Get input/output gradient of neural network
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Matlab's built in functions in the NN toolbox seem to provide a good set of options for getting the gradient of the network performance wrt the network parameters. Is there a way to get the gradient of the network output with respect to the network input?
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Mahesh Taparia
2020-9-14
Hi
In general, in any neural network, the network tries to learn the weights which can reduce the cost/ loss function. The gradients are updated iteratively by using the derivative of loss function with respect to weights.
Usually for a fix input, calculating gradients of loss with respect to input is not meaningful because if input is fix, then d(loss)/d(Input) is not defined. If the network is feed with 2 different input sequence, in this case you can find the gradient by calculating (Loss2-Loss1)/(X2-X1), where Loss is the value of network loss with respect to input X. There is no use of this while training the network.
Hope it will helps!
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David Leather
2020-11-24
编辑:David Leather
2020-11-24
This seems like an oversight. When applying the trained neural network to other applications, it is essential to be able to evaluate the gradient wrt to the output of the neural network, and not the loss function....
Ruyue Yang
2021-7-22
Get the gradient dy/dx can be really trick for the trained multi-layer neural network (not that deep, maybe 3 or 4 layer). Such function can help a lot for the network's various application.
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