function g = glmderiv(net, x)%GLMDERIV Evaluate derivatives of GLM outputs with respect to weights.%%	Description%	G = GLMDERIV(NET, X) takes a network data structure NET and a matrix%	of input vectors X and returns a three-index matrix mat{g} whose  I,%	J, K element contains the derivative of network output K with respect%	to weight or bias parameter J for input pattern I. The ordering of%	the weight and bias parameters is defined by GLMUNPAK.%%	Copyright (c) Ian T Nabney (1996-2001)% Check arguments for consistencyerrstring = consist(net, 'glm', x);if ~isempty(errstring)    error(errstring);endndata = size(x, 1);if isfield(net, 'mask')  nwts = size(find(net.mask), 1);  temp = zeros(1, net.nwts);else  nwts = net.nwts;endg = zeros(ndata, nwts, net.nout);temp = zeros(net.nwts, net.nout);for n = 1:ndata    % Weight matrix w1    temp(1:(net.nin*net.nout), :) = kron(eye(net.nout), (x(n, :))');    % Bias term b1    temp(net.nin*net.nout+1:end, :) = eye(net.nout);    if isfield(net, 'mask')	g(n, :, :) = temp(logical(net.mask));    else	g(n, :, :) = temp;    endend