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 1.8.4 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 lengthscale
.