If you wrap your Function's backward method with this wrapper, the Tensors that you will get as input will never require gradients and you don’t have to write a backward function that computes the gradients in a differentiable manner. For example, you can use other libraries to do the computation.
If you try to backward through the backward pass of such Function, an error will be raised stating that this Function is only differentiable once.