I am sorry what do you mean by gradient here?

You want finite difference approximation of the gradient? How do you read the tensors? Two different evaluations of the same functions? Or each Tensor corresponds to a single function?
You want gradients with autodiff like we usually do and one tensor was created in a differentiable manner from the other? And you want the gradient for the function that did the mapping from one to the other.