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If I'm not mistaken, Tensorflow keeps all functions and their gradients' representations, before calculating. That's why you need to give the gradient function representation as well, when you define your custom and advanced function. Also I'm not sure, but I think it can calculate the gradients using iterative algorithms, obviously which give approximate values.

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