-
Notifications
You must be signed in to change notification settings - Fork 98
[WIP][BUG] Fix CAGRA search recall with a graph built by NN Descent #819
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.
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
base: branch-25.06
Are you sure you want to change the base?
Conversation
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Thank you @enp1s0 for this PR! Looks good overall, I have just one request to clarify the expectations for the random graph.
@@ -829,36 +830,29 @@ void GnndGraph<Index_t>::sample_graph_new(InternalID_t<Index_t>* new_neighbors, | |||
template <typename Index_t> | |||
void GnndGraph<Index_t>::init_random_graph() |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Could you add a docstring to describe what properties the random graph is expected to have? What is ensured by the current PR to fix the low recall issue? E.g. is it guaranteed to be fully connected?
This PR addresses an unexpected low recall issue in the CAGRA search with a graph generated by NN Descent.
For that, it updates the initial NN Descent graph generation so that all indices are included, whereas some nodes are not found in the branch-25.06 implementation.
This PR also makes the following changes: