Looking for an Auto Differentiation package can be easily used as a function

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I construct a neural network in MATLAB using the basic array since I have no experience in the neural network toolbox. Now I need to take the derivative of all the parameters, like weight, bias, which are inside the activation function.
Is there any package (library) in MATLAB that can help me to do the auto differentiation without changing my basic data structure?
clc
clear
global stackw
stackw=1;
Ninput=2;
Noutput=2;
Nneuron=3; % each layer
Nlayers=3; % hidden layer
inputdata=ones(Ninput,1);
NNstruc=[];
NNstruc(1)=Ninput;
NNstruc(2:(Nlayers+1))=Nneuron;
NNstruc=[NNstruc,Noutput];
wsize=sum(NNstruc(1:(end-1)).*NNstruc(2:end));
bsize=Nlayers+1;
wset=rand(wsize,1);
bset=rand(bsize,1);
for i=1:(length(NNstruc)-1)
temp=NNtrack(inputdata, NNstruc, wset, i);
temp=logsig(temp+bset(i));
inputdata=temp;
end
function [output] = NNtrack(x, NNconfig, w, index)
global stackw;
x=x(:);
current=NNconfig(index);
next=NNconfig(index+1);
Nw=current*next;
Nb=next;
wtemp=reshape(w(stackw:(stackw+Nw-1)),[next current]);
stackw=stackw+Nw;
temp=wtemp*x;
output =wtemp*x;
end

Answers (1)

Walter Roberson
Walter Roberson on 3 May 2022
Edited: Walter Roberson on 4 May 2022
No, the available package would require changes to your data structure.
  2 Comments
Torsten
Torsten on 3 May 2022
So you don't lack theoretical knowledge about neural networks, but you want to gain knowledge on how to use the Neural Network Toolbox ? Then usually its documentation together with the examples provided is the best tutorial.

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