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How to compute the derivative of the neural network?

 Hi,

Once you have trained a neural network, is it possible to obtain a derivative of it? I have a neural network "net" in a structure. I would like to know if there is a routine that will provide the derivatives of net (derivative of its outputs with respect to its inputs).
 
It is probably not difficult, for a feedforward model, there is just matrix multiplications and sigmoid functions, but it would be nice to have a routine that will do that directly on "net".



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Differentiate to obtain dyi/dxn
y = b2 + LW*h
h = tanh(b1+IW*x)
or, with tensor notation(i.e., summation over repeated indices),
yi = b2i + Lwij*hj
hj = tanh(b1j + IWjk*xk)
Now just use the chain rule.

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