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

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

Answer 1

[Walter Roberson]

No, the available package would require changes to your data structure.

https://www.mathworks.com/help/deeplearning/ug/deep-learning-with-automatic-differentiation-in-matlab.html

[Miraboreasu]

Any good tutorial for a beginner to use MATLAB for neural netwrorks? except the link you put, thank you!

[Torsten]

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.