When I try
import torch import pyro.contrib.gp as gp kernel = gp.kernels.RBF(1) likelihood = gp.likelihoods.Gaussian() X = torch.tensor([1., 2., 3., 4., 5.]).double() gpmodel = gp.models.VariationalGP(X, None, kernel, likelihood) gpmodel.set_data(X, None) gpmodel.model()
I invariably get
(tensor([0., 0., 0., 0., 0.], dtype=torch.float64, grad_fn=<AddBackward0>), tensor([1., 1., 1., 1., 1.], dtype=torch.float64, grad_fn=<SumBackward1>))
Is that the expected result @fehiepsi?
Also, I was looking through the tutorials (Gaussian Processes — Pyro Tutorials 1.7.0 documentation) and noticed that even though the
lengthscale is set to 10, the draws from the prior look like white noise:
I would have expected much smoother draws from the prior with that