[T.arange(D), ordering], 1.)

        mask_o_lt_d = T.cumsum(mask_o_d, axis=0)
        mask_o_lt_d = T.set_subtensor(mask_o_lt_d[1:], mask_o_lt_d[:-1])
        mask_o_lt_d = T.set_subtensor(mask_o_lt_d[0, :], 0.)

        input = T.tile(input[None, :], (D, 1))
        nll = -T.sum(self.lnp_x_o_d_given_x_o_lt_d(input, mask_o_d, mask_o_lt_d))
        return nll