Simple Derivatives with PyTorch

Derivatives are simple with PyTorch. Like many other neural network libraries, PyTorch includes an automatic differentiation package, autograd, which does the heavy lifting. But derivatives seem especially simple with PyTorch. One of the things I wish I had when first learning about how derivatives and practical implementations of neural networks fit together were concrete examples of using such neural network packages to find simple derivatives and perform calculations on them, separate from computation graphs in neural networks. PyTorch's architecture makes such pedagogical examples easy.