Skip to content

Use gpytorch's dist function instead of legacy Distance() #1599

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

Use gpytorch's dist function instead of legacy Distance() #1599

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions botorch/models/fully_bayesian.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@
from gpytorch.constraints import GreaterThan
from gpytorch.distributions.multivariate_normal import MultivariateNormal
from gpytorch.kernels import MaternKernel, ScaleKernel
from gpytorch.kernels.kernel import Distance, Kernel
from gpytorch.kernels.kernel import dist, Kernel
from gpytorch.likelihoods.gaussian_likelihood import (
FixedNoiseGaussianLikelihood,
GaussianLikelihood,
Expand All @@ -74,7 +74,7 @@ def matern52_kernel(X: Tensor, lengthscale: Tensor) -> Tensor:
def compute_dists(X: Tensor, lengthscale: Tensor) -> Tensor:
"""Compute kernel distances."""
scaled_X = X / lengthscale
return Distance()._dist(scaled_X, scaled_X, postprocess=False, x1_eq_x2=True)
return dist(scaled_X, scaled_X, x1_eq_x2=True)


def reshape_and_detach(target: Tensor, new_value: Tensor) -> None:
Expand Down