I mean partial derivatives aren't that complicated if you know normal derivatives, which most people do. And backpropagation isn't too difficult either.

The value of PyTorch lies more in utilizing accelerators like GPUs while offering a nice abstraction. But you can build your own (inefficient) tensor library without too much effort as e.g. Andrej Karpathy has shown in his "NN zero to hero" youtube series.