3 ms·
It's not about smoothness, it's about how to JIT the gradient function. ML libs don't generally do interpolation, partly because it's tricky to vectorize (you h
by svantana 5y ago
It's not about smoothness, it's about how to JIT the gradient function. ML libs don't generally do interpolation, partly because it's tricky to vectorize (you have to search for which segment to use for each element) and partly because most ML practioners don't need it. What I've done in my code is use all the vertices for all the elements, but with weights that are mostly zero. It's pretty fast on GPU because I don't use that many vertices.
- hyperbovine 5y ago"Interpolation" here I think effectively boils down to np.searchsorted() or its equivalent, which is implemented in all the major ML libs (jittable and backpropable).