It is good to always say it as “the gradient of function with respect to argument to that function” to keep the mathematical nature of things happy, so in this case p.grad will be the gradient of the loss (from loss.backward() - actually the sum of all of them since the beginning or last time you used opt.zero_grad or so) with respect to p.