Skip to content

fix warnings #26

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
etienne87 wants to merge 1 commit into
base: main
Choose a base branch
from
Open

fix warnings #26

Show file tree
Hide file tree
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
2 changes: 1 addition & 1 deletion keymorph/keypoint_aligners.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -268,7 +268,7 @@ def __init__(
# Note we flip the order of the points here
if use_checkpoint:
self.inverse_theta = checkpoint.checkpoint(
self.fit, points_f, points_m, lmbda, w
self.fit, points_f, points_m, lmbda, w, use_reentrant=False
)
else:
self.inverse_theta = self.fit(points_f, points_m, lmbda, weights=w)
Expand Down
2 changes: 1 addition & 1 deletion keymorph/model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -183,7 +183,7 @@ def forward(self, img_f, img_m, transform_type="affine", **kwargs):
if self.weight_keypoints == "power":
if self.use_checkpoint:
weights = checkpoint.checkpoint(
self.weight_by_power, feat_f, feat_m
self.weight_by_power, feat_f, feat_m, use_reentrant=False
)
else:
weights = self.weight_by_power(feat_f, feat_m)
Expand Down
4 changes: 2 additions & 2 deletions keymorph/utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -251,7 +251,7 @@ def convert_points_norm2voxel(points, grid_sizes):
Returns:
Array of points in voxel space.
"""
grid_sizes = torch.tensor(grid_sizes).to(points.device)
grid_sizes = torch.as_tensor(grid_sizes).to(points.device)
assert grid_sizes.shape[-1] == points.shape[-1], "Dimensions don't match"
translated_points = points + 1
scaled_points = (translated_points * grid_sizes) / 2
Expand All @@ -270,7 +270,7 @@ def convert_points_voxel2norm(points, grid_sizes):
Returns:
Array of points in the normalized space [-1, 1].
"""
grid_sizes = torch.tensor(grid_sizes).to(points.device)
grid_sizes = torch.as_tensor(grid_sizes).to(points.device)
assert grid_sizes.shape[-1] == points.shape[-1], "Dimensions don't match"
rescaled_points_shifted = points + 0.5
normalized_points = (2 * rescaled_points_shifted / grid_sizes) - 1
Expand Down