def _build_predict(self, Xnew, full_cov=False):
        """
        Compute the mean and variance of the latent function at some new points
        Xnew.
        """
        _, _, Luu, L, _, _, gamma = self._build_common_terms()
        Kus = features.Kuf(self.feature, self.kern, Xnew)  # size  M x Xnew

        w = tf.matrix_triangular_solve(Luu, Kus, lower=True)  # size M x Xnew

        tmp = tf.matrix_triangular_solve(tf.transpose(L), gamma, lower=False)
        mean = tf.matmul(w, tmp, transpose_a=True) + self.mean_function(Xnew)
        intermediateA = tf.matrix_triangular_solve(L, w, lower=True)

        if full_cov:
            var = self.kern.K(Xnew) - tf.matmul(w, w, transpose_a=True) \
                  + tf.matmul(intermediateA, intermediateA, transpose_a=True)
            var = tf.tile(var[None, ...], [self.num_latent, 1, 1])  # P x N x N
        else:
            var = self.kern.Kdiag(Xnew) - tf.reduce_sum(tf.square(w), 0) \
                  + tf.reduce_sum(tf.square(intermediateA), 0)  # size Xnew,
            var = tf.tile(var[:, None], [1, self.num_latent])

        return mean, var
def _build_predict ( self , Xnew , full_cov = False ) : _ , _ , Luu , L , _ , _ , gamma = self . _build_common_terms ( ) Kus = features . Kuf ( self . feature , self . kern , Xnew ) w = tf . matrix_triangular_solve ( Luu , Kus , lower = True ) tmp = tf . matrix_triangular_solve ( tf . transpose ( L ) , gamma , lower = False ) mean = tf . matmul ( w , tmp , transpose_a = True ) + self . mean_function ( Xnew ) intermediateA = tf . matrix_triangular_solve ( L , w , lower = True ) if full_cov : var = self . kern . K ( Xnew ) - tf . matmul ( w , w , transpose_a = True ) + tf . matmul ( intermediateA , intermediateA , transpose_a = True ) var = tf . tile ( var [ None , ... ] , [ self . num_latent , 1 , 1 ] ) else : var = self . kern . Kdiag ( Xnew ) - tf . reduce_sum ( tf . square ( w ) , 0 ) + tf . reduce_sum ( tf . square ( intermediateA ) , 0 ) var = tf . tile ( var [ : , None ] , [ 1 , self . num_latent ] ) return mean , var
Compute the mean and variance of the latent function at some new points
        Xnew.