Skip to content

Restore the previous autograd setting #49

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

Open
martenlienen wants to merge 1 commit into
base: main
Choose a base branch
from
Open

Restore the previous autograd setting #49

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
5 changes: 3 additions & 2 deletions geomloss/sinkhorn_divergence.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -175,6 +175,7 @@ def sinkhorn_loop(
C_xxs, C_yys = [C_xxs], [C_yys]
C_xys, C_yxs = [C_xys], [C_yxs]

prev_autograd = torch.is_grad_enabled()
torch.autograd.set_grad_enabled(False)

k = 0 # Scale index; we start at the coarsest resolution available
Expand Down Expand Up @@ -219,7 +220,7 @@ def sinkhorn_loop(
C_xy_, C_yx_ = C_xys[k + 1], C_yxs[k + 1]

last_extrapolation = False # No need to re-extrapolate after the loop
torch.autograd.set_grad_enabled(True)
torch.autograd.set_grad_enabled(prev_autograd)

else: # It's worth investing some time on kernel truncation...

Expand Down Expand Up @@ -277,7 +278,7 @@ def sinkhorn_loop(
C_xx, C_yy = C_xx_, C_yy_
C_xy, C_yx = C_xy_, C_yx_

torch.autograd.set_grad_enabled(True)
torch.autograd.set_grad_enabled(prev_autograd)

if last_extrapolation:
# Last extrapolation, to get the correct gradients:
Expand Down