You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: glmevfwd.m
    path of file: ./repos/bnt/netlab3.3
    
    the code of the file until where you have to start completion: function [y, extra, invhess] = glmevfwd(net, x, t, x_test, invhess)
%GLMEVFWD Forward propagation with evidence for GLM
%
%	Description
%	Y = GLMEVFWD(NET, X, T, X_TEST) takes a network data structure  NET
%	together with the input X and target T training data and input test
%	data X_TEST. It returns the normal forward propagation through the
%	network Y together with a matrix EXTRA which consists of error bars
%	(variance) for a regression problem or moderated outputs for a
%	classification problem.
%
%	The optional argument (and return value)  INVHESS is the inverse of
%	the network Hessian computed on the training data inputs and targets.
%	Passing it in avoids recomputing it, which can be a significant
%	saving for large training sets.
%

    
function [y, extra, invhess] = glmevfwd(net, x, t, x_test, invhess)
%GLMEVFWD Forward propagation with evidence for GLM
%
%	Description
%	Y = GLMEVFWD(NET, X, T, X_TEST) takes a network data structure  NET
%	together with the input X and target T training data and input test
%	data X_TEST. It returns the normal forward propagation through the
%	network Y together with a matrix EXTRA which consists of error bars
%	(variance) for a regression problem or moderated outputs for a
%	classification problem.
%
%	The optional argument (and return value)  INVHESS is the inverse of
%	the network Hessian computed on the training data inputs and targets.
%	Passing it in avoids recomputing it, which can be a significant
%	saving for large training sets.
%
%	See also
%	FEVBAYES
%

%	Copyright (c) Ian T Nabney (1996-2001)

[y, a] = glmfwd(net, x_test);
if nargin == 4
  [extra, invhess] = fevbayes(net, y, a, x, t, x_test);
else
  [extra, invhess] = fevbayes(net, y, a, x, t, x_test, invhess);
end