Higher order derivative by 'dlgradient'

Hi

I am currently coding custom deep learning, but the process stopped at the higher derivative.

I am curious about how to make a higher derivative through dlgradient.

Alternatively, you are welcome to suggest a way to do higher derivatives in matlab.

For example, how to get ddydxx in the following example.

-----------------------------------------------------------------------------------------------------------------------

Code

clc,clear,close all

x=3;

x0=dlarray(x);

[fval,gradval,ggradval] = dlfeval(@Myfunc,x0);

function [fval,gradval,ggradval] = Myfunc(x)

y = 100*(3*x - 7*x.^2).^2;

dydx=dlgradient(y,x,'RetainData',true);

ddydxx=dlgradient(dydx,x);

end

-----------------------------------------------------------------------------------------------------------------------

Error

Error using dlfeval (line 43)

Value to differentiate must be a traced dlarray scalar.

Error in gradtest (line 7)

[fval,gradval,dd] = dlfeval(@Myfunc,x0,y);

-----------------------------------------------------------------------------------------------------------------------

Thanks for reading my question.

[Walter Roberson]

What is the difference between this and https://www.mathworks.com/matlabcentral/answers/745857-how-higher-derivative-by-dlgradient-or-higher-derivative-in-matlab?s_tid=srchtitle and https://www.mathworks.com/matlabcentral/answers/746512-how-higher-derivative-by-dlgradient-or-higher-derivative-in-matlab?s_tid=srchtitle ?

[jaehong kim]

i am sorry...

I just posted to update the question. Sorry for violating the community rules. I'll be careful.